tangyx/MetaQA_overall · Datasets at Hugging Face

data_source stringclasses 1 value	prompt stringlengths 1.02k 13.9k	ability stringclasses 1 value	reward_model dict	extra_info dict
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24004, 10 21931, 1941 31486, 1970 724, 1979 25221, 1981 3085, A LITTLE PRINCESS 12649, A LITTLE ROMANCE 21158, A TOUCH OF CLASS 1216, AMERICATHON 36833, BARBRA STREISAND 34744, BEING THERE 23022, BOARDING SCHOOL 16452, BORN TO WIN 37601, BREAKING AWAY 5800, CARBON COPY 13302, CHAPTER TWO 38678, CHILLY SCENES OF WINTER 30463, COMEDY 36212, DRAMA 19367, ESCAPE TO ATHENA 9048, EVIL 9130, FUN WITH DICK AND JANE 19579, GEORGE SEGAL 10481, GLENDA JACKSON 35760, H.O.T.S. 20263, HAIR 24681, LOOK WHO'S TALKING 2781, LOST AND FOUND 11331, LOVE AT FIRST BITE 34700, LOVING 33790, MANHATTAN 6108, MEATBALLS 27102, MELVIN FRANK 26484, MORE AMERICAN GRAFFITI 6773, REAL LIFE 22107, ROCK 'N' ROLL HIGH SCHOOL 27231, STARTING OVER 16018, THE APPLE DUMPLING GANG RIDES AGAIN 28510, THE FRISCO KID 32636, THE HOT ROCK 19104, THE IN-LAWS 33024, THE JERK 4091, THE LADY VANISHES 32382, THE MAIN EVENT 17527, THE MIRROR HAS TWO FACES 12809, THE MUPPET MOVIE 2080, THE OWL AND THE PUSSYCAT 31851, THE PRISONER OF ZENDA 26036, THE TEMPEST 31435, UNCLE MARIN, THE BILLIONAIRE 28231, WHERE'S POPPA? 14695, WHO IS KILLING THE GREAT CHEFS OF EUROPE? 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 22774, WISE BLOOD src, edge_attr, dst 24004, has_genre, 30463 24004, release_year, 724 21931, has_genre, 30463 21931, release_year, 724 25221, has_genre, 30463 3085, has_genre, 36212 3085, has_tags, 23022 12649, has_genre, 30463 12649, release_year, 724 21158, directed_by, 27102 21158, has_genre, 30463 21158, starred_actors, 19579 21158, starred_actors, 10481 21158, written_by, 27102 1216, has_genre, 30463 1216, release_year, 724 34744, has_genre, 30463 34744, release_year, 724 16452, has_genre, 30463 16452, starred_actors, 19579 37601, has_genre, 30463 37601, release_year, 724 5800, has_genre, 30463 5800, release_year, 25221 5800, starred_actors, 19579 13302, has_genre, 30463 13302, release_year, 724 38678, has_genre, 30463 38678, release_year, 724 19367, has_genre, 30463 19367, release_year, 724 9048, has_genre, 36212 9048, has_tags, 23022 9130, has_genre, 30463 9130, starred_actors, 19579 35760, has_genre, 30463 35760, release_year, 724 20263, has_genre, 30463 20263, release_year, 724 24681, has_genre, 30463 24681, has_tags, 30463 24681, starred_actors, 19579 2781, directed_by, 27102 2781, release_year, 724 2781, starred_actors, 19579 2781, starred_actors, 10481 2781, written_by, 27102 11331, has_genre, 30463 11331, release_year, 724 34700, has_genre, 30463 34700, release_year, 31486 34700, starred_actors, 19579 33790, has_genre, 30463 33790, has_tags, 30463 33790, release_year, 724 6108, has_genre, 30463 6108, release_year, 724 26484, has_genre, 30463 26484, release_year, 724 6773, has_genre, 30463 6773, release_year, 724 22107, has_genre, 30463 22107, release_year, 724 27231, has_genre, 30463 27231, release_year, 724 16018, has_genre, 30463 16018, release_year, 724 28510, has_genre, 30463 28510, release_year, 724 32636, has_genre, 30463 32636, starred_actors, 19579 19104, has_genre, 30463 19104, release_year, 724 33024, has_genre, 30463 33024, release_year, 724 4091, has_genre, 30463 4091, release_year, 724 32382, has_genre, 30463 32382, release_year, 724 17527, directed_by, 36833 17527, has_genre, 30463 17527, has_genre, 36212 17527, has_tags, 36833 17527, starred_actors, 36833 17527, starred_actors, 19579 12809, has_genre, 30463 12809, release_year, 724 2080, has_genre, 30463 2080, release_year, 31486 2080, starred_actors, 36833 2080, starred_actors, 19579 31851, has_genre, 30463 31851, release_year, 724 26036, has_genre, 30463 26036, release_year, 724 31435, has_genre, 30463 31435, release_year, 724 28231, has_genre, 30463 28231, release_year, 31486 28231, starred_actors, 19579 14695, has_genre, 30463 14695, starred_actors, 19579 35212, has_genre, 36212 35212, starred_actors, 19579 22774, has_genre, 30463 22774, release_year, 724 Question: In what context are BOARDING SCHOOL, GEORGE SEGAL, and THE MUPPET MOVIE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BOARDING SCHOOL", "GEORGE SEGAL", "THE MUPPET MOVIE" ], "valid_edges": [ [ "10", "has_genre", "COMEDY" ], [ "10", "release_year", "1979" ], [ "1941", "has_genre", "COMEDY" ], [ "1941", "release_year", "1979" ], [ "1981", "has_genre", "COMEDY" ], [ "A LITTLE PRINCESS", "has_genre", "DRAMA" ], [ "A LITTLE PRINCESS", "has_tags", "BOARDING SCHOOL" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "release_year", "1979" ], [ "A TOUCH OF CLASS", "directed_by", "MELVIN FRANK" ], [ "A TOUCH OF CLASS", "has_genre", "COMEDY" ], [ "A TOUCH OF CLASS", "starred_actors", "GEORGE SEGAL" ], [ "A TOUCH OF CLASS", "starred_actors", "GLENDA JACKSON" ], [ "A TOUCH OF CLASS", "written_by", "MELVIN FRANK" ], [ "AMERICATHON", "has_genre", "COMEDY" ], [ "AMERICATHON", "release_year", "1979" ], [ "BEING THERE", "has_genre", "COMEDY" ], [ "BEING THERE", "release_year", "1979" ], [ "BORN TO WIN", "has_genre", "COMEDY" ], [ "BORN TO WIN", "starred_actors", "GEORGE SEGAL" ], [ "BREAKING AWAY", "has_genre", "COMEDY" ], [ "BREAKING AWAY", "release_year", "1979" ], [ "CARBON COPY", "has_genre", "COMEDY" ], [ "CARBON COPY", "release_year", "1981" ], [ "CARBON COPY", "starred_actors", "GEORGE SEGAL" ], [ "CHAPTER TWO", "has_genre", "COMEDY" ], [ "CHAPTER TWO", "release_year", "1979" ], [ "CHILLY SCENES OF WINTER", "has_genre", "COMEDY" ], [ "CHILLY SCENES OF WINTER", "release_year", "1979" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "ESCAPE TO ATHENA", "release_year", "1979" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "has_tags", "BOARDING SCHOOL" ], [ "FUN WITH DICK AND JANE", "has_genre", "COMEDY" ], [ "FUN WITH DICK AND JANE", "starred_actors", "GEORGE SEGAL" ], [ "H.O.T.S.", "has_genre", "COMEDY" ], [ "H.O.T.S.", "release_year", "1979" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "release_year", "1979" ], [ "LOOK WHO'S TALKING", "has_genre", "COMEDY" ], [ "LOOK WHO'S TALKING", "has_tags", "COMEDY" ], [ "LOOK WHO'S TALKING", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "directed_by", "MELVIN FRANK" ], [ "LOST AND FOUND", "release_year", "1979" ], [ "LOST AND FOUND", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "starred_actors", "GLENDA JACKSON" ], [ "LOST AND FOUND", "written_by", "MELVIN FRANK" ], [ "LOVE AT FIRST BITE", "has_genre", "COMEDY" ], [ "LOVE AT FIRST BITE", "release_year", "1979" ], [ "LOVING", "has_genre", "COMEDY" ], [ "LOVING", "release_year", "1970" ], [ "LOVING", "starred_actors", "GEORGE SEGAL" ], [ "MANHATTAN", "has_genre", "COMEDY" ], [ "MANHATTAN", "has_tags", "COMEDY" ], [ "MANHATTAN", "release_year", "1979" ], [ "MEATBALLS", "has_genre", "COMEDY" ], [ "MEATBALLS", "release_year", "1979" ], [ "MORE AMERICAN GRAFFITI", "has_genre", "COMEDY" ], [ "MORE AMERICAN GRAFFITI", "release_year", "1979" ], [ "REAL LIFE", "has_genre", "COMEDY" ], [ "REAL LIFE", "release_year", "1979" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "release_year", "1979" ], [ "STARTING OVER", "has_genre", "COMEDY" ], [ "STARTING OVER", "release_year", "1979" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "has_genre", "COMEDY" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "release_year", "1979" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "release_year", "1979" ], [ "THE HOT ROCK", "has_genre", "COMEDY" ], [ "THE HOT ROCK", "starred_actors", "GEORGE SEGAL" ], [ "THE IN-LAWS", "has_genre", "COMEDY" ], [ "THE IN-LAWS", "release_year", "1979" ], [ "THE JERK", "has_genre", "COMEDY" ], [ "THE JERK", "release_year", "1979" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1979" ], [ "THE MAIN EVENT", "has_genre", "COMEDY" ], [ "THE MAIN EVENT", "release_year", "1979" ], [ "THE MIRROR HAS TWO FACES", "directed_by", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "COMEDY" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "DRAMA" ], [ "THE MIRROR HAS TWO FACES", "has_tags", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "GEORGE SEGAL" ], [ "THE MUPPET MOVIE", "has_genre", "COMEDY" ], [ "THE MUPPET MOVIE", "release_year", "1979" ], [ "THE OWL AND THE PUSSYCAT", "has_genre", "COMEDY" ], [ "THE OWL AND THE PUSSYCAT", "release_year", "1970" ], [ "THE OWL AND THE PUSSYCAT", "starred_actors", "BARBRA STREISAND" ], [ "THE OWL AND THE PUSSYCAT", "starred_actors", "GEORGE SEGAL" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "release_year", "1979" ], [ "THE TEMPEST", "has_genre", "COMEDY" ], [ "THE TEMPEST", "release_year", "1979" ], [ "UNCLE MARIN, THE BILLIONAIRE", "has_genre", "COMEDY" ], [ "UNCLE MARIN, THE BILLIONAIRE", "release_year", "1979" ], [ "WHERE'S POPPA?", "has_genre", "COMEDY" ], [ "WHERE'S POPPA?", "release_year", "1970" ], [ "WHERE'S POPPA?", "starred_actors", "GEORGE SEGAL" ], [ "WHO IS KILLING THE GREAT CHEFS OF EUROPE?", "has_genre", "COMEDY" ], [ "WHO IS KILLING THE GREAT CHEFS OF EUROPE?", "starred_actors", "GEORGE SEGAL" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_genre", "DRAMA" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "starred_actors", "GEORGE SEGAL" ], [ "WISE BLOOD", "has_genre", "COMEDY" ], [ "WISE BLOOD", "release_year", "1979" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18132, 1938 25221, 1981 36647, 8 WOMEN 30146, A CHRISTMAS CAROL 9698, A CHRISTMAS TALE 12649, A LITTLE ROMANCE 16566, A MONKEY IN WINTER 9230, A SLIGHT CASE OF MURDER 11188, A WOMAN IS A WOMAN 4028, AALTRA 13939, ALL TOGETHER 12224, AMÉLIE 36929, ANNABEL TAKES A TOUR 6200, ATTILA MARCEL 17083, BABYSITTING 10067, BERNIE 340, BLOCK-HEADS 11298, BOLIVIA 10081, BOTTLE SHOCK 8655, BOY MEETS GIRL 15416, BOYFRIENDS AND GIRLFRIENDS 235, BRINGING UP BABY 23286, CARNAGE 230, CARNIVAL IN FLANDERS 18400, CASE DÉPART 21981, CHOUCHOU 30463, COMEDY 16536, CYRANO DE BERGERAC 22667, DAYS OF DARKNESS 9709, DE L'AUTRE CÔTÉ DU LIT 6375, DELICACY 30433, DELUSIONS OF GRANDEUR 36212, DRAMA 32892, ENGLISH VINGLISH 17072, FAREWELL, HOME SWEET HOME 22941, FATHER AND GUNS 33845, FISTON 9539, FREDDY FLORES 6012, FRENCH 4096, FRENCH KISS 13389, FRENCH TWIST 23743, GET OUT YOUR HANDKERCHIEFS 5527, GIGI 37514, GOING PLACES 26909, GREEN CARD 38162, HAPPINESS IS IN THE FIELD 34345, HAPPINESS NEVER COMES ALONE 12085, HAPPY NEW YEAR 11783, HEARTBREAKER 7289, HOLIDAY 4429, HOW MUCH DO YOU LOVE ME? 10411, HOW TASTY WAS MY LITTLE FRENCHMAN 35625, HUMAN NATURE 38589, I DO 27285, I WAS A MALE WAR BRIDE 38392, I, CESAR 18699, JULIET OF THE SPIRITS 23366, JUST AROUND THE CORNER 16839, JUST VISITING 14209, KING OF HEARTS 24238, L'AGE D'OR 15175, LE HAVRE 22443, LE MILLION 19966, LE PLAISIR 25390, LIFE IS A LONG QUIET RIVER 16814, LITTLE WHITE LIES 17372, LOL 10284, LOVE FINDS ANDY HARDY 10560, MAN BITES DOG 34969, MAN-PROOF 39509, MARCEL PAGNOL 22420, ME, MYSELF AND MUM 3092, MERRILY WE LIVE 31657, MON ONCLE 17748, MY WIFE IS AN ACTRESS 12152, NOTHING TO DECLARE 32901, ON TOUR 352, ONE HUNDRED AND ONE NIGHTS 11056, PAULETTE 5958, PERCHED ON A TREE 5311, PLAYTIME 10493, POPULAIRE 33032, PORT OF SHADOWS 11213, POTICHE 15021, PROFESSOR BEWARE 9019, RATATOUILLE 22488, REBECCA OF SUNNYBROOK FARM 6201, ROOM SERVICE 18478, RUSH HOUR 3 4689, SABRINA 24060, SEDUCING DOCTOR LEWIS 6603, SEX IS COMEDY 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 39915, SHALL WE KISS? 28126, SHEITAN 15380, SIDEWALKS OF LONDON 30664, SMOKING/NO SMOKING 17447, SON OF RAMBOW 7175, STOLEN KISSES 39270, SUBWAY 16165, SUPERCONDRIAQUE 345, TANGUY 10732, TAXI 8416, TAXI 3 24351, TAXI 4 9091, THE ADVENTURES OF PICASSO 24625, THE APARTMENT 39795, THE ARTIST 8234, THE BAKER'S WIFE 38965, THE BARBARIAN INVASIONS 32454, THE BIG PICTURE 14643, THE BRAIN 39773, THE CLINK OF ICE 30164, THE CLOSET 33017, THE COWBOY AND THE LADY 13316, THE DECLINE OF THE AMERICAN EMPIRE 29539, THE DIVORCE OF LADY X 38918, THE FAMILY 12169, THE FRENCH MINISTER 9093, THE GRAND MANEUVER 22995, THE HAPPY ROAD 6289, THE INTOUCHABLES 4091, THE LADY VANISHES 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 31569, THE LOVE PARADE 7954, THE MAD MISS MANTON 33513, THE MAN WHO LOVED WOMEN 32297, THE MERRY WIDOW 38843, THE MURDERER LIVES AT NUMBER 21 31851, THE PRISONER OF ZENDA 37461, THE RULES OF THE GAME 11383, THE SCIENCE OF SLEEP 15930, THE SUCKER 36903, THE SUITOR 26678, THE SWINDLE 11663, THE TALL BLOND MAN WITH ONE BLACK SHOE 26185, THE TOY 25591, THE TRIPLETS OF BELLEVILLE 4542, THE VALET 13003, THE WELL-DIGGER'S DAUGHTER 26408, THE WISE GUYS 6471, THE YOUNG IN HEART 5128, THERE GOES MY HEART 22238, THERE'S ALWAYS A WOMAN 1459, TOO BEAUTIFUL FOR YOU 17536, TRAFIC 12860, TRUE LIES 3286, UNDER THE ROOFS OF PARIS 31732, URANUS 37344, VERY HAPPY ALEXANDER 11659, VIVA MARIA! 13631, VIVACIOUS LADY 29077, WASABI 35511, WE HAVE A POPE 22241, WE'RE NO ANGELS 33483, WEEKEND 5927, WELLS ROOT 38905, WHAT'S IN A NAME? 3569, WHY NOT ME? 22756, WINDOW TO PARIS 367, WITH LOVE... FROM THE AGE OF REASON 8184, YOU CAN'T TAKE IT WITH YOU src, edge_attr, dst 25221, has_genre, 30463 25221, in_language, 6012 36647, has_genre, 30463 36647, has_tags, 6012 36647, in_language, 6012 30146, has_genre, 30463 30146, release_year, 18132 9698, has_genre, 30463 9698, in_language, 6012 12649, has_genre, 30463 12649, in_language, 6012 16566, has_genre, 30463 16566, in_language, 6012 9230, has_genre, 30463 9230, has_tags, 30463 9230, release_year, 18132 11188, has_genre, 30463 11188, in_language, 6012 4028, has_genre, 30463 4028, in_language, 6012 13939, has_genre, 30463 13939, in_language, 6012 12224, has_genre, 30463 12224, has_tags, 30463 12224, has_tags, 6012 12224, in_language, 6012 36929, has_genre, 30463 36929, release_year, 18132 6200, has_genre, 30463 6200, in_language, 6012 17083, has_genre, 30463 17083, in_language, 6012 10067, has_genre, 30463 10067, in_language, 6012 340, has_genre, 30463 340, release_year, 18132 11298, has_genre, 36212 11298, starred_actors, 9539 10081, has_genre, 30463 10081, in_language, 6012 8655, has_genre, 30463 8655, in_language, 6012 8655, release_year, 18132 15416, has_genre, 30463 15416, in_language, 6012 235, has_genre, 30463 235, has_tags, 30463 235, release_year, 18132 23286, has_genre, 30463 23286, in_language, 6012 230, has_genre, 30463 230, in_language, 6012 18400, has_genre, 30463 18400, has_tags, 6012 18400, in_language, 6012 21981, has_genre, 30463 21981, has_tags, 6012 21981, in_language, 6012 16536, has_genre, 30463 16536, has_tags, 6012 16536, in_language, 6012 22667, has_genre, 30463 22667, in_language, 6012 9709, has_genre, 30463 9709, in_language, 6012 6375, has_genre, 30463 6375, in_language, 6012 30433, has_genre, 30463 30433, in_language, 6012 32892, has_genre, 30463 32892, in_language, 6012 17072, has_genre, 30463 17072, in_language, 6012 22941, has_genre, 30463 22941, in_language, 6012 33845, has_genre, 30463 33845, has_tags, 6012 33845, in_language, 6012 4096, has_genre, 30463 4096, has_tags, 30463 4096, in_language, 6012 13389, has_genre, 30463 13389, in_language, 6012 23743, has_genre, 30463 23743, in_language, 6012 5527, has_genre, 30463 5527, in_language, 6012 37514, has_genre, 30463 37514, in_language, 6012 26909, has_genre, 30463 26909, in_language, 6012 38162, has_genre, 30463 38162, in_language, 6012 34345, has_genre, 30463 34345, in_language, 6012 12085, has_genre, 30463 12085, in_language, 6012 11783, has_genre, 30463 11783, has_tags, 6012 11783, in_language, 6012 7289, has_genre, 30463 7289, has_tags, 30463 7289, release_year, 18132 4429, has_genre, 30463 4429, in_language, 6012 10411, has_genre, 30463 10411, in_language, 6012 35625, has_genre, 30463 35625, in_language, 6012 38589, has_genre, 30463 38589, has_tags, 6012 38589, in_language, 6012 27285, has_genre, 30463 27285, in_language, 6012 38392, has_genre, 30463 38392, has_tags, 6012 38392, in_language, 6012 18699, has_genre, 30463 18699, in_language, 6012 23366, has_genre, 30463 23366, release_year, 18132 16839, has_genre, 30463 16839, in_language, 6012 14209, has_genre, 30463 14209, in_language, 6012 24238, has_genre, 30463 24238, in_language, 6012 15175, has_genre, 30463 15175, in_language, 6012 22443, has_genre, 30463 22443, in_language, 6012 19966, has_genre, 30463 19966, in_language, 6012 25390, has_genre, 30463 25390, in_language, 6012 16814, has_genre, 30463 16814, in_language, 6012 17372, has_genre, 30463 17372, in_language, 6012 10284, has_genre, 30463 10284, release_year, 18132 10560, has_genre, 30463 10560, in_language, 6012 34969, has_genre, 30463 34969, release_year, 18132 22420, has_genre, 30463 22420, in_language, 6012 3092, has_genre, 30463 3092, release_year, 18132 31657, has_genre, 30463 31657, in_language, 6012 17748, has_genre, 30463 17748, in_language, 6012 12152, has_genre, 30463 12152, has_tags, 30463 12152, in_language, 6012 32901, has_genre, 30463 32901, in_language, 6012 352, has_genre, 30463 352, in_language, 6012 11056, has_genre, 30463 11056, in_language, 6012 5958, has_genre, 30463 5958, in_language, 6012 5311, has_genre, 30463 5311, in_language, 6012 10493, has_genre, 30463 10493, in_language, 6012 33032, in_language, 6012 33032, release_year, 18132 11213, has_genre, 30463 11213, in_language, 6012 15021, has_genre, 30463 15021, release_year, 18132 9019, has_genre, 30463 9019, in_language, 6012 22488, has_genre, 30463 22488, release_year, 18132 6201, has_genre, 30463 6201, release_year, 18132 18478, has_genre, 30463 18478, has_tags, 30463 18478, in_language, 6012 4689, has_genre, 30463 4689, in_language, 6012 24060, has_genre, 30463 24060, in_language, 6012 6603, has_genre, 30463 6603, in_language, 6012 25060, has_genre, 30463 25060, in_language, 6012 39915, has_genre, 30463 39915, in_language, 6012 28126, has_genre, 30463 28126, in_language, 6012 15380, has_genre, 30463 15380, release_year, 18132 30664, has_genre, 30463 30664, in_language, 6012 17447, has_genre, 30463 17447, in_language, 6012 7175, has_genre, 30463 7175, in_language, 6012 39270, has_genre, 30463 39270, in_language, 6012 16165, has_genre, 30463 16165, in_language, 6012 345, has_genre, 30463 345, in_language, 6012 10732, has_genre, 30463 10732, has_tags, 30463 10732, has_tags, 6012 10732, in_language, 6012 8416, has_genre, 30463 8416, in_language, 6012 24351, has_genre, 30463 24351, in_language, 6012 9091, has_genre, 30463 9091, in_language, 6012 24625, has_genre, 30463 24625, has_tags, 30463 24625, in_language, 6012 39795, has_genre, 30463 39795, has_tags, 6012 39795, in_language, 6012 8234, directed_by, 39509 8234, has_genre, 30463 8234, has_tags, 39509 8234, in_language, 6012 8234, release_year, 18132 38965, has_genre, 30463 38965, in_language, 6012 32454, has_genre, 30463 32454, has_tags, 6012 32454, in_language, 6012 14643, has_genre, 30463 14643, in_language, 6012 39773, has_genre, 30463 39773, in_language, 6012 30164, has_genre, 30463 30164, has_tags, 30463 30164, has_tags, 6012 30164, in_language, 6012 33017, has_genre, 30463 33017, release_year, 18132 13316, has_genre, 30463 13316, in_language, 6012 29539, has_genre, 30463 29539, release_year, 18132 38918, has_genre, 30463 38918, in_language, 6012 12169, has_genre, 30463 12169, has_tags, 6012 12169, in_language, 6012 9093, has_genre, 30463 9093, in_language, 6012 22995, has_genre, 30463 22995, in_language, 6012 6289, has_genre, 30463 6289, has_tags, 6012 6289, in_language, 6012 4091, has_genre, 30463 4091, release_year, 18132 28217, has_genre, 30463 28217, has_tags, 30463 28217, in_language, 6012 31569, has_genre, 30463 31569, in_language, 6012 7954, has_genre, 30463 7954, release_year, 18132 33513, has_genre, 30463 33513, in_language, 6012 32297, has_genre, 30463 32297, in_language, 6012 38843, has_genre, 30463 38843, in_language, 6012 31851, has_genre, 30463 31851, has_genre, 36212 31851, written_by, 5927 37461, has_genre, 30463 37461, has_tags, 30463 37461, in_language, 6012 11383, has_genre, 30463 11383, in_language, 6012 15930, has_genre, 30463 15930, in_language, 6012 36903, has_genre, 30463 36903, in_language, 6012 26678, has_genre, 30463 26678, in_language, 6012 11663, has_genre, 30463 11663, in_language, 6012 26185, has_genre, 30463 26185, in_language, 6012 25591, has_genre, 30463 25591, has_tags, 6012 25591, in_language, 6012 4542, has_genre, 30463 4542, has_tags, 30463 4542, has_tags, 6012 4542, in_language, 6012 13003, directed_by, 39509 13003, has_genre, 30463 13003, has_tags, 39509 13003, in_language, 6012 13003, written_by, 39509 26408, has_genre, 30463 26408, in_language, 6012 6471, has_genre, 30463 6471, release_year, 18132 5128, has_genre, 30463 5128, release_year, 18132 22238, has_genre, 30463 22238, release_year, 18132 1459, has_genre, 30463 1459, in_language, 6012 17536, has_genre, 30463 17536, in_language, 6012 12860, has_genre, 30463 12860, has_tags, 30463 12860, in_language, 6012 3286, has_genre, 30463 3286, in_language, 6012 31732, has_genre, 30463 31732, in_language, 6012 37344, has_genre, 30463 37344, in_language, 6012 11659, has_genre, 30463 11659, has_tags, 6012 11659, in_language, 6012 13631, has_genre, 30463 13631, release_year, 18132 29077, has_genre, 30463 29077, has_tags, 30463 29077, in_language, 6012 35511, has_genre, 30463 35511, has_tags, 30463 35511, in_language, 6012 22241, has_genre, 30463 22241, has_tags, 30463 22241, in_language, 6012 33483, has_genre, 30463 33483, has_tags, 6012 33483, in_language, 6012 38905, has_genre, 30463 38905, has_tags, 6012 38905, in_language, 6012 3569, has_genre, 30463 3569, has_tags, 6012 3569, in_language, 6012 22756, has_genre, 30463 22756, in_language, 6012 367, has_genre, 30463 367, in_language, 6012 8184, has_genre, 30463 8184, release_year, 18132 Question: How are FREDDY FLORES, THE BAKER'S WIFE, and WELLS ROOT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FREDDY FLORES", "THE BAKER'S WIFE", "WELLS ROOT" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "in_language", "FRENCH" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "has_tags", "FRENCH" ], [ "8 WOMEN", "in_language", "FRENCH" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "release_year", "1938" ], [ "A CHRISTMAS TALE", "has_genre", "COMEDY" ], [ "A CHRISTMAS TALE", "in_language", "FRENCH" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "in_language", "FRENCH" ], [ "A MONKEY IN WINTER", "has_genre", "COMEDY" ], [ "A MONKEY IN WINTER", "in_language", "FRENCH" ], [ "A SLIGHT CASE OF MURDER", "has_genre", "COMEDY" ], [ "A SLIGHT CASE OF MURDER", "has_tags", "COMEDY" ], [ "A SLIGHT CASE OF MURDER", "release_year", "1938" ], [ "A WOMAN IS A WOMAN", "has_genre", "COMEDY" ], [ "A WOMAN IS A WOMAN", "in_language", "FRENCH" ], [ "AALTRA", "has_genre", "COMEDY" ], [ "AALTRA", "in_language", "FRENCH" ], [ "ALL TOGETHER", "has_genre", "COMEDY" ], [ "ALL TOGETHER", "in_language", "FRENCH" ], [ "AMÉLIE", "has_genre", "COMEDY" ], [ "AMÉLIE", "has_tags", "COMEDY" ], [ "AMÉLIE", "has_tags", "FRENCH" ], [ "AMÉLIE", "in_language", "FRENCH" ], [ "ANNABEL TAKES A TOUR", "has_genre", "COMEDY" ], [ "ANNABEL TAKES A TOUR", "release_year", "1938" ], [ "ATTILA MARCEL", "has_genre", "COMEDY" ], [ "ATTILA MARCEL", "in_language", "FRENCH" ], [ "BABYSITTING", "has_genre", "COMEDY" ], [ "BABYSITTING", "in_language", "FRENCH" ], [ "BERNIE", "has_genre", "COMEDY" ], [ "BERNIE", "in_language", "FRENCH" ], [ "BLOCK-HEADS", "has_genre", "COMEDY" ], [ "BLOCK-HEADS", "release_year", "1938" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "starred_actors", "FREDDY FLORES" ], [ "BOTTLE SHOCK", "has_genre", "COMEDY" ], [ "BOTTLE SHOCK", "in_language", "FRENCH" ], [ "BOY MEETS GIRL", "has_genre", "COMEDY" ], [ "BOY MEETS GIRL", "in_language", "FRENCH" ], [ "BOY MEETS GIRL", "release_year", "1938" ], [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "in_language", "FRENCH" ], [ "BRINGING UP BABY", "has_genre", "COMEDY" ], [ "BRINGING UP BABY", "has_tags", "COMEDY" ], [ "BRINGING UP BABY", "release_year", "1938" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "in_language", "FRENCH" ], [ "CARNIVAL IN FLANDERS", "has_genre", "COMEDY" ], [ "CARNIVAL IN FLANDERS", "in_language", "FRENCH" ], [ "CASE DÉPART", "has_genre", "COMEDY" ], [ "CASE DÉPART", "has_tags", "FRENCH" ], [ "CASE DÉPART", "in_language", "FRENCH" ], [ "CHOUCHOU", "has_genre", "COMEDY" ], [ "CHOUCHOU", "has_tags", "FRENCH" ], [ "CHOUCHOU", "in_language", "FRENCH" ], [ "CYRANO DE BERGERAC", "has_genre", "COMEDY" ], [ "CYRANO DE BERGERAC", "has_tags", "FRENCH" ], [ "CYRANO DE BERGERAC", "in_language", "FRENCH" ], [ "DAYS OF DARKNESS", "has_genre", "COMEDY" ], [ "DAYS OF DARKNESS", "in_language", "FRENCH" ], [ "DE L'AUTRE CÔTÉ DU LIT", "has_genre", "COMEDY" ], [ "DE L'AUTRE CÔTÉ DU LIT", "in_language", "FRENCH" ], [ "DELICACY", "has_genre", "COMEDY" ], [ "DELICACY", "in_language", "FRENCH" ], [ "DELUSIONS OF GRANDEUR", "has_genre", "COMEDY" ], [ "DELUSIONS OF GRANDEUR", "in_language", "FRENCH" ], [ "ENGLISH VINGLISH", "has_genre", "COMEDY" ], [ "ENGLISH VINGLISH", "in_language", "FRENCH" ], [ "FAREWELL, HOME SWEET HOME", "has_genre", "COMEDY" ], [ "FAREWELL, HOME SWEET HOME", "in_language", "FRENCH" ], [ "FATHER AND GUNS", "has_genre", "COMEDY" ], [ "FATHER AND GUNS", "in_language", "FRENCH" ], [ "FISTON", "has_genre", "COMEDY" ], [ "FISTON", "has_tags", "FRENCH" ], [ "FISTON", "in_language", "FRENCH" ], [ "FRENCH KISS", "has_genre", "COMEDY" ], [ "FRENCH KISS", "has_tags", "COMEDY" ], [ "FRENCH KISS", "in_language", "FRENCH" ], [ "FRENCH TWIST", "has_genre", "COMEDY" ], [ "FRENCH TWIST", "in_language", "FRENCH" ], [ "GET OUT YOUR HANDKERCHIEFS", "has_genre", "COMEDY" ], [ "GET OUT YOUR HANDKERCHIEFS", "in_language", "FRENCH" ], [ "GIGI", "has_genre", "COMEDY" ], [ "GIGI", "in_language", "FRENCH" ], [ "GOING PLACES", "has_genre", "COMEDY" ], [ "GOING PLACES", "in_language", "FRENCH" ], [ "GREEN CARD", "has_genre", "COMEDY" ], [ "GREEN CARD", "in_language", "FRENCH" ], [ "HAPPINESS IS IN THE FIELD", "has_genre", "COMEDY" ], [ "HAPPINESS IS IN THE FIELD", "in_language", "FRENCH" ], [ "HAPPINESS NEVER COMES ALONE", "has_genre", "COMEDY" ], [ "HAPPINESS NEVER COMES ALONE", "in_language", "FRENCH" ], [ "HAPPY NEW YEAR", "has_genre", "COMEDY" ], [ "HAPPY NEW YEAR", "in_language", "FRENCH" ], [ "HEARTBREAKER", "has_genre", "COMEDY" ], [ "HEARTBREAKER", "has_tags", "FRENCH" ], [ "HEARTBREAKER", "in_language", "FRENCH" ], [ "HOLIDAY", "has_genre", "COMEDY" ], [ "HOLIDAY", "has_tags", "COMEDY" ], [ "HOLIDAY", "release_year", "1938" ], [ "HOW MUCH DO YOU LOVE ME?", "has_genre", "COMEDY" ], [ "HOW MUCH DO YOU LOVE ME?", "in_language", "FRENCH" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "has_genre", "COMEDY" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "in_language", "FRENCH" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "in_language", "FRENCH" ], [ "I DO", "has_genre", "COMEDY" ], [ "I DO", "has_tags", "FRENCH" ], [ "I DO", "in_language", "FRENCH" ], [ "I WAS A MALE WAR BRIDE", "has_genre", "COMEDY" ], [ "I WAS A MALE WAR BRIDE", "in_language", "FRENCH" ], [ "I, CESAR", "has_genre", "COMEDY" ], [ "I, CESAR", "has_tags", "FRENCH" ], [ "I, CESAR", "in_language", "FRENCH" ], [ "JULIET OF THE SPIRITS", "has_genre", "COMEDY" ], [ "JULIET OF THE SPIRITS", "in_language", "FRENCH" ], [ "JUST AROUND THE CORNER", "has_genre", "COMEDY" ], [ "JUST AROUND THE CORNER", "release_year", "1938" ], [ "JUST VISITING", "has_genre", "COMEDY" ], [ "JUST VISITING", "in_language", "FRENCH" ], [ "KING OF HEARTS", "has_genre", "COMEDY" ], [ "KING OF HEARTS", "in_language", "FRENCH" ], [ "L'AGE D'OR", "has_genre", "COMEDY" ], [ "L'AGE D'OR", "in_language", "FRENCH" ], [ "LE HAVRE", "has_genre", "COMEDY" ], [ "LE HAVRE", "in_language", "FRENCH" ], [ "LE MILLION", "has_genre", "COMEDY" ], [ "LE MILLION", "in_language", "FRENCH" ], [ "LE PLAISIR", "has_genre", "COMEDY" ], [ "LE PLAISIR", "in_language", "FRENCH" ], [ "LIFE IS A LONG QUIET RIVER", "has_genre", "COMEDY" ], [ "LIFE IS A LONG QUIET RIVER", "in_language", "FRENCH" ], [ "LITTLE WHITE LIES", "has_genre", "COMEDY" ], [ "LITTLE WHITE LIES", "in_language", "FRENCH" ], [ "LOL", "has_genre", "COMEDY" ], [ "LOL", "in_language", "FRENCH" ], [ "LOVE FINDS ANDY HARDY", "has_genre", "COMEDY" ], [ "LOVE FINDS ANDY HARDY", "release_year", "1938" ], [ "MAN BITES DOG", "has_genre", "COMEDY" ], [ "MAN BITES DOG", "in_language", "FRENCH" ], [ "MAN-PROOF", "has_genre", "COMEDY" ], [ "MAN-PROOF", "release_year", "1938" ], [ "ME, MYSELF AND MUM", "has_genre", "COMEDY" ], [ "ME, MYSELF AND MUM", "in_language", "FRENCH" ], [ "MERRILY WE LIVE", "has_genre", "COMEDY" ], [ "MERRILY WE LIVE", "release_year", "1938" ], [ "MON ONCLE", "has_genre", "COMEDY" ], [ "MON ONCLE", "in_language", "FRENCH" ], [ "MY WIFE IS AN ACTRESS", "has_genre", "COMEDY" ], [ "MY WIFE IS AN ACTRESS", "in_language", "FRENCH" ], [ "NOTHING TO DECLARE", "has_genre", "COMEDY" ], [ "NOTHING TO DECLARE", "has_tags", "COMEDY" ], [ "NOTHING TO DECLARE", "in_language", "FRENCH" ], [ "ON TOUR", "has_genre", "COMEDY" ], [ "ON TOUR", "in_language", "FRENCH" ], [ "ONE HUNDRED AND ONE NIGHTS", "has_genre", "COMEDY" ], [ "ONE HUNDRED AND ONE NIGHTS", "in_language", "FRENCH" ], [ "PAULETTE", "has_genre", "COMEDY" ], [ "PAULETTE", "in_language", "FRENCH" ], [ "PERCHED ON A TREE", "has_genre", "COMEDY" ], [ "PERCHED ON A TREE", "in_language", "FRENCH" ], [ "PLAYTIME", "has_genre", "COMEDY" ], [ "PLAYTIME", "in_language", "FRENCH" ], [ "POPULAIRE", "has_genre", "COMEDY" ], [ "POPULAIRE", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "release_year", "1938" ], [ "POTICHE", "has_genre", "COMEDY" ], [ "POTICHE", "in_language", "FRENCH" ], [ "PROFESSOR BEWARE", "has_genre", "COMEDY" ], [ "PROFESSOR BEWARE", "release_year", "1938" ], [ "RATATOUILLE", "has_genre", "COMEDY" ], [ "RATATOUILLE", "in_language", "FRENCH" ], [ "REBECCA OF SUNNYBROOK FARM", "has_genre", "COMEDY" ], [ "REBECCA OF SUNNYBROOK FARM", "release_year", "1938" ], [ "ROOM SERVICE", "has_genre", "COMEDY" ], [ "ROOM SERVICE", "release_year", "1938" ], [ "RUSH HOUR 3", "has_genre", "COMEDY" ], [ "RUSH HOUR 3", "has_tags", "COMEDY" ], [ "RUSH HOUR 3", "in_language", "FRENCH" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "in_language", "FRENCH" ], [ "SEDUCING DOCTOR LEWIS", "has_genre", "COMEDY" ], [ "SEDUCING DOCTOR LEWIS", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "has_genre", "COMEDY" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "has_genre", "COMEDY" ], [ "SHALL WE KISS?", "in_language", "FRENCH" ], [ "SHEITAN", "has_genre", "COMEDY" ], [ "SHEITAN", "in_language", "FRENCH" ], [ "SIDEWALKS OF LONDON", "has_genre", "COMEDY" ], [ "SIDEWALKS OF LONDON", "release_year", "1938" ], [ "SMOKING/NO SMOKING", "has_genre", "COMEDY" ], [ "SMOKING/NO SMOKING", "in_language", "FRENCH" ], [ "SON OF RAMBOW", "has_genre", "COMEDY" ], [ "SON OF RAMBOW", "in_language", "FRENCH" ], [ "STOLEN KISSES", "has_genre", "COMEDY" ], [ "STOLEN KISSES", "in_language", "FRENCH" ], [ "SUBWAY", "has_genre", "COMEDY" ], [ "SUBWAY", "in_language", "FRENCH" ], [ "SUPERCONDRIAQUE", "has_genre", "COMEDY" ], [ "SUPERCONDRIAQUE", "in_language", "FRENCH" ], [ "TANGUY", "has_genre", "COMEDY" ], [ "TANGUY", "in_language", "FRENCH" ], [ "TAXI", "has_genre", "COMEDY" ], [ "TAXI", "has_tags", "COMEDY" ], [ "TAXI", "has_tags", "FRENCH" ], [ "TAXI", "in_language", "FRENCH" ], [ "TAXI 3", "has_genre", "COMEDY" ], [ "TAXI 3", "in_language", "FRENCH" ], [ "TAXI 4", "has_genre", "COMEDY" ], [ "TAXI 4", "in_language", "FRENCH" ], [ "THE ADVENTURES OF PICASSO", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PICASSO", "in_language", "FRENCH" ], [ "THE APARTMENT", "has_genre", "COMEDY" ], [ "THE APARTMENT", "has_tags", "COMEDY" ], [ "THE APARTMENT", "in_language", "FRENCH" ], [ "THE ARTIST", "has_genre", "COMEDY" ], [ "THE ARTIST", "has_tags", "FRENCH" ], [ "THE ARTIST", "in_language", "FRENCH" ], [ "THE BAKER'S WIFE", "directed_by", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "has_genre", "COMEDY" ], [ "THE BAKER'S WIFE", "has_tags", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "in_language", "FRENCH" ], [ "THE BAKER'S WIFE", "release_year", "1938" ], [ "THE BARBARIAN INVASIONS", "has_genre", "COMEDY" ], [ "THE BARBARIAN INVASIONS", "in_language", "FRENCH" ], [ "THE BIG PICTURE", "has_genre", "COMEDY" ], [ "THE BIG PICTURE", "has_tags", "FRENCH" ], [ "THE BIG PICTURE", "in_language", "FRENCH" ], [ "THE BRAIN", "has_genre", "COMEDY" ], [ "THE BRAIN", "in_language", "FRENCH" ], [ "THE CLINK OF ICE", "has_genre", "COMEDY" ], [ "THE CLINK OF ICE", "in_language", "FRENCH" ], [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE CLOSET", "has_tags", "FRENCH" ], [ "THE CLOSET", "in_language", "FRENCH" ], [ "THE COWBOY AND THE LADY", "has_genre", "COMEDY" ], [ "THE COWBOY AND THE LADY", "release_year", "1938" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "COMEDY" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "in_language", "FRENCH" ], [ "THE DIVORCE OF LADY X", "has_genre", "COMEDY" ], [ "THE DIVORCE OF LADY X", "release_year", "1938" ], [ "THE FAMILY", "has_genre", "COMEDY" ], [ "THE FAMILY", "in_language", "FRENCH" ], [ "THE FRENCH MINISTER", "has_genre", "COMEDY" ], [ "THE FRENCH MINISTER", "has_tags", "FRENCH" ], [ "THE FRENCH MINISTER", "in_language", "FRENCH" ], [ "THE GRAND MANEUVER", "has_genre", "COMEDY" ], [ "THE GRAND MANEUVER", "in_language", "FRENCH" ], [ "THE HAPPY ROAD", "has_genre", "COMEDY" ], [ "THE HAPPY ROAD", "in_language", "FRENCH" ], [ "THE INTOUCHABLES", "has_genre", "COMEDY" ], [ "THE INTOUCHABLES", "has_tags", "FRENCH" ], [ "THE INTOUCHABLES", "in_language", "FRENCH" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "COMEDY" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_tags", "COMEDY" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "in_language", "FRENCH" ], [ "THE LOVE PARADE", "has_genre", "COMEDY" ], [ "THE LOVE PARADE", "in_language", "FRENCH" ], [ "THE MAD MISS MANTON", "has_genre", "COMEDY" ], [ "THE MAD MISS MANTON", "release_year", "1938" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "COMEDY" ], [ "THE MAN WHO LOVED WOMEN", "in_language", "FRENCH" ], [ "THE MERRY WIDOW", "has_genre", "COMEDY" ], [ "THE MERRY WIDOW", "in_language", "FRENCH" ], [ "THE MURDERER LIVES AT NUMBER 21", "has_genre", "COMEDY" ], [ "THE MURDERER LIVES AT NUMBER 21", "in_language", "FRENCH" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE PRISONER OF ZENDA", "written_by", "WELLS ROOT" ], [ "THE RULES OF THE GAME", "has_genre", "COMEDY" ], [ "THE RULES OF THE GAME", "has_tags", "COMEDY" ], [ "THE RULES OF THE GAME", "in_language", "FRENCH" ], [ "THE SCIENCE OF SLEEP", "has_genre", "COMEDY" ], [ "THE SCIENCE OF SLEEP", "in_language", "FRENCH" ], [ "THE SUCKER", "has_genre", "COMEDY" ], [ "THE SUCKER", "in_language", "FRENCH" ], [ "THE SUITOR", "has_genre", "COMEDY" ], [ "THE SUITOR", "in_language", "FRENCH" ], [ "THE SWINDLE", "has_genre", "COMEDY" ], [ "THE SWINDLE", "in_language", "FRENCH" ], [ "THE TALL BLOND MAN WITH ONE BLACK SHOE", "has_genre", "COMEDY" ], [ "THE TALL BLOND MAN WITH ONE BLACK SHOE", "in_language", "FRENCH" ], [ "THE TOY", "has_genre", "COMEDY" ], [ "THE TOY", "in_language", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "has_genre", "COMEDY" ], [ "THE TRIPLETS OF BELLEVILLE", "has_tags", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "in_language", "FRENCH" ], [ "THE VALET", "has_genre", "COMEDY" ], [ "THE VALET", "has_tags", "COMEDY" ], [ "THE VALET", "has_tags", "FRENCH" ], [ "THE VALET", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "directed_by", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "COMEDY" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_tags", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "written_by", "MARCEL PAGNOL" ], [ "THE WISE GUYS", "has_genre", "COMEDY" ], [ "THE WISE GUYS", "in_language", "FRENCH" ], [ "THE YOUNG IN HEART", "has_genre", "COMEDY" ], [ "THE YOUNG IN HEART", "release_year", "1938" ], [ "THERE GOES MY HEART", "has_genre", "COMEDY" ], [ "THERE GOES MY HEART", "release_year", "1938" ], [ "THERE'S ALWAYS A WOMAN", "has_genre", "COMEDY" ], [ "THERE'S ALWAYS A WOMAN", "release_year", "1938" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "COMEDY" ], [ "TOO BEAUTIFUL FOR YOU", "in_language", "FRENCH" ], [ "TRAFIC", "has_genre", "COMEDY" ], [ "TRAFIC", "in_language", "FRENCH" ], [ "TRUE LIES", "has_genre", "COMEDY" ], [ "TRUE LIES", "has_tags", "COMEDY" ], [ "TRUE LIES", "in_language", "FRENCH" ], [ "UNDER THE ROOFS OF PARIS", "has_genre", "COMEDY" ], [ "UNDER THE ROOFS OF PARIS", "in_language", "FRENCH" ], [ "URANUS", "has_genre", "COMEDY" ], [ "URANUS", "in_language", "FRENCH" ], [ "VERY HAPPY ALEXANDER", "has_genre", "COMEDY" ], [ "VERY HAPPY ALEXANDER", "in_language", "FRENCH" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "VIVA MARIA!", "has_tags", "FRENCH" ], [ "VIVA MARIA!", "in_language", "FRENCH" ], [ "VIVACIOUS LADY", "has_genre", "COMEDY" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "WASABI", "has_genre", "COMEDY" ], [ "WASABI", "has_tags", "COMEDY" ], [ "WASABI", "in_language", "FRENCH" ], [ "WE HAVE A POPE", "has_genre", "COMEDY" ], [ "WE HAVE A POPE", "has_tags", "COMEDY" ], [ "WE HAVE A POPE", "in_language", "FRENCH" ], [ "WE'RE NO ANGELS", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "COMEDY" ], [ "WE'RE NO ANGELS", "in_language", "FRENCH" ], [ "WEEKEND", "has_genre", "COMEDY" ], [ "WEEKEND", "has_tags", "FRENCH" ], [ "WEEKEND", "in_language", "FRENCH" ], [ "WHAT'S IN A NAME?", "has_genre", "COMEDY" ], [ "WHAT'S IN A NAME?", "has_tags", "FRENCH" ], [ "WHAT'S IN A NAME?", "in_language", "FRENCH" ], [ "WHY NOT ME?", "has_genre", "COMEDY" ], [ "WHY NOT ME?", "has_tags", "FRENCH" ], [ "WHY NOT ME?", "in_language", "FRENCH" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "in_language", "FRENCH" ], [ "WITH LOVE... FROM THE AGE OF REASON", "has_genre", "COMEDY" ], [ "WITH LOVE... FROM THE AGE OF REASON", "in_language", "FRENCH" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 319, A BUG'S LIFE 33657, A NIGHT AT THE ROXBURY 35485, ALMOST HEROES 35941, ANTZ 8321, BASEKETBALL 36971, BEDROOMS AND HALLWAYS 29908, BILLY'S HOLLYWOOD SCREEN KISS 212, BLACK CAT, WHITE CAT 7318, BLOOD, GUTS, BULLETS AND OCTANE 16023, BLUES BROTHERS 2000 31902, BRIDE OF CHUCKY 32530, BUFFALO '66 5776, BULWORTH 16129, CAN'T HARDLY WAIT 26848, CELEBRITY 36568, CLAY PIGEONS 30463, COMEDY 36016, COUSIN BETTE 8872, DANCER, TEXAS POP. 81 25018, DEAD HUSBANDS 36117, DEAD MAN ON CAMPUS 39905, DECAMPITATED 29689, DIRTY WORK 3911, DIVORCING JACK 35714, DOG PARK 1200, DUPLICATE 3426, EDGE OF SEVENTEEN 24644, ERNEST IN THE ARMY 30820, FEAR AND LOATHING IN LAS VEGAS 3955, FINDING NORTH 30704, FREE MONEY 2547, GLASBLÅSARNS BARN 4278, HALF BAKED 17933, HAPPINESS 35633, HOLY MAN 7980, HOMEGROWN 24023, HOUSEBOUND 22348, I GOT THE HOOK UP 33211, I'LL BE HOME FOR CHRISTMAS 19868, JACK FROST 25363, JERRY AND TOM 14711, KISSING A FOOL 28004, KUCH KUCH HOTA HAI 37426, LIVING OUT LOUD 38721, LOCK, STOCK AND TWO SMOKING BARRELS 14997, MACKENZIE CROOK 37141, MEET THE DEEDLES 38276, MIDNIGHT 112, MUSIC FROM ANOTHER ROOM 16841, MY GIANT 22946, NEXT STOP WONDERLAND 10734, ORPHANS 4235, OUT OF SIGHT 1300, OVERNIGHT DELIVERY 3297, PATCH ADAMS 10640, PECKER 14282, PLEASANTVILLE 30118, POLISH WEDDING 16172, PRACTICAL MAGIC 22150, RIDE 24415, RINGMASTER 32607, RUSH HOUR 12153, RUSHMORE 8020, SAFE MEN 34686, SAMURAI FICTION 20220, SENSELESS 39218, SEX LIVES OF THE POTATO MEN 3657, SHAKESPEARE IN LOVE 217, SIMON BIRCH 23608, SIX DAYS SEVEN NIGHTS 32807, SIX-STRING SAMURAI 31596, SLAPPY AND THE STINKERS 34249, SLC PUNK! 28065, SLIDING DOORS 31526, SLUMS OF BEVERLY HILLS 36556, SMALL SOLDIERS 32731, SOME GIRL 6831, SOMEWHERE IN THE CITY 10819, SOUR GRAPES 33439, STEPMOM 10732, TAXI 4519, THE ADVENTURES OF SEBASTIAN COLE 36412, THE BIG HIT 14696, THE BIG LEBOWSKI 27549, THE BOOK OF LIFE 4068, THE GENERAL 40028, THE GODSON 17872, THE IDIOTS 32440, THE IMPOSTORS 4223, THE INTERVIEW 9059, THE LAST DAYS OF DISCO 844, THE LOVE LETTER 34003, THE MISADVENTURES OF MARGARET 22210, THE NAKED MAN 15569, THE OBJECT OF MY AFFECTION 24357, THE PARENT TRAP 27932, THE PENTAGON WARS 16573, THE PLAYERS CLUB 17460, THE RUGRATS MOVIE 36038, THE WATERBOY 11628, THE WEDDING SINGER 13738, THERE'S SOMETHING ABOUT MARY 8012, TOMORROW NIGHT 15511, TORRENTE, EL BRAZO TONTO DE LA LEY 7379, VERY BAD THINGS 4736, WHERE'S MARLOWE? 19679, WIDE AWAKE 25949, WOO 9552, WRONGFULLY ACCUSED 15808, YOU'VE GOT MAIL src, edge_attr, dst 319, has_genre, 30463 319, has_tags, 30463 319, release_year, 2133 33657, has_genre, 30463 33657, release_year, 2133 35485, has_genre, 30463 35485, release_year, 2133 35941, has_genre, 30463 35941, release_year, 2133 8321, has_genre, 30463 8321, has_tags, 30463 8321, release_year, 2133 36971, has_genre, 30463 36971, release_year, 2133 29908, has_genre, 30463 29908, release_year, 2133 212, has_genre, 30463 212, release_year, 2133 7318, has_genre, 30463 7318, release_year, 2133 16023, has_genre, 30463 16023, release_year, 2133 31902, has_genre, 30463 31902, release_year, 2133 32530, has_genre, 30463 32530, release_year, 2133 5776, has_genre, 30463 5776, has_tags, 30463 5776, release_year, 2133 16129, has_genre, 30463 16129, release_year, 2133 26848, has_genre, 30463 26848, release_year, 2133 36568, has_genre, 30463 36568, release_year, 2133 36016, has_genre, 30463 36016, release_year, 2133 8872, has_genre, 30463 8872, release_year, 2133 25018, has_genre, 30463 25018, release_year, 2133 36117, has_genre, 30463 36117, release_year, 2133 39905, has_genre, 30463 39905, release_year, 2133 29689, has_genre, 30463 29689, has_tags, 30463 29689, release_year, 2133 3911, has_genre, 30463 3911, has_tags, 30463 3911, release_year, 2133 35714, has_genre, 30463 35714, release_year, 2133 1200, has_genre, 30463 1200, release_year, 2133 3426, has_genre, 30463 3426, release_year, 2133 24644, has_genre, 30463 24644, release_year, 2133 30820, has_genre, 30463 30820, has_tags, 30463 30820, release_year, 2133 3955, has_genre, 30463 3955, release_year, 2133 30704, has_genre, 30463 30704, release_year, 2133 2547, release_year, 2133 4278, has_genre, 30463 4278, has_tags, 30463 4278, release_year, 2133 17933, has_genre, 30463 17933, release_year, 2133 35633, has_genre, 30463 35633, release_year, 2133 7980, has_genre, 30463 7980, release_year, 2133 24023, has_genre, 30463 22348, has_genre, 30463 22348, release_year, 2133 33211, has_genre, 30463 33211, release_year, 2133 19868, has_genre, 30463 19868, release_year, 2133 25363, has_genre, 30463 25363, release_year, 2133 14711, has_genre, 30463 14711, release_year, 2133 28004, has_genre, 30463 28004, release_year, 2133 37426, has_genre, 30463 37426, release_year, 2133 38721, has_genre, 30463 38721, has_tags, 30463 38721, release_year, 2133 37141, has_genre, 30463 37141, release_year, 2133 38276, has_genre, 30463 38276, release_year, 2133 112, has_genre, 30463 112, release_year, 2133 16841, has_genre, 30463 16841, release_year, 2133 22946, has_genre, 30463 22946, release_year, 2133 10734, has_genre, 30463 10734, release_year, 2133 4235, has_genre, 30463 4235, release_year, 2133 1300, has_genre, 30463 1300, release_year, 2133 3297, has_genre, 30463 3297, release_year, 2133 10640, has_genre, 30463 10640, release_year, 2133 14282, has_genre, 30463 14282, release_year, 2133 30118, has_genre, 30463 30118, release_year, 2133 16172, has_genre, 30463 16172, release_year, 2133 22150, has_genre, 30463 22150, release_year, 2133 24415, has_genre, 30463 24415, release_year, 2133 32607, has_genre, 30463 32607, has_tags, 30463 32607, release_year, 2133 12153, has_genre, 30463 12153, has_tags, 30463 12153, release_year, 2133 8020, has_genre, 30463 8020, release_year, 2133 34686, has_genre, 30463 34686, release_year, 2133 20220, has_genre, 30463 20220, release_year, 2133 39218, has_genre, 30463 39218, starred_actors, 14997 3657, has_genre, 30463 3657, release_year, 2133 217, has_genre, 30463 217, release_year, 2133 23608, has_genre, 30463 23608, has_tags, 30463 23608, release_year, 2133 32807, has_genre, 30463 32807, release_year, 2133 31596, has_genre, 30463 31596, release_year, 2133 34249, has_genre, 30463 34249, release_year, 2133 28065, has_genre, 30463 28065, release_year, 2133 31526, has_genre, 30463 31526, release_year, 2133 36556, has_genre, 30463 36556, release_year, 2133 32731, has_genre, 30463 32731, release_year, 2133 6831, has_genre, 30463 6831, release_year, 2133 10819, has_genre, 30463 10819, release_year, 2133 33439, has_genre, 30463 33439, release_year, 2133 10732, has_genre, 30463 10732, has_tags, 30463 10732, release_year, 2133 4519, has_genre, 30463 4519, release_year, 2133 36412, has_genre, 30463 36412, has_tags, 30463 36412, release_year, 2133 14696, has_genre, 30463 14696, has_tags, 30463 14696, release_year, 2133 27549, has_genre, 30463 27549, release_year, 2133 4068, has_genre, 30463 4068, has_tags, 30463 4068, release_year, 2133 40028, has_genre, 30463 40028, release_year, 2133 17872, has_genre, 30463 17872, release_year, 2133 32440, has_genre, 30463 32440, release_year, 2133 4223, has_genre, 30463 4223, has_tags, 30463 4223, release_year, 2133 9059, has_genre, 30463 9059, release_year, 2133 844, has_genre, 30463 844, release_year, 2133 34003, has_genre, 30463 34003, release_year, 2133 22210, has_genre, 30463 22210, release_year, 2133 15569, has_genre, 30463 15569, release_year, 2133 24357, has_genre, 30463 24357, release_year, 2133 27932, has_genre, 30463 27932, release_year, 2133 16573, has_genre, 30463 16573, release_year, 2133 17460, has_genre, 30463 17460, release_year, 2133 36038, has_genre, 30463 36038, has_tags, 30463 36038, release_year, 2133 11628, has_genre, 30463 11628, has_tags, 30463 11628, release_year, 2133 13738, has_genre, 30463 13738, has_tags, 30463 13738, release_year, 2133 8012, has_genre, 30463 8012, has_tags, 30463 8012, release_year, 2133 15511, has_genre, 30463 15511, release_year, 2133 7379, has_genre, 30463 7379, release_year, 2133 4736, has_genre, 30463 4736, release_year, 2133 19679, has_genre, 30463 19679, release_year, 2133 25949, has_genre, 30463 25949, release_year, 2133 9552, has_genre, 30463 9552, release_year, 2133 15808, has_genre, 30463 15808, has_tags, 30463 15808, release_year, 2133 Question: In what context are GLASBLÅSARNS BARN, HOUSEBOUND, and MACKENZIE CROOK connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GLASBLÅSARNS BARN", "HOUSEBOUND", "MACKENZIE CROOK" ], "valid_edges": [ [ "A BUG'S LIFE", "has_genre", "COMEDY" ], [ "A BUG'S LIFE", "has_tags", "COMEDY" ], [ "A BUG'S LIFE", "release_year", "1998" ], [ "A NIGHT AT THE ROXBURY", "has_genre", "COMEDY" ], [ "A NIGHT AT THE ROXBURY", "release_year", "1998" ], [ "ALMOST HEROES", "has_genre", "COMEDY" ], [ "ALMOST HEROES", "release_year", "1998" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "release_year", "1998" ], [ "BASEKETBALL", "has_genre", "COMEDY" ], [ "BASEKETBALL", "has_tags", "COMEDY" ], [ "BASEKETBALL", "release_year", "1998" ], [ "BEDROOMS AND HALLWAYS", "has_genre", "COMEDY" ], [ "BEDROOMS AND HALLWAYS", "release_year", "1998" ], [ "BILLY'S HOLLYWOOD SCREEN KISS", "has_genre", "COMEDY" ], [ "BILLY'S HOLLYWOOD SCREEN KISS", "release_year", "1998" ], [ "BLACK CAT, WHITE CAT", "has_genre", "COMEDY" ], [ "BLACK CAT, WHITE CAT", "release_year", "1998" ], [ "BLOOD, GUTS, BULLETS AND OCTANE", "has_genre", "COMEDY" ], [ "BLOOD, GUTS, BULLETS AND OCTANE", "release_year", "1998" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "release_year", "1998" ], [ "BRIDE OF CHUCKY", "has_genre", "COMEDY" ], [ "BRIDE OF CHUCKY", "release_year", "1998" ], [ "BUFFALO '66", "has_genre", "COMEDY" ], [ "BUFFALO '66", "release_year", "1998" ], [ "BULWORTH", "has_genre", "COMEDY" ], [ "BULWORTH", "has_tags", "COMEDY" ], [ "BULWORTH", "release_year", "1998" ], [ "CAN'T HARDLY WAIT", "has_genre", "COMEDY" ], [ "CAN'T HARDLY WAIT", "release_year", "1998" ], [ "CELEBRITY", "has_genre", "COMEDY" ], [ "CELEBRITY", "release_year", "1998" ], [ "CLAY PIGEONS", "has_genre", "COMEDY" ], [ "CLAY PIGEONS", "release_year", "1998" ], [ "COUSIN BETTE", "has_genre", "COMEDY" ], [ "COUSIN BETTE", "release_year", "1998" ], [ "DANCER, TEXAS POP. 81", "has_genre", "COMEDY" ], [ "DANCER, TEXAS POP. 81", "release_year", "1998" ], [ "DEAD HUSBANDS", "has_genre", "COMEDY" ], [ "DEAD HUSBANDS", "release_year", "1998" ], [ "DEAD MAN ON CAMPUS", "has_genre", "COMEDY" ], [ "DEAD MAN ON CAMPUS", "release_year", "1998" ], [ "DECAMPITATED", "has_genre", "COMEDY" ], [ "DECAMPITATED", "release_year", "1998" ], [ "DIRTY WORK", "has_genre", "COMEDY" ], [ "DIRTY WORK", "has_tags", "COMEDY" ], [ "DIRTY WORK", "release_year", "1998" ], [ "DIVORCING JACK", "has_genre", "COMEDY" ], [ "DIVORCING JACK", "has_tags", "COMEDY" ], [ "DIVORCING JACK", "release_year", "1998" ], [ "DOG PARK", "has_genre", "COMEDY" ], [ "DOG PARK", "release_year", "1998" ], [ "DUPLICATE", "has_genre", "COMEDY" ], [ "DUPLICATE", "release_year", "1998" ], [ "EDGE OF SEVENTEEN", "has_genre", "COMEDY" ], [ "EDGE OF SEVENTEEN", "release_year", "1998" ], [ "ERNEST IN THE ARMY", "has_genre", "COMEDY" ], [ "ERNEST IN THE ARMY", "release_year", "1998" ], [ "FEAR AND LOATHING IN LAS VEGAS", "has_genre", "COMEDY" ], [ "FEAR AND LOATHING IN LAS VEGAS", "has_tags", "COMEDY" ], [ "FEAR AND LOATHING IN LAS VEGAS", "release_year", "1998" ], [ "FINDING NORTH", "has_genre", "COMEDY" ], [ "FINDING NORTH", "release_year", "1998" ], [ "FREE MONEY", "has_genre", "COMEDY" ], [ "FREE MONEY", "release_year", "1998" ], [ "GLASBLÅSARNS BARN", "release_year", "1998" ], [ "HALF BAKED", "has_genre", "COMEDY" ], [ "HALF BAKED", "has_tags", "COMEDY" ], [ "HALF BAKED", "release_year", "1998" ], [ "HAPPINESS", "has_genre", "COMEDY" ], [ "HAPPINESS", "release_year", "1998" ], [ "HOLY MAN", "has_genre", "COMEDY" ], [ "HOLY MAN", "release_year", "1998" ], [ "HOMEGROWN", "has_genre", "COMEDY" ], [ "HOMEGROWN", "release_year", "1998" ], [ "HOUSEBOUND", "has_genre", "COMEDY" ], [ "I GOT THE HOOK UP", "has_genre", "COMEDY" ], [ "I GOT THE HOOK UP", "release_year", "1998" ], [ "I'LL BE HOME FOR CHRISTMAS", "has_genre", "COMEDY" ], [ "I'LL BE HOME FOR CHRISTMAS", "release_year", "1998" ], [ "JACK FROST", "has_genre", "COMEDY" ], [ "JACK FROST", "release_year", "1998" ], [ "JERRY AND TOM", "has_genre", "COMEDY" ], [ "JERRY AND TOM", "release_year", "1998" ], [ "KISSING A FOOL", "has_genre", "COMEDY" ], [ "KISSING A FOOL", "release_year", "1998" ], [ "KUCH KUCH HOTA HAI", "has_genre", "COMEDY" ], [ "KUCH KUCH HOTA HAI", "release_year", "1998" ], [ "LIVING OUT LOUD", "has_genre", "COMEDY" ], [ "LIVING OUT LOUD", "release_year", "1998" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_genre", "COMEDY" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_tags", "COMEDY" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "release_year", "1998" ], [ "MEET THE DEEDLES", "has_genre", "COMEDY" ], [ "MEET THE DEEDLES", "release_year", "1998" ], [ "MIDNIGHT", "has_genre", "COMEDY" ], [ "MIDNIGHT", "release_year", "1998" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "COMEDY" ], [ "MUSIC FROM ANOTHER ROOM", "release_year", "1998" ], [ "MY GIANT", "has_genre", "COMEDY" ], [ "MY GIANT", "release_year", "1998" ], [ "NEXT STOP WONDERLAND", "has_genre", "COMEDY" ], [ "NEXT STOP WONDERLAND", "release_year", "1998" ], [ "ORPHANS", "has_genre", "COMEDY" ], [ "ORPHANS", "release_year", "1998" ], [ "OUT OF SIGHT", "has_genre", "COMEDY" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "OVERNIGHT DELIVERY", "has_genre", "COMEDY" ], [ "OVERNIGHT DELIVERY", "release_year", "1998" ], [ "PATCH ADAMS", "has_genre", "COMEDY" ], [ "PATCH ADAMS", "release_year", "1998" ], [ "PECKER", "has_genre", "COMEDY" ], [ "PECKER", "release_year", "1998" ], [ "PLEASANTVILLE", "has_genre", "COMEDY" ], [ "PLEASANTVILLE", "release_year", "1998" ], [ "POLISH WEDDING", "has_genre", "COMEDY" ], [ "POLISH WEDDING", "release_year", "1998" ], [ "PRACTICAL MAGIC", "has_genre", "COMEDY" ], [ "PRACTICAL MAGIC", "release_year", "1998" ], [ "RIDE", "has_genre", "COMEDY" ], [ "RIDE", "release_year", "1998" ], [ "RINGMASTER", "has_genre", "COMEDY" ], [ "RINGMASTER", "release_year", "1998" ], [ "RUSH HOUR", "has_genre", "COMEDY" ], [ "RUSH HOUR", "has_tags", "COMEDY" ], [ "RUSH HOUR", "release_year", "1998" ], [ "RUSHMORE", "has_genre", "COMEDY" ], [ "RUSHMORE", "has_tags", "COMEDY" ], [ "RUSHMORE", "release_year", "1998" ], [ "SAFE MEN", "has_genre", "COMEDY" ], [ "SAFE MEN", "release_year", "1998" ], [ "SAMURAI FICTION", "has_genre", "COMEDY" ], [ "SAMURAI FICTION", "release_year", "1998" ], [ "SENSELESS", "has_genre", "COMEDY" ], [ "SENSELESS", "release_year", "1998" ], [ "SEX LIVES OF THE POTATO MEN", "has_genre", "COMEDY" ], [ "SEX LIVES OF THE POTATO MEN", "starred_actors", "MACKENZIE CROOK" ], [ "SHAKESPEARE IN LOVE", "has_genre", "COMEDY" ], [ "SHAKESPEARE IN LOVE", "release_year", "1998" ], [ "SIMON BIRCH", "has_genre", "COMEDY" ], [ "SIMON BIRCH", "release_year", "1998" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "release_year", "1998" ], [ "SIX-STRING SAMURAI", "has_genre", "COMEDY" ], [ "SIX-STRING SAMURAI", "release_year", "1998" ], [ "SLAPPY AND THE STINKERS", "has_genre", "COMEDY" ], [ "SLAPPY AND THE STINKERS", "release_year", "1998" ], [ "SLC PUNK!", "has_genre", "COMEDY" ], [ "SLC PUNK!", "release_year", "1998" ], [ "SLIDING DOORS", "has_genre", "COMEDY" ], [ "SLIDING DOORS", "release_year", "1998" ], [ "SLUMS OF BEVERLY HILLS", "has_genre", "COMEDY" ], [ "SLUMS OF BEVERLY HILLS", "release_year", "1998" ], [ "SMALL SOLDIERS", "has_genre", "COMEDY" ], [ "SMALL SOLDIERS", "release_year", "1998" ], [ "SOME GIRL", "has_genre", "COMEDY" ], [ "SOME GIRL", "release_year", "1998" ], [ "SOMEWHERE IN THE CITY", "has_genre", "COMEDY" ], [ "SOMEWHERE IN THE CITY", "release_year", "1998" ], [ "SOUR GRAPES", "has_genre", "COMEDY" ], [ "SOUR GRAPES", "release_year", "1998" ], [ "STEPMOM", "has_genre", "COMEDY" ], [ "STEPMOM", "release_year", "1998" ], [ "TAXI", "has_genre", "COMEDY" ], [ "TAXI", "has_tags", "COMEDY" ], [ "TAXI", "release_year", "1998" ], [ "THE ADVENTURES OF SEBASTIAN COLE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF SEBASTIAN COLE", "release_year", "1998" ], [ "THE BIG HIT", "has_genre", "COMEDY" ], [ "THE BIG HIT", "has_tags", "COMEDY" ], [ "THE BIG HIT", "release_year", "1998" ], [ "THE BIG LEBOWSKI", "has_genre", "COMEDY" ], [ "THE BIG LEBOWSKI", "has_tags", "COMEDY" ], [ "THE BIG LEBOWSKI", "release_year", "1998" ], [ "THE BOOK OF LIFE", "has_genre", "COMEDY" ], [ "THE BOOK OF LIFE", "release_year", "1998" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE GENERAL", "release_year", "1998" ], [ "THE GODSON", "has_genre", "COMEDY" ], [ "THE GODSON", "release_year", "1998" ], [ "THE IDIOTS", "has_genre", "COMEDY" ], [ "THE IDIOTS", "release_year", "1998" ], [ "THE IMPOSTORS", "has_genre", "COMEDY" ], [ "THE IMPOSTORS", "release_year", "1998" ], [ "THE INTERVIEW", "has_genre", "COMEDY" ], [ "THE INTERVIEW", "has_tags", "COMEDY" ], [ "THE INTERVIEW", "release_year", "1998" ], [ "THE LAST DAYS OF DISCO", "has_genre", "COMEDY" ], [ "THE LAST DAYS OF DISCO", "release_year", "1998" ], [ "THE LOVE LETTER", "has_genre", "COMEDY" ], [ "THE LOVE LETTER", "release_year", "1998" ], [ "THE MISADVENTURES OF MARGARET", "has_genre", "COMEDY" ], [ "THE MISADVENTURES OF MARGARET", "release_year", "1998" ], [ "THE NAKED MAN", "has_genre", "COMEDY" ], [ "THE NAKED MAN", "release_year", "1998" ], [ "THE OBJECT OF MY AFFECTION", "has_genre", "COMEDY" ], [ "THE OBJECT OF MY AFFECTION", "release_year", "1998" ], [ "THE PARENT TRAP", "has_genre", "COMEDY" ], [ "THE PARENT TRAP", "release_year", "1998" ], [ "THE PENTAGON WARS", "has_genre", "COMEDY" ], [ "THE PENTAGON WARS", "release_year", "1998" ], [ "THE PLAYERS CLUB", "has_genre", "COMEDY" ], [ "THE PLAYERS CLUB", "release_year", "1998" ], [ "THE RUGRATS MOVIE", "has_genre", "COMEDY" ], [ "THE RUGRATS MOVIE", "release_year", "1998" ], [ "THE WATERBOY", "has_genre", "COMEDY" ], [ "THE WATERBOY", "has_tags", "COMEDY" ], [ "THE WATERBOY", "release_year", "1998" ], [ "THE WEDDING SINGER", "has_genre", "COMEDY" ], [ "THE WEDDING SINGER", "has_tags", "COMEDY" ], [ "THE WEDDING SINGER", "release_year", "1998" ], [ "THERE'S SOMETHING ABOUT MARY", "has_genre", "COMEDY" ], [ "THERE'S SOMETHING ABOUT MARY", "has_tags", "COMEDY" ], [ "THERE'S SOMETHING ABOUT MARY", "release_year", "1998" ], [ "TOMORROW NIGHT", "has_genre", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "COMEDY" ], [ "TOMORROW NIGHT", "release_year", "1998" ], [ "TORRENTE, EL BRAZO TONTO DE LA LEY", "has_genre", "COMEDY" ], [ "TORRENTE, EL BRAZO TONTO DE LA LEY", "release_year", "1998" ], [ "VERY BAD THINGS", "has_genre", "COMEDY" ], [ "VERY BAD THINGS", "release_year", "1998" ], [ "WHERE'S MARLOWE?", "has_genre", "COMEDY" ], [ "WHERE'S MARLOWE?", "release_year", "1998" ], [ "WIDE AWAKE", "has_genre", "COMEDY" ], [ "WIDE AWAKE", "release_year", "1998" ], [ "WOO", "has_genre", "COMEDY" ], [ "WOO", "release_year", "1998" ], [ "WRONGFULLY ACCUSED", "has_genre", "COMEDY" ], [ "WRONGFULLY ACCUSED", "release_year", "1998" ], [ "YOU'VE GOT MAIL", "has_genre", "COMEDY" ], [ "YOU'VE GOT MAIL", "has_tags", "COMEDY" ], [ "YOU'VE GOT MAIL", "release_year", "1998" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 9655, EXECUTION 5870, HORROR 37036, JACK BENNY 18923, ROBERT HILTZIK 18299, SLEEPAWAY CAMP 37380, THE HORROR SHOW 3640, TO BE OR NOT TO BE src, edge_attr, dst 18299, directed_by, 18923 18299, has_genre, 5870 18299, has_tags, 5870 18299, release_year, 16055 18299, written_by, 18923 37380, has_genre, 5870 37380, has_tags, 9655 3640, release_year, 16055 3640, starred_actors, 37036 Question: How are EXECUTION, JACK BENNY, and ROBERT HILTZIK related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EXECUTION", "JACK BENNY", "ROBERT HILTZIK" ], "valid_edges": [ [ "SLEEPAWAY CAMP", "directed_by", "ROBERT HILTZIK" ], [ "SLEEPAWAY CAMP", "has_genre", "HORROR" ], [ "SLEEPAWAY CAMP", "has_tags", "HORROR" ], [ "SLEEPAWAY CAMP", "release_year", "1983" ], [ "SLEEPAWAY CAMP", "written_by", "ROBERT HILTZIK" ], [ "THE HORROR SHOW", "has_genre", "HORROR" ], [ "THE HORROR SHOW", "has_tags", "EXECUTION" ], [ "TO BE OR NOT TO BE", "release_year", "1983" ], [ "TO BE OR NOT TO BE", "starred_actors", "JACK BENNY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4763, ADVENTURE 14409, ANTHONY ANDERSON 9449, ARTHUR MAYSE 30463, COMEDY 35313, DESPERATE SEARCH 36212, DRAMA 37372, JUNO 2368, KANGAROO JACK 12571, TEEN 38200, TEENAGER 17931, THE BREAKFAST CLUB src, edge_attr, dst 35313, has_genre, 4763 35313, has_genre, 36212 35313, written_by, 9449 37372, has_genre, 30463 37372, has_genre, 36212 37372, has_tags, 30463 37372, has_tags, 12571 37372, has_tags, 38200 2368, has_genre, 4763 2368, has_genre, 30463 2368, has_tags, 30463 2368, starred_actors, 14409 17931, has_genre, 30463 17931, has_genre, 36212 17931, has_tags, 30463 17931, has_tags, 36212 17931, has_tags, 12571 17931, has_tags, 38200 Question: In what context are ANTHONY ANDERSON, ARTHUR MAYSE, and TEENAGER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANTHONY ANDERSON", "ARTHUR MAYSE", "TEENAGER" ], "valid_edges": [ [ "DESPERATE SEARCH", "has_genre", "ADVENTURE" ], [ "DESPERATE SEARCH", "has_genre", "DRAMA" ], [ "DESPERATE SEARCH", "written_by", "ARTHUR MAYSE" ], [ "JUNO", "has_genre", "COMEDY" ], [ "JUNO", "has_genre", "DRAMA" ], [ "JUNO", "has_tags", "COMEDY" ], [ "JUNO", "has_tags", "TEEN" ], [ "JUNO", "has_tags", "TEENAGER" ], [ "KANGAROO JACK", "has_genre", "ADVENTURE" ], [ "KANGAROO JACK", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_tags", "COMEDY" ], [ "KANGAROO JACK", "starred_actors", "ANTHONY ANDERSON" ], [ "THE BREAKFAST CLUB", "has_genre", "COMEDY" ], [ "THE BREAKFAST CLUB", "has_genre", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "COMEDY" ], [ "THE BREAKFAST CLUB", "has_tags", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "TEEN" ], [ "THE BREAKFAST CLUB", "has_tags", "TEENAGER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35798, 2010 14771, A CAT IN PARIS 32158, A SCREAMING MAN 39824, BABIES 10045, BD-R 7051, BLACK VENUS 5840, CERTIFIED COPY 33512, DUE DATE 8176, FAREWELL 6012, FRENCH 11783, HEARTBREAKER 5387, HEREAFTER 10124, JOHN KORTY 16814, LITTLE WHITE LIES 9792, LOVE CRIME 19594, MAMMUTH 33422, MAN AT BATH 18073, MOZART'S SISTER 5452, MY AFTERNOONS WITH MARGUERITTE 12152, NOTHING TO DECLARE 27983, OF GODS AND MEN 32901, ON TOUR 745, OUR DAY WILL COME 35556, OUTSIDE THE LAW 21835, POINT BLANK 11213, POTICHE 3729, ROMANTICS ANONYMOUS 32454, THE BIG PICTURE 39773, THE CLINK OF ICE 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 25529, THE ILLUSIONIST 33265, THE NAMES OF LOVE 27456, THE PRINCESS OF MONTPENSIER 23150, THE WOMEN ON THE 6TH FLOOR 24440, TOUT CE QUI BRILLE 39715, TWICE UPON A TIME 16992, TWO IN THE WAVE 367, WITH LOVE... FROM THE AGE OF REASON src, edge_attr, dst 35798, has_tags, 10045 14771, in_language, 6012 14771, release_year, 35798 32158, in_language, 6012 32158, release_year, 35798 39824, has_tags, 6012 39824, release_year, 35798 7051, in_language, 6012 7051, release_year, 35798 5840, in_language, 6012 5840, release_year, 35798 33512, release_year, 35798 8176, in_language, 6012 11783, has_tags, 6012 11783, in_language, 6012 11783, release_year, 35798 5387, has_tags, 6012 5387, in_language, 6012 5387, release_year, 35798 16814, in_language, 6012 16814, release_year, 35798 9792, in_language, 6012 9792, release_year, 35798 19594, in_language, 6012 19594, release_year, 35798 33422, has_tags, 6012 33422, in_language, 6012 33422, release_year, 35798 18073, in_language, 6012 18073, release_year, 35798 5452, in_language, 6012 5452, release_year, 35798 12152, in_language, 6012 12152, release_year, 35798 27983, in_language, 6012 27983, release_year, 35798 32901, in_language, 6012 32901, release_year, 35798 745, in_language, 6012 745, release_year, 35798 35556, has_tags, 6012 35556, in_language, 6012 35556, release_year, 35798 21835, in_language, 6012 21835, release_year, 35798 11213, in_language, 6012 11213, release_year, 35798 3729, has_tags, 6012 3729, in_language, 6012 3729, release_year, 35798 32454, has_tags, 6012 32454, in_language, 6012 32454, release_year, 35798 39773, in_language, 6012 39773, release_year, 35798 10344, has_tags, 6012 10344, in_language, 6012 10344, release_year, 35798 25529, in_language, 6012 25529, release_year, 35798 33265, has_tags, 6012 33265, in_language, 6012 33265, release_year, 35798 27456, in_language, 6012 27456, release_year, 35798 23150, in_language, 6012 23150, release_year, 35798 24440, in_language, 6012 24440, release_year, 35798 39715, directed_by, 10124 39715, has_tags, 10045 39715, has_tags, 10124 39715, written_by, 10124 16992, in_language, 6012 16992, release_year, 35798 367, in_language, 6012 367, release_year, 35798 Question: In what context are DUE DATE, FAREWELL, and JOHN KORTY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DUE DATE", "FAREWELL", "JOHN KORTY" ], "valid_edges": [ [ "2010", "has_tags", "BD-R" ], [ "A CAT IN PARIS", "in_language", "FRENCH" ], [ "A CAT IN PARIS", "release_year", "2010" ], [ "A SCREAMING MAN", "in_language", "FRENCH" ], [ "A SCREAMING MAN", "release_year", "2010" ], [ "BABIES", "has_tags", "FRENCH" ], [ "BABIES", "release_year", "2010" ], [ "BLACK VENUS", "in_language", "FRENCH" ], [ "BLACK VENUS", "release_year", "2010" ], [ "CERTIFIED COPY", "in_language", "FRENCH" ], [ "CERTIFIED COPY", "release_year", "2010" ], [ "DUE DATE", "release_year", "2010" ], [ "FAREWELL", "in_language", "FRENCH" ], [ "HEARTBREAKER", "has_tags", "FRENCH" ], [ "HEARTBREAKER", "in_language", "FRENCH" ], [ "HEARTBREAKER", "release_year", "2010" ], [ "HEREAFTER", "has_tags", "FRENCH" ], [ "HEREAFTER", "in_language", "FRENCH" ], [ "HEREAFTER", "release_year", "2010" ], [ "LITTLE WHITE LIES", "in_language", "FRENCH" ], [ "LITTLE WHITE LIES", "release_year", "2010" ], [ "LOVE CRIME", "in_language", "FRENCH" ], [ "LOVE CRIME", "release_year", "2010" ], [ "MAMMUTH", "in_language", "FRENCH" ], [ "MAMMUTH", "release_year", "2010" ], [ "MAN AT BATH", "has_tags", "FRENCH" ], [ "MAN AT BATH", "in_language", "FRENCH" ], [ "MAN AT BATH", "release_year", "2010" ], [ "MOZART'S SISTER", "in_language", "FRENCH" ], [ "MOZART'S SISTER", "release_year", "2010" ], [ "MY AFTERNOONS WITH MARGUERITTE", "in_language", "FRENCH" ], [ "MY AFTERNOONS WITH MARGUERITTE", "release_year", "2010" ], [ "NOTHING TO DECLARE", "in_language", "FRENCH" ], [ "NOTHING TO DECLARE", "release_year", "2010" ], [ "OF GODS AND MEN", "in_language", "FRENCH" ], [ "OF GODS AND MEN", "release_year", "2010" ], [ "ON TOUR", "in_language", "FRENCH" ], [ "ON TOUR", "release_year", "2010" ], [ "OUR DAY WILL COME", "in_language", "FRENCH" ], [ "OUR DAY WILL COME", "release_year", "2010" ], [ "OUTSIDE THE LAW", "has_tags", "FRENCH" ], [ "OUTSIDE THE LAW", "in_language", "FRENCH" ], [ "OUTSIDE THE LAW", "release_year", "2010" ], [ "POINT BLANK", "in_language", "FRENCH" ], [ "POINT BLANK", "release_year", "2010" ], [ "POTICHE", "in_language", "FRENCH" ], [ "POTICHE", "release_year", "2010" ], [ "ROMANTICS ANONYMOUS", "has_tags", "FRENCH" ], [ "ROMANTICS ANONYMOUS", "in_language", "FRENCH" ], [ "ROMANTICS ANONYMOUS", "release_year", "2010" ], [ "THE BIG PICTURE", "has_tags", "FRENCH" ], [ "THE BIG PICTURE", "in_language", "FRENCH" ], [ "THE BIG PICTURE", "release_year", "2010" ], [ "THE CLINK OF ICE", "in_language", "FRENCH" ], [ "THE CLINK OF ICE", "release_year", "2010" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_tags", "FRENCH" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "in_language", "FRENCH" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "release_year", "2010" ], [ "THE ILLUSIONIST", "in_language", "FRENCH" ], [ "THE ILLUSIONIST", "release_year", "2010" ], [ "THE NAMES OF LOVE", "has_tags", "FRENCH" ], [ "THE NAMES OF LOVE", "in_language", "FRENCH" ], [ "THE NAMES OF LOVE", "release_year", "2010" ], [ "THE PRINCESS OF MONTPENSIER", "in_language", "FRENCH" ], [ "THE PRINCESS OF MONTPENSIER", "release_year", "2010" ], [ "THE WOMEN ON THE 6TH FLOOR", "in_language", "FRENCH" ], [ "THE WOMEN ON THE 6TH FLOOR", "release_year", "2010" ], [ "TOUT CE QUI BRILLE", "in_language", "FRENCH" ], [ "TOUT CE QUI BRILLE", "release_year", "2010" ], [ "TWICE UPON A TIME", "directed_by", "JOHN KORTY" ], [ "TWICE UPON A TIME", "has_tags", "BD-R" ], [ "TWICE UPON A TIME", "has_tags", "JOHN KORTY" ], [ "TWICE UPON A TIME", "written_by", "JOHN KORTY" ], [ "TWO IN THE WAVE", "in_language", "FRENCH" ], [ "TWO IN THE WAVE", "release_year", "2010" ], [ "WITH LOVE... FROM THE AGE OF REASON", "in_language", "FRENCH" ], [ "WITH LOVE... FROM THE AGE OF REASON", "release_year", "2010" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 17480, 1988 24438, 1993 37616, BORN YESTERDAY 7646, D.O.A. 27105, HERO AND THE TERROR 11421, STEFANO QUANTESTORIE 11310, THE REFORMER AND THE REDHEAD 17568, THE VANISHING src, edge_attr, dst 37616, release_year, 26423 37616, release_year, 24438 7646, release_year, 26423 7646, release_year, 17480 27105, release_year, 17480 11421, release_year, 24438 11310, release_year, 26423 17568, release_year, 17480 17568, release_year, 24438 Question: For what reason are HERO AND THE TERROR, STEFANO QUANTESTORIE, and THE REFORMER AND THE REDHEAD associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HERO AND THE TERROR", "STEFANO QUANTESTORIE", "THE REFORMER AND THE REDHEAD" ], "valid_edges": [ [ "BORN YESTERDAY", "release_year", "1950" ], [ "BORN YESTERDAY", "release_year", "1993" ], [ "D.O.A.", "release_year", "1950" ], [ "D.O.A.", "release_year", "1988" ], [ "HERO AND THE TERROR", "release_year", "1988" ], [ "STEFANO QUANTESTORIE", "release_year", "1993" ], [ "THE REFORMER AND THE REDHEAD", "release_year", "1950" ], [ "THE VANISHING", "release_year", "1988" ], [ "THE VANISHING", "release_year", "1993" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 29628, 28 DAYS 33688, ABERDEEN 21087, ADANGGAMAN 29155, ADRIAN HODGES 25900, ALMOST FAMOUS 37611, ANIMAL FACTORY 9078, APRIL CAPTAINS 24455, AUTUMN IN NEW YORK 33000, BAD LUCK LOVE 668, BATTLE FOR HADITHA 33410, BEFORE NIGHT FALLS 34615, BIG EDEN 39085, BILLY ELLIOT 3292, BOILER ROOM 18836, BOOTMEN 26583, BOUNCE 18439, BREAD AND ROSES 25059, CAST AWAY 395, CENTER STAGE 4476, CHOCOLAT 9601, COMEDY OF INNOCENCE 34253, COYOTE UGLY 19379, CRUEL INTENTIONS 2 3465, DANCER IN THE DARK 22930, DANCING AT THE BLUE IGUANA 22665, DIAMOND MEN 35235, DIRTY PICTURES 36212, DRAMA 27336, ERIN BROCKOVICH 16970, EUREKA 35306, EVERYTHING PUT TOGETHER 34004, FAIL SAFE 7108, FAITHLESS 8272, FINAL DESTINATION 34503, FINDING FORRESTER 32434, GEORGE WASHINGTON 4685, GIRLFIGHT 9778, GLADIATOR 32380, GOSSIP 20941, HAMLET 13413, HANGING UP 35023, HERE ON EARTH 6785, HEY RAM 22945, HIGH FIDELITY 33603, HOW TO KILL YOUR NEIGHBOR'S DOG 35899, JOE GOULD'S SECRET 37108, KING OF THE JUNGLE 17279, KIPPUR 40116, LAKEBOAT 18494, LIAM 1130, LISA PICARD IS FAMOUS 14822, LOCKDOWN 34628, MALÈNA 32842, ME YOU THEM 24153, MEN OF HONOR 21701, MERCY STREETS 31515, METROLAND 25561, MOHABBATEIN 2487, MY WEEK WITH MARILYN 1922, NINE QUEENS 30889, ON THE BEACH 28530, PASSION OF MIND 9995, PAY IT FORWARD 27893, POSSESSED 37084, PRICE OF GLORY 1687, PURELY BELTER 28745, RED PLANET 5193, REMEMBER THE TITANS 34510, REQUIEM FOR A DREAM 35664, RESTLESS 1372, RETURN TO ME 6759, RULES OF ENGAGEMENT 20488, SONGCATCHER 19388, STARDOM 30787, SUCH IS LIFE 2268, SUNSET STRIP 37356, SUSPICIOUS RIVER 30285, THE BEACH 16983, THE BENCH 5013, THE CIRCLE 15323, THE CONTENDER 16929, THE GIRL 39873, THE GOLDEN BOWL 29697, THE MILLION DOLLAR HOTEL 20674, THE NEXT BEST THING 36328, THE OPPORTUNISTS 39217, THE PERFECT STORM 29326, THE PRINCESS AND THE WARRIOR 29643, THE TAO OF STEVE 11250, THE TOWN IS QUIET 11360, THIRTEEN DAYS 3934, TIGERLAND 22625, TOGETHER 33836, TRAFFIC 24743, TULLY 24452, UNBREAKABLE 26494, UNDER SUSPICION 38911, WAKING THE DEAD 1183, WATER DROPS ON BURNING ROCKS 1524, WHAT LIES BENEATH 3572, WHAT'S COOKING? 33070, WHERE THE HEART IS 12162, YOU CAN COUNT ON ME src, edge_attr, dst 29628, has_genre, 36212 29628, release_year, 6776 33688, has_genre, 36212 33688, release_year, 6776 21087, has_genre, 36212 21087, release_year, 6776 25900, has_genre, 36212 25900, has_tags, 36212 25900, release_year, 6776 37611, has_genre, 36212 37611, release_year, 6776 9078, has_genre, 36212 9078, release_year, 6776 24455, has_genre, 36212 24455, release_year, 6776 33000, has_genre, 36212 33000, release_year, 6776 668, has_genre, 36212 33410, has_genre, 36212 33410, release_year, 6776 34615, has_genre, 36212 34615, release_year, 6776 39085, has_genre, 36212 39085, has_tags, 36212 39085, release_year, 6776 3292, has_genre, 36212 3292, release_year, 6776 18836, has_genre, 36212 18836, release_year, 6776 26583, has_genre, 36212 26583, release_year, 6776 18439, has_genre, 36212 18439, release_year, 6776 25059, has_genre, 36212 25059, has_tags, 36212 25059, release_year, 6776 395, has_genre, 36212 395, release_year, 6776 4476, has_genre, 36212 4476, release_year, 6776 9601, has_genre, 36212 9601, release_year, 6776 34253, has_genre, 36212 34253, release_year, 6776 19379, has_genre, 36212 19379, release_year, 6776 3465, has_genre, 36212 3465, has_tags, 36212 3465, release_year, 6776 22930, has_genre, 36212 22930, release_year, 6776 22665, has_genre, 36212 22665, release_year, 6776 35235, has_genre, 36212 35235, release_year, 6776 27336, has_genre, 36212 27336, has_tags, 36212 27336, release_year, 6776 16970, has_genre, 36212 16970, release_year, 6776 35306, has_genre, 36212 35306, release_year, 6776 34004, has_genre, 36212 34004, has_tags, 36212 34004, release_year, 6776 7108, has_genre, 36212 7108, release_year, 6776 8272, has_tags, 36212 8272, release_year, 6776 34503, has_genre, 36212 34503, release_year, 6776 32434, has_genre, 36212 32434, release_year, 6776 4685, has_genre, 36212 4685, has_tags, 36212 4685, release_year, 6776 9778, has_genre, 36212 9778, has_tags, 36212 9778, release_year, 6776 32380, has_genre, 36212 32380, release_year, 6776 20941, has_genre, 36212 20941, has_tags, 36212 20941, release_year, 6776 13413, has_genre, 36212 13413, release_year, 6776 35023, has_genre, 36212 35023, release_year, 6776 6785, has_genre, 36212 6785, release_year, 6776 22945, has_genre, 36212 22945, has_tags, 36212 22945, release_year, 6776 33603, has_genre, 36212 33603, release_year, 6776 35899, has_genre, 36212 35899, release_year, 6776 37108, has_genre, 36212 37108, release_year, 6776 17279, has_genre, 36212 17279, release_year, 6776 40116, has_genre, 36212 40116, release_year, 6776 18494, has_genre, 36212 18494, release_year, 6776 1130, has_genre, 36212 1130, release_year, 6776 14822, has_genre, 36212 14822, release_year, 6776 34628, has_genre, 36212 34628, has_tags, 36212 34628, release_year, 6776 32842, has_genre, 36212 32842, release_year, 6776 24153, has_genre, 36212 24153, release_year, 6776 21701, has_genre, 36212 21701, release_year, 6776 31515, has_genre, 36212 31515, written_by, 29155 25561, has_genre, 36212 25561, release_year, 6776 2487, has_genre, 36212 2487, written_by, 29155 1922, has_genre, 36212 1922, release_year, 6776 30889, has_genre, 36212 30889, release_year, 6776 28530, has_genre, 36212 28530, release_year, 6776 9995, has_genre, 36212 9995, has_tags, 36212 9995, release_year, 6776 27893, has_genre, 36212 27893, release_year, 6776 37084, has_genre, 36212 37084, release_year, 6776 1687, has_genre, 36212 1687, release_year, 6776 28745, release_year, 6776 5193, has_genre, 36212 5193, has_tags, 36212 5193, release_year, 6776 34510, has_genre, 36212 34510, has_tags, 36212 34510, release_year, 6776 35664, has_genre, 36212 35664, release_year, 6776 1372, has_genre, 36212 1372, release_year, 6776 6759, has_genre, 36212 6759, release_year, 6776 20488, has_genre, 36212 20488, has_tags, 36212 20488, release_year, 6776 19388, has_genre, 36212 19388, release_year, 6776 30787, has_genre, 36212 30787, release_year, 6776 2268, has_genre, 36212 2268, release_year, 6776 37356, has_genre, 36212 37356, release_year, 6776 30285, has_genre, 36212 30285, release_year, 6776 16983, has_genre, 36212 16983, release_year, 6776 5013, has_genre, 36212 5013, release_year, 6776 15323, has_genre, 36212 15323, release_year, 6776 16929, has_genre, 36212 16929, release_year, 6776 39873, has_genre, 36212 39873, release_year, 6776 29697, has_genre, 36212 29697, has_tags, 36212 29697, release_year, 6776 20674, has_genre, 36212 20674, release_year, 6776 36328, has_genre, 36212 36328, release_year, 6776 39217, has_genre, 36212 39217, has_tags, 36212 39217, release_year, 6776 29326, has_genre, 36212 29326, release_year, 6776 29643, has_genre, 36212 29643, release_year, 6776 11250, has_genre, 36212 11250, release_year, 6776 11360, has_genre, 36212 11360, release_year, 6776 3934, has_genre, 36212 3934, release_year, 6776 22625, has_genre, 36212 22625, release_year, 6776 33836, has_genre, 36212 33836, release_year, 6776 24743, has_genre, 36212 24743, release_year, 6776 24452, has_genre, 36212 24452, release_year, 6776 26494, has_genre, 36212 26494, release_year, 6776 38911, has_genre, 36212 38911, has_tags, 36212 38911, release_year, 6776 1183, has_genre, 36212 1183, release_year, 6776 1524, has_genre, 36212 1524, release_year, 6776 3572, has_genre, 36212 3572, release_year, 6776 33070, has_genre, 36212 33070, release_year, 6776 12162, has_genre, 36212 12162, release_year, 6776 Question: For what reason are ADRIAN HODGES, BATTLE FOR HADITHA, and RED PLANET associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ADRIAN HODGES", "BATTLE FOR HADITHA", "RED PLANET" ], "valid_edges": [ [ "28 DAYS", "has_genre", "DRAMA" ], [ "28 DAYS", "release_year", "2000" ], [ "ABERDEEN", "has_genre", "DRAMA" ], [ "ABERDEEN", "release_year", "2000" ], [ "ADANGGAMAN", "has_genre", "DRAMA" ], [ "ADANGGAMAN", "release_year", "2000" ], [ "ALMOST FAMOUS", "has_genre", "DRAMA" ], [ "ALMOST FAMOUS", "has_tags", "DRAMA" ], [ "ALMOST FAMOUS", "release_year", "2000" ], [ "ANIMAL FACTORY", "has_genre", "DRAMA" ], [ "ANIMAL FACTORY", "release_year", "2000" ], [ "APRIL CAPTAINS", "has_genre", "DRAMA" ], [ "APRIL CAPTAINS", "release_year", "2000" ], [ "AUTUMN IN NEW YORK", "has_genre", "DRAMA" ], [ "AUTUMN IN NEW YORK", "release_year", "2000" ], [ "BAD LUCK LOVE", "has_genre", "DRAMA" ], [ "BAD LUCK LOVE", "release_year", "2000" ], [ "BATTLE FOR HADITHA", "has_genre", "DRAMA" ], [ "BEFORE NIGHT FALLS", "has_genre", "DRAMA" ], [ "BEFORE NIGHT FALLS", "release_year", "2000" ], [ "BIG EDEN", "has_genre", "DRAMA" ], [ "BIG EDEN", "release_year", "2000" ], [ "BILLY ELLIOT", "has_genre", "DRAMA" ], [ "BILLY ELLIOT", "has_tags", "DRAMA" ], [ "BILLY ELLIOT", "release_year", "2000" ], [ "BOILER ROOM", "has_genre", "DRAMA" ], [ "BOILER ROOM", "release_year", "2000" ], [ "BOOTMEN", "has_genre", "DRAMA" ], [ "BOOTMEN", "release_year", "2000" ], [ "BOUNCE", "has_genre", "DRAMA" ], [ "BOUNCE", "release_year", "2000" ], [ "BREAD AND ROSES", "has_genre", "DRAMA" ], [ "BREAD AND ROSES", "release_year", "2000" ], [ "CAST AWAY", "has_genre", "DRAMA" ], [ "CAST AWAY", "has_tags", "DRAMA" ], [ "CAST AWAY", "release_year", "2000" ], [ "CENTER STAGE", "has_genre", "DRAMA" ], [ "CENTER STAGE", "release_year", "2000" ], [ "CHOCOLAT", "has_genre", "DRAMA" ], [ "CHOCOLAT", "release_year", "2000" ], [ "COMEDY OF INNOCENCE", "has_genre", "DRAMA" ], [ "COMEDY OF INNOCENCE", "release_year", "2000" ], [ "COYOTE UGLY", "has_genre", "DRAMA" ], [ "COYOTE UGLY", "release_year", "2000" ], [ "CRUEL INTENTIONS 2", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "release_year", "2000" ], [ "DANCER IN THE DARK", "has_genre", "DRAMA" ], [ "DANCER IN THE DARK", "has_tags", "DRAMA" ], [ "DANCER IN THE DARK", "release_year", "2000" ], [ "DANCING AT THE BLUE IGUANA", "has_genre", "DRAMA" ], [ "DANCING AT THE BLUE IGUANA", "release_year", "2000" ], [ "DIAMOND MEN", "has_genre", "DRAMA" ], [ "DIAMOND MEN", "release_year", "2000" ], [ "DIRTY PICTURES", "has_genre", "DRAMA" ], [ "DIRTY PICTURES", "release_year", "2000" ], [ "ERIN BROCKOVICH", "has_genre", "DRAMA" ], [ "ERIN BROCKOVICH", "has_tags", "DRAMA" ], [ "ERIN BROCKOVICH", "release_year", "2000" ], [ "EUREKA", "has_genre", "DRAMA" ], [ "EUREKA", "release_year", "2000" ], [ "EVERYTHING PUT TOGETHER", "has_genre", "DRAMA" ], [ "EVERYTHING PUT TOGETHER", "release_year", "2000" ], [ "FAIL SAFE", "has_genre", "DRAMA" ], [ "FAIL SAFE", "has_tags", "DRAMA" ], [ "FAIL SAFE", "release_year", "2000" ], [ "FAITHLESS", "has_genre", "DRAMA" ], [ "FAITHLESS", "release_year", "2000" ], [ "FINAL DESTINATION", "has_tags", "DRAMA" ], [ "FINAL DESTINATION", "release_year", "2000" ], [ "FINDING FORRESTER", "has_genre", "DRAMA" ], [ "FINDING FORRESTER", "release_year", "2000" ], [ "GEORGE WASHINGTON", "has_genre", "DRAMA" ], [ "GEORGE WASHINGTON", "release_year", "2000" ], [ "GIRLFIGHT", "has_genre", "DRAMA" ], [ "GIRLFIGHT", "has_tags", "DRAMA" ], [ "GIRLFIGHT", "release_year", "2000" ], [ "GLADIATOR", "has_genre", "DRAMA" ], [ "GLADIATOR", "has_tags", "DRAMA" ], [ "GLADIATOR", "release_year", "2000" ], [ "GOSSIP", "has_genre", "DRAMA" ], [ "GOSSIP", "release_year", "2000" ], [ "HAMLET", "has_genre", "DRAMA" ], [ "HAMLET", "has_tags", "DRAMA" ], [ "HAMLET", "release_year", "2000" ], [ "HANGING UP", "has_genre", "DRAMA" ], [ "HANGING UP", "release_year", "2000" ], [ "HERE ON EARTH", "has_genre", "DRAMA" ], [ "HERE ON EARTH", "release_year", "2000" ], [ "HEY RAM", "has_genre", "DRAMA" ], [ "HEY RAM", "release_year", "2000" ], [ "HIGH FIDELITY", "has_genre", "DRAMA" ], [ "HIGH FIDELITY", "has_tags", "DRAMA" ], [ "HIGH FIDELITY", "release_year", "2000" ], [ "HOW TO KILL YOUR NEIGHBOR'S DOG", "has_genre", "DRAMA" ], [ "HOW TO KILL YOUR NEIGHBOR'S DOG", "release_year", "2000" ], [ "JOE GOULD'S SECRET", "has_genre", "DRAMA" ], [ "JOE GOULD'S SECRET", "release_year", "2000" ], [ "KING OF THE JUNGLE", "has_genre", "DRAMA" ], [ "KING OF THE JUNGLE", "release_year", "2000" ], [ "KIPPUR", "has_genre", "DRAMA" ], [ "KIPPUR", "release_year", "2000" ], [ "LAKEBOAT", "has_genre", "DRAMA" ], [ "LAKEBOAT", "release_year", "2000" ], [ "LIAM", "has_genre", "DRAMA" ], [ "LIAM", "release_year", "2000" ], [ "LISA PICARD IS FAMOUS", "has_genre", "DRAMA" ], [ "LISA PICARD IS FAMOUS", "release_year", "2000" ], [ "LOCKDOWN", "has_genre", "DRAMA" ], [ "LOCKDOWN", "release_year", "2000" ], [ "MALÈNA", "has_genre", "DRAMA" ], [ "MALÈNA", "has_tags", "DRAMA" ], [ "MALÈNA", "release_year", "2000" ], [ "ME YOU THEM", "has_genre", "DRAMA" ], [ "ME YOU THEM", "release_year", "2000" ], [ "MEN OF HONOR", "has_genre", "DRAMA" ], [ "MEN OF HONOR", "release_year", "2000" ], [ "MERCY STREETS", "has_genre", "DRAMA" ], [ "MERCY STREETS", "release_year", "2000" ], [ "METROLAND", "has_genre", "DRAMA" ], [ "METROLAND", "written_by", "ADRIAN HODGES" ], [ "MOHABBATEIN", "has_genre", "DRAMA" ], [ "MOHABBATEIN", "release_year", "2000" ], [ "MY WEEK WITH MARILYN", "has_genre", "DRAMA" ], [ "MY WEEK WITH MARILYN", "written_by", "ADRIAN HODGES" ], [ "NINE QUEENS", "has_genre", "DRAMA" ], [ "NINE QUEENS", "release_year", "2000" ], [ "ON THE BEACH", "has_genre", "DRAMA" ], [ "ON THE BEACH", "release_year", "2000" ], [ "PASSION OF MIND", "has_genre", "DRAMA" ], [ "PASSION OF MIND", "release_year", "2000" ], [ "PAY IT FORWARD", "has_genre", "DRAMA" ], [ "PAY IT FORWARD", "has_tags", "DRAMA" ], [ "PAY IT FORWARD", "release_year", "2000" ], [ "POSSESSED", "has_genre", "DRAMA" ], [ "POSSESSED", "release_year", "2000" ], [ "PRICE OF GLORY", "has_genre", "DRAMA" ], [ "PRICE OF GLORY", "release_year", "2000" ], [ "PURELY BELTER", "has_genre", "DRAMA" ], [ "PURELY BELTER", "release_year", "2000" ], [ "RED PLANET", "release_year", "2000" ], [ "REMEMBER THE TITANS", "has_genre", "DRAMA" ], [ "REMEMBER THE TITANS", "has_tags", "DRAMA" ], [ "REMEMBER THE TITANS", "release_year", "2000" ], [ "REQUIEM FOR A DREAM", "has_genre", "DRAMA" ], [ "REQUIEM FOR A DREAM", "has_tags", "DRAMA" ], [ "REQUIEM FOR A DREAM", "release_year", "2000" ], [ "RESTLESS", "has_genre", "DRAMA" ], [ "RESTLESS", "release_year", "2000" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "release_year", "2000" ], [ "RULES OF ENGAGEMENT", "has_genre", "DRAMA" ], [ "RULES OF ENGAGEMENT", "release_year", "2000" ], [ "SONGCATCHER", "has_genre", "DRAMA" ], [ "SONGCATCHER", "has_tags", "DRAMA" ], [ "SONGCATCHER", "release_year", "2000" ], [ "STARDOM", "has_genre", "DRAMA" ], [ "STARDOM", "release_year", "2000" ], [ "SUCH IS LIFE", "has_genre", "DRAMA" ], [ "SUCH IS LIFE", "release_year", "2000" ], [ "SUNSET STRIP", "has_genre", "DRAMA" ], [ "SUNSET STRIP", "release_year", "2000" ], [ "SUSPICIOUS RIVER", "has_genre", "DRAMA" ], [ "SUSPICIOUS RIVER", "release_year", "2000" ], [ "THE BEACH", "has_genre", "DRAMA" ], [ "THE BEACH", "release_year", "2000" ], [ "THE BENCH", "has_genre", "DRAMA" ], [ "THE BENCH", "release_year", "2000" ], [ "THE CIRCLE", "has_genre", "DRAMA" ], [ "THE CIRCLE", "release_year", "2000" ], [ "THE CONTENDER", "has_genre", "DRAMA" ], [ "THE CONTENDER", "release_year", "2000" ], [ "THE GIRL", "has_genre", "DRAMA" ], [ "THE GIRL", "release_year", "2000" ], [ "THE GOLDEN BOWL", "has_genre", "DRAMA" ], [ "THE GOLDEN BOWL", "release_year", "2000" ], [ "THE MILLION DOLLAR HOTEL", "has_genre", "DRAMA" ], [ "THE MILLION DOLLAR HOTEL", "has_tags", "DRAMA" ], [ "THE MILLION DOLLAR HOTEL", "release_year", "2000" ], [ "THE NEXT BEST THING", "has_genre", "DRAMA" ], [ "THE NEXT BEST THING", "release_year", "2000" ], [ "THE OPPORTUNISTS", "has_genre", "DRAMA" ], [ "THE OPPORTUNISTS", "release_year", "2000" ], [ "THE PERFECT STORM", "has_genre", "DRAMA" ], [ "THE PERFECT STORM", "has_tags", "DRAMA" ], [ "THE PERFECT STORM", "release_year", "2000" ], [ "THE PRINCESS AND THE WARRIOR", "has_genre", "DRAMA" ], [ "THE PRINCESS AND THE WARRIOR", "release_year", "2000" ], [ "THE TAO OF STEVE", "has_genre", "DRAMA" ], [ "THE TAO OF STEVE", "release_year", "2000" ], [ "THE TOWN IS QUIET", "has_genre", "DRAMA" ], [ "THE TOWN IS QUIET", "release_year", "2000" ], [ "THIRTEEN DAYS", "has_genre", "DRAMA" ], [ "THIRTEEN DAYS", "release_year", "2000" ], [ "TIGERLAND", "has_genre", "DRAMA" ], [ "TIGERLAND", "release_year", "2000" ], [ "TOGETHER", "has_genre", "DRAMA" ], [ "TOGETHER", "release_year", "2000" ], [ "TRAFFIC", "has_genre", "DRAMA" ], [ "TRAFFIC", "release_year", "2000" ], [ "TULLY", "has_genre", "DRAMA" ], [ "TULLY", "release_year", "2000" ], [ "UNBREAKABLE", "has_genre", "DRAMA" ], [ "UNBREAKABLE", "release_year", "2000" ], [ "UNDER SUSPICION", "has_genre", "DRAMA" ], [ "UNDER SUSPICION", "release_year", "2000" ], [ "WAKING THE DEAD", "has_genre", "DRAMA" ], [ "WAKING THE DEAD", "has_tags", "DRAMA" ], [ "WAKING THE DEAD", "release_year", "2000" ], [ "WATER DROPS ON BURNING ROCKS", "has_genre", "DRAMA" ], [ "WATER DROPS ON BURNING ROCKS", "release_year", "2000" ], [ "WHAT LIES BENEATH", "has_genre", "DRAMA" ], [ "WHAT LIES BENEATH", "release_year", "2000" ], [ "WHAT'S COOKING?", "has_genre", "DRAMA" ], [ "WHAT'S COOKING?", "release_year", "2000" ], [ "WHERE THE HEART IS", "has_genre", "DRAMA" ], [ "WHERE THE HEART IS", "release_year", "2000" ], [ "YOU CAN COUNT ON ME", "has_genre", "DRAMA" ], [ "YOU CAN COUNT ON ME", "release_year", "2000" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 28173, CLIMBING 36212, DRAMA 10487, GUTS 19722, INTERVIEW 1403, TARA ELDERS 7702, TO THE LIMIT src, edge_attr, dst 10487, has_genre, 36212 19722, has_genre, 36212 19722, has_tags, 36212 19722, release_year, 17315 19722, starred_actors, 1403 7702, has_tags, 28173 7702, release_year, 17315 Question: How are CLIMBING, GUTS, and TARA ELDERS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CLIMBING", "GUTS", "TARA ELDERS" ], "valid_edges": [ [ "GUTS", "has_genre", "DRAMA" ], [ "INTERVIEW", "has_genre", "DRAMA" ], [ "INTERVIEW", "has_tags", "DRAMA" ], [ "INTERVIEW", "release_year", "2007" ], [ "INTERVIEW", "starred_actors", "TARA ELDERS" ], [ "TO THE LIMIT", "has_tags", "CLIMBING" ], [ "TO THE LIMIT", "release_year", "2007" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3473, AMAZON WOMEN ON THE MOON 22939, ARSENIO HALL 2627, CLARENCE NASH 30463, COMEDY 9144, COMING TO AMERICA 36212, DRAMA 24494, ELLIE PARKER 5870, HORROR 141, I HEART HUCKABEES 18555, JOHN LANDIS 22764, NAOMI WATTS 19715, ST. VINCENT 2492, THE RING 17409, TRICK OR TREAT 6279, YOU WILL MEET A TALL DARK STRANGER src, edge_attr, dst 3473, directed_by, 18555 3473, has_genre, 30463 3473, starred_actors, 22939 9144, directed_by, 18555 9144, has_genre, 30463 9144, has_tags, 30463 9144, has_tags, 18555 9144, starred_actors, 22939 24494, has_genre, 30463 24494, has_genre, 36212 24494, starred_actors, 22764 141, has_genre, 30463 141, has_tags, 30463 141, has_tags, 22764 19715, has_genre, 30463 19715, has_genre, 36212 19715, has_tags, 22764 19715, starred_actors, 22764 2492, has_genre, 5870 2492, has_tags, 5870 2492, has_tags, 22764 2492, starred_actors, 22764 17409, has_genre, 5870 17409, starred_actors, 2627 6279, has_genre, 30463 6279, has_genre, 36212 6279, has_tags, 30463 6279, has_tags, 36212 6279, has_tags, 22764 Question: In what context are ARSENIO HALL, CLARENCE NASH, and NAOMI WATTS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ARSENIO HALL", "CLARENCE NASH", "NAOMI WATTS" ], "valid_edges": [ [ "AMAZON WOMEN ON THE MOON", "directed_by", "JOHN LANDIS" ], [ "AMAZON WOMEN ON THE MOON", "has_genre", "COMEDY" ], [ "AMAZON WOMEN ON THE MOON", "starred_actors", "ARSENIO HALL" ], [ "COMING TO AMERICA", "directed_by", "JOHN LANDIS" ], [ "COMING TO AMERICA", "has_genre", "COMEDY" ], [ "COMING TO AMERICA", "has_tags", "COMEDY" ], [ "COMING TO AMERICA", "has_tags", "JOHN LANDIS" ], [ "COMING TO AMERICA", "starred_actors", "ARSENIO HALL" ], [ "ELLIE PARKER", "has_genre", "COMEDY" ], [ "ELLIE PARKER", "has_genre", "DRAMA" ], [ "ELLIE PARKER", "starred_actors", "NAOMI WATTS" ], [ "I HEART HUCKABEES", "has_genre", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "NAOMI WATTS" ], [ "ST. VINCENT", "has_genre", "COMEDY" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "has_tags", "NAOMI WATTS" ], [ "ST. VINCENT", "starred_actors", "NAOMI WATTS" ], [ "THE RING", "has_genre", "HORROR" ], [ "THE RING", "has_tags", "HORROR" ], [ "THE RING", "has_tags", "NAOMI WATTS" ], [ "THE RING", "starred_actors", "NAOMI WATTS" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "starred_actors", "CLARENCE NASH" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_genre", "COMEDY" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_genre", "DRAMA" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "COMEDY" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "DRAMA" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "NAOMI WATTS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 22845, MUSIC 11061, PAUL ROBESON 238, RIDERS OF DESTINY 39373, SONG OF FREEDOM 15207, THE EMPEROR JONES 19226, THE MARC PEASE EXPERIENCE 23317, WILD BOYS OF THE ROAD src, edge_attr, dst 238, has_genre, 22845 238, release_year, 15506 39373, starred_actors, 11061 15207, release_year, 15506 15207, starred_actors, 11061 19226, has_genre, 22845 23317, release_year, 15506 Question: How are SONG OF FREEDOM, THE MARC PEASE EXPERIENCE, and WILD BOYS OF THE ROAD related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "SONG OF FREEDOM", "THE MARC PEASE EXPERIENCE", "WILD BOYS OF THE ROAD" ], "valid_edges": [ [ "RIDERS OF DESTINY", "has_genre", "MUSIC" ], [ "RIDERS OF DESTINY", "release_year", "1933" ], [ "SONG OF FREEDOM", "starred_actors", "PAUL ROBESON" ], [ "THE EMPEROR JONES", "release_year", "1933" ], [ "THE EMPEROR JONES", "starred_actors", "PAUL ROBESON" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "MUSIC" ], [ "WILD BOYS OF THE ROAD", "release_year", "1933" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 25221, 1981 28171, 1986 39289, ACTION 4763, ADVENTURE 18169, APRIL FOOL'S DAY 12952, ARMED AND DANGEROUS 35779, ARMOUR OF GOD 32646, AT LONG LAST LOVE 11687, CHARLIE SHEEN 14884, CLASS OF NUKE 'EM HIGH 30463, COMEDY 12489, CRAZY MAMA 6743, CRITTERS 29991, DAVID SELTZER 25400, DENHOLM ELLIOTT 2221, DOLEMITE 24481, FRANCHISE 310, GEORGE LUCAS 15135, GINGER AND FRED 13794, GOON 16240, HARRISON FORD 35856, HEARTS OF THE WEST 5870, HORROR 5068, HOT SHOTS! PART DEUX 10147, HOUSE 358, HOWARD THE DUCK 18585, INDIANA JONES 22790, INDIANA JONES AND THE LAST CRUSADE 8257, LIES MY FATHER TOLD ME 940, LIEV SCHREIBER 8851, LITTLE SHOP OF HORRORS 13183, LOVE AND DEATH 32181, LUCAS 38259, MONEY TALKS 20500, MONSTER IN THE CLOSET 32834, MONTY PYTHON AND THE HOLY GRAIL 32916, MY FRIENDS 26892, NAZIS 26151, NOBODY'S BABY 18416, ONE OF OUR DINOSAURS IS MISSING 8, PHANTOMS 8526, PUNCHLINE 29299, RAIDERS OF THE LOST ARK 34930, RANCHO DELUXE 33108, RUNNING SCARED 30173, SALT 1045, SMILE 34888, SOMETHING WILD 2152, SPIELBERG 23639, SPINNING BORIS 26730, STEVEN SPIELBERG 5932, TERRORVISION 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 5469, THE BEST OF TIMES 13685, THE CHASE 32237, THE FORTUNE 17331, THE LAST DAYS ON MARS 21920, THE OLSEN GANG ON THE TRACK 17910, THE OMEN 10721, THE ROCKY HORROR PICTURE SHOW 23847, THE STEPFORD WIVES 26081, THE SUNSHINE BOYS 9715, THE TEXAS CHAINSAW MASSACRE 2 7816, THE THREE MUSKETEERS src, edge_attr, dst 25221, has_genre, 30463 18169, has_genre, 30463 18169, release_year, 28171 12952, has_genre, 30463 12952, release_year, 28171 35779, has_genre, 30463 35779, release_year, 28171 32646, has_genre, 30463 32646, release_year, 39435 14884, has_genre, 30463 14884, release_year, 28171 12489, has_genre, 30463 12489, release_year, 39435 6743, has_genre, 30463 6743, release_year, 28171 2221, has_genre, 30463 2221, release_year, 39435 15135, has_genre, 30463 15135, release_year, 28171 13794, has_genre, 30463 13794, starred_actors, 940 35856, has_genre, 30463 35856, release_year, 39435 5068, has_genre, 30463 5068, has_tags, 11687 5068, has_tags, 30463 5068, starred_actors, 11687 10147, has_genre, 30463 10147, release_year, 28171 358, has_genre, 30463 358, release_year, 28171 22790, directed_by, 26730 22790, has_genre, 39289 22790, has_genre, 4763 22790, has_tags, 39289 22790, has_tags, 4763 22790, has_tags, 25400 22790, has_tags, 24481 22790, has_tags, 16240 22790, has_tags, 18585 22790, has_tags, 32181 22790, has_tags, 26892 22790, has_tags, 2152 22790, has_tags, 26730 22790, starred_actors, 25400 22790, starred_actors, 16240 22790, written_by, 310 8257, release_year, 39435 8851, has_genre, 30463 8851, release_year, 28171 13183, has_genre, 30463 13183, has_tags, 30463 13183, release_year, 39435 32181, directed_by, 29991 32181, has_genre, 30463 32181, has_tags, 11687 32181, release_year, 28171 32181, starred_actors, 11687 32181, written_by, 29991 38259, has_genre, 30463 38259, starred_actors, 11687 20500, has_genre, 30463 20500, release_year, 28171 32834, has_genre, 30463 32834, has_tags, 30463 32834, release_year, 39435 32916, has_genre, 30463 32916, release_year, 39435 26151, directed_by, 29991 26151, has_genre, 30463 26151, written_by, 29991 18416, has_genre, 30463 18416, release_year, 39435 8, has_genre, 5870 8, starred_actors, 940 8526, directed_by, 29991 8526, has_genre, 30463 8526, written_by, 29991 29299, directed_by, 26730 29299, has_genre, 39289 29299, has_genre, 4763 29299, has_tags, 39289 29299, has_tags, 4763 29299, has_tags, 25400 29299, has_tags, 24481 29299, has_tags, 16240 29299, has_tags, 18585 29299, has_tags, 32181 29299, has_tags, 26892 29299, has_tags, 2152 29299, has_tags, 26730 29299, release_year, 25221 29299, starred_actors, 16240 29299, written_by, 310 34930, has_genre, 30463 34930, release_year, 39435 33108, has_genre, 30463 33108, release_year, 28171 30173, has_genre, 39289 30173, has_tags, 39289 30173, has_tags, 940 30173, starred_actors, 940 1045, has_genre, 30463 1045, release_year, 39435 34888, has_genre, 30463 34888, release_year, 28171 23639, has_genre, 30463 23639, starred_actors, 940 5932, has_genre, 30463 5932, release_year, 28171 10409, has_genre, 30463 10409, release_year, 39435 5469, has_genre, 30463 5469, release_year, 28171 13685, has_genre, 30463 13685, has_tags, 11687 13685, starred_actors, 11687 32237, has_genre, 30463 32237, release_year, 39435 17331, has_genre, 5870 17331, starred_actors, 940 21920, has_genre, 30463 21920, release_year, 39435 17910, has_genre, 5870 17910, has_tags, 5870 17910, starred_actors, 940 17910, written_by, 29991 10721, has_genre, 30463 10721, release_year, 39435 23847, has_genre, 30463 23847, release_year, 39435 26081, has_genre, 30463 26081, release_year, 39435 9715, has_genre, 30463 9715, release_year, 28171 7816, has_genre, 30463 7816, starred_actors, 11687 Question: In what context are LIES MY FATHER TOLD ME, LIEV SCHREIBER, and LUCAS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LIES MY FATHER TOLD ME", "LIEV SCHREIBER", "LUCAS" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "APRIL FOOL'S DAY", "has_genre", "COMEDY" ], [ "APRIL FOOL'S DAY", "release_year", "1986" ], [ "ARMED AND DANGEROUS", "has_genre", "COMEDY" ], [ "ARMED AND DANGEROUS", "release_year", "1986" ], [ "ARMOUR OF GOD", "has_genre", "COMEDY" ], [ "ARMOUR OF GOD", "release_year", "1986" ], [ "AT LONG LAST LOVE", "has_genre", "COMEDY" ], [ "AT LONG LAST LOVE", "release_year", "1975" ], [ "CLASS OF NUKE 'EM HIGH", "has_genre", "COMEDY" ], [ "CLASS OF NUKE 'EM HIGH", "release_year", "1986" ], [ "CRAZY MAMA", "has_genre", "COMEDY" ], [ "CRAZY MAMA", "release_year", "1975" ], [ "CRITTERS", "has_genre", "COMEDY" ], [ "CRITTERS", "release_year", "1986" ], [ "DOLEMITE", "has_genre", "COMEDY" ], [ "DOLEMITE", "release_year", "1975" ], [ "GINGER AND FRED", "has_genre", "COMEDY" ], [ "GINGER AND FRED", "release_year", "1986" ], [ "GOON", "has_genre", "COMEDY" ], [ "GOON", "starred_actors", "LIEV SCHREIBER" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "release_year", "1975" ], [ "HOT SHOTS! PART DEUX", "has_genre", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "has_tags", "CHARLIE SHEEN" ], [ "HOT SHOTS! PART DEUX", "has_tags", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "starred_actors", "CHARLIE SHEEN" ], [ "HOUSE", "has_genre", "COMEDY" ], [ "HOUSE", "release_year", "1986" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "HOWARD THE DUCK", "release_year", "1986" ], [ "INDIANA JONES AND THE LAST CRUSADE", "directed_by", "STEVEN SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "DENHOLM ELLIOTT" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "FRANCHISE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "HARRISON FORD" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "INDIANA JONES" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "LUCAS" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "NAZIS" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "STEVEN SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "DENHOLM ELLIOTT" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "HARRISON FORD" ], [ "INDIANA JONES AND THE LAST CRUSADE", "written_by", "GEORGE LUCAS" ], [ "LIES MY FATHER TOLD ME", "release_year", "1975" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "COMEDY" ], [ "LITTLE SHOP OF HORRORS", "release_year", "1986" ], [ "LOVE AND DEATH", "has_genre", "COMEDY" ], [ "LOVE AND DEATH", "has_tags", "COMEDY" ], [ "LOVE AND DEATH", "release_year", "1975" ], [ "LUCAS", "directed_by", "DAVID SELTZER" ], [ "LUCAS", "has_genre", "COMEDY" ], [ "LUCAS", "has_tags", "CHARLIE SHEEN" ], [ "LUCAS", "release_year", "1986" ], [ "LUCAS", "starred_actors", "CHARLIE SHEEN" ], [ "LUCAS", "written_by", "DAVID SELTZER" ], [ "MONEY TALKS", "has_genre", "COMEDY" ], [ "MONEY TALKS", "starred_actors", "CHARLIE SHEEN" ], [ "MONSTER IN THE CLOSET", "has_genre", "COMEDY" ], [ "MONSTER IN THE CLOSET", "release_year", "1986" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_genre", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_tags", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "release_year", "1975" ], [ "MY FRIENDS", "has_genre", "COMEDY" ], [ "MY FRIENDS", "release_year", "1975" ], [ "NOBODY'S BABY", "directed_by", "DAVID SELTZER" ], [ "NOBODY'S BABY", "has_genre", "COMEDY" ], [ "NOBODY'S BABY", "written_by", "DAVID SELTZER" ], [ "ONE OF OUR DINOSAURS IS MISSING", "has_genre", "COMEDY" ], [ "ONE OF OUR DINOSAURS IS MISSING", "release_year", "1975" ], [ "PHANTOMS", "has_genre", "HORROR" ], [ "PHANTOMS", "starred_actors", "LIEV SCHREIBER" ], [ "PUNCHLINE", "directed_by", "DAVID SELTZER" ], [ "PUNCHLINE", "has_genre", "COMEDY" ], [ "PUNCHLINE", "written_by", "DAVID SELTZER" ], [ "RAIDERS OF THE LOST ARK", "directed_by", "STEVEN SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "DENHOLM ELLIOTT" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "FRANCHISE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "INDIANA JONES" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "LUCAS" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "NAZIS" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "STEVEN SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "release_year", "1981" ], [ "RAIDERS OF THE LOST ARK", "starred_actors", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "written_by", "GEORGE LUCAS" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "release_year", "1975" ], [ "RUNNING SCARED", "has_genre", "COMEDY" ], [ "RUNNING SCARED", "release_year", "1986" ], [ "SALT", "has_genre", "ACTION" ], [ "SALT", "has_tags", "ACTION" ], [ "SALT", "has_tags", "LIEV SCHREIBER" ], [ "SALT", "starred_actors", "LIEV SCHREIBER" ], [ "SMILE", "has_genre", "COMEDY" ], [ "SMILE", "release_year", "1975" ], [ "SOMETHING WILD", "has_genre", "COMEDY" ], [ "SOMETHING WILD", "release_year", "1986" ], [ "SPINNING BORIS", "has_genre", "COMEDY" ], [ "SPINNING BORIS", "starred_actors", "LIEV SCHREIBER" ], [ "TERRORVISION", "has_genre", "COMEDY" ], [ "TERRORVISION", "release_year", "1986" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "COMEDY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "release_year", "1975" ], [ "THE BEST OF TIMES", "has_genre", "COMEDY" ], [ "THE BEST OF TIMES", "release_year", "1986" ], [ "THE CHASE", "has_genre", "COMEDY" ], [ "THE CHASE", "has_tags", "CHARLIE SHEEN" ], [ "THE CHASE", "starred_actors", "CHARLIE SHEEN" ], [ "THE FORTUNE", "has_genre", "COMEDY" ], [ "THE FORTUNE", "release_year", "1975" ], [ "THE LAST DAYS ON MARS", "has_genre", "HORROR" ], [ "THE LAST DAYS ON MARS", "starred_actors", "LIEV SCHREIBER" ], [ "THE OLSEN GANG ON THE TRACK", "has_genre", "COMEDY" ], [ "THE OLSEN GANG ON THE TRACK", "release_year", "1975" ], [ "THE OMEN", "has_genre", "HORROR" ], [ "THE OMEN", "has_tags", "HORROR" ], [ "THE OMEN", "starred_actors", "LIEV SCHREIBER" ], [ "THE OMEN", "written_by", "DAVID SELTZER" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "release_year", "1975" ], [ "THE STEPFORD WIVES", "has_genre", "COMEDY" ], [ "THE STEPFORD WIVES", "release_year", "1975" ], [ "THE SUNSHINE BOYS", "has_genre", "COMEDY" ], [ "THE SUNSHINE BOYS", "release_year", "1975" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_genre", "COMEDY" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "release_year", "1986" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "starred_actors", "CHARLIE SHEEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 1006, 1996 8486, 1999 30146, A CHRISTMAS CAROL 29638, ALICE IN WONDERLAND 10045, BD-R 350, BOYS ON THE SIDE 30182, BURGLAR 33914, CHÉRI 14728, CLASSIC 30463, COMEDY 36212, DRAMA 10757, EDDIE 2939, EMMANUEL MOURET 22958, FAMOUS 36066, FANTASY 6012, FRENCH 12126, GHOSTS OF MISSISSIPPI 22532, GIRL, INTERRUPTED 10964, HOW STELLA GOT HER GROOVE BACK 35335, IT ALL STARTS TODAY 2938, JUMPIN' JACK FLASH 17663, MADE IN AMERICA 21386, POLA X 32180, RAT RACE 8379, ROMANCE 39915, SHALL WE KISS? 8652, SISTER ACT 6882, THE COLOR PURPLE 6150, THE CONFESSION 791, THE DEEP END OF THE OCEAN 9799, THE LOST SON 35362, THE MAGICAL LEGEND OF THE LEPRECHAUNS 29027, THE TELEPHONE 16292, TRUE STORY 37332, WHOOPI GOLDBERG 21449, YOU WILL BE MY SON src, edge_attr, dst 30146, has_genre, 30463 30146, has_genre, 36212 30146, has_genre, 36066 30146, has_imdb_votes, 22958 30146, has_tags, 10045 30146, has_tags, 14728 30146, release_year, 8486 30146, starred_actors, 37332 29638, has_genre, 36066 29638, has_tags, 10045 29638, has_tags, 14728 29638, has_tags, 36066 29638, release_year, 38097 29638, release_year, 8486 29638, starred_actors, 37332 350, has_genre, 30463 350, has_genre, 36212 350, has_tags, 37332 350, starred_actors, 37332 30182, has_genre, 30463 30182, starred_actors, 37332 33914, has_genre, 36212 33914, in_language, 6012 10757, has_genre, 30463 10757, release_year, 1006 10757, starred_actors, 37332 12126, has_genre, 36212 12126, has_tags, 16292 12126, has_tags, 37332 12126, release_year, 1006 12126, starred_actors, 37332 22532, has_genre, 36212 22532, has_tags, 36212 22532, has_tags, 37332 22532, release_year, 8486 10964, has_genre, 36212 10964, has_tags, 37332 10964, starred_actors, 37332 35335, has_genre, 36212 35335, in_language, 6012 2938, has_genre, 30463 2938, has_tags, 37332 2938, starred_actors, 37332 17663, has_genre, 30463 17663, has_tags, 37332 17663, starred_actors, 37332 21386, has_genre, 36212 21386, in_language, 6012 32180, has_genre, 30463 32180, has_tags, 30463 32180, has_tags, 37332 8379, has_genre, 36212 8379, in_language, 6012 39915, directed_by, 2939 39915, has_genre, 30463 39915, in_language, 6012 39915, starred_actors, 2939 39915, written_by, 2939 8652, has_genre, 30463 8652, has_tags, 37332 8652, starred_actors, 37332 6882, has_genre, 36212 6882, has_imdb_votes, 22958 6882, has_tags, 37332 6882, release_year, 38097 6882, starred_actors, 37332 6150, has_genre, 36212 6150, in_language, 6012 791, has_genre, 36212 791, release_year, 8486 791, starred_actors, 37332 9799, has_genre, 36212 9799, in_language, 6012 35362, release_year, 8486 35362, starred_actors, 37332 29027, has_genre, 30463 29027, starred_actors, 37332 16292, has_genre, 36212 16292, has_tags, 36212 21449, has_genre, 36212 21449, in_language, 6012 Question: How are EMMANUEL MOURET, WHOOPI GOLDBERG, and YOU WILL BE MY SON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EMMANUEL MOURET", "WHOOPI GOLDBERG", "YOU WILL BE MY SON" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A CHRISTMAS CAROL", "has_genre", "FANTASY" ], [ "A CHRISTMAS CAROL", "has_imdb_votes", "FAMOUS" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "has_tags", "CLASSIC" ], [ "A CHRISTMAS CAROL", "release_year", "1999" ], [ "A CHRISTMAS CAROL", "starred_actors", "WHOOPI GOLDBERG" ], [ "ALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "ALICE IN WONDERLAND", "has_tags", "BD-R" ], [ "ALICE IN WONDERLAND", "has_tags", "CLASSIC" ], [ "ALICE IN WONDERLAND", "has_tags", "FANTASY" ], [ "ALICE IN WONDERLAND", "release_year", "1985" ], [ "ALICE IN WONDERLAND", "release_year", "1999" ], [ "ALICE IN WONDERLAND", "starred_actors", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_genre", "DRAMA" ], [ "BOYS ON THE SIDE", "has_tags", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "starred_actors", "WHOOPI GOLDBERG" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "starred_actors", "WHOOPI GOLDBERG" ], [ "CHÉRI", "has_genre", "DRAMA" ], [ "CHÉRI", "in_language", "FRENCH" ], [ "EDDIE", "has_genre", "COMEDY" ], [ "EDDIE", "release_year", "1996" ], [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "GHOSTS OF MISSISSIPPI", "has_genre", "DRAMA" ], [ "GHOSTS OF MISSISSIPPI", "has_tags", "TRUE STORY" ], [ "GHOSTS OF MISSISSIPPI", "has_tags", "WHOOPI GOLDBERG" ], [ "GHOSTS OF MISSISSIPPI", "release_year", "1996" ], [ "GHOSTS OF MISSISSIPPI", "starred_actors", "WHOOPI GOLDBERG" ], [ "GIRL, INTERRUPTED", "has_genre", "DRAMA" ], [ "GIRL, INTERRUPTED", "has_tags", "DRAMA" ], [ "GIRL, INTERRUPTED", "has_tags", "WHOOPI GOLDBERG" ], [ "GIRL, INTERRUPTED", "release_year", "1999" ], [ "HOW STELLA GOT HER GROOVE BACK", "has_genre", "DRAMA" ], [ "HOW STELLA GOT HER GROOVE BACK", "has_tags", "WHOOPI GOLDBERG" ], [ "HOW STELLA GOT HER GROOVE BACK", "starred_actors", "WHOOPI GOLDBERG" ], [ "IT ALL STARTS TODAY", "has_genre", "DRAMA" ], [ "IT ALL STARTS TODAY", "in_language", "FRENCH" ], [ "JUMPIN' JACK FLASH", "has_genre", "COMEDY" ], [ "JUMPIN' JACK FLASH", "has_tags", "WHOOPI GOLDBERG" ], [ "JUMPIN' JACK FLASH", "starred_actors", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "has_tags", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "starred_actors", "WHOOPI GOLDBERG" ], [ "POLA X", "has_genre", "DRAMA" ], [ "POLA X", "in_language", "FRENCH" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "has_tags", "WHOOPI GOLDBERG" ], [ "ROMANCE", "has_genre", "DRAMA" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "directed_by", "EMMANUEL MOURET" ], [ "SHALL WE KISS?", "has_genre", "COMEDY" ], [ "SHALL WE KISS?", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "starred_actors", "EMMANUEL MOURET" ], [ "SHALL WE KISS?", "written_by", "EMMANUEL MOURET" ], [ "SISTER ACT", "has_genre", "COMEDY" ], [ "SISTER ACT", "has_tags", "WHOOPI GOLDBERG" ], [ "SISTER ACT", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE COLOR PURPLE", "has_genre", "DRAMA" ], [ "THE COLOR PURPLE", "has_imdb_votes", "FAMOUS" ], [ "THE COLOR PURPLE", "has_tags", "WHOOPI GOLDBERG" ], [ "THE COLOR PURPLE", "release_year", "1985" ], [ "THE COLOR PURPLE", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE CONFESSION", "has_genre", "DRAMA" ], [ "THE CONFESSION", "in_language", "FRENCH" ], [ "THE DEEP END OF THE OCEAN", "has_genre", "DRAMA" ], [ "THE DEEP END OF THE OCEAN", "release_year", "1999" ], [ "THE DEEP END OF THE OCEAN", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE LOST SON", "has_genre", "DRAMA" ], [ "THE LOST SON", "in_language", "FRENCH" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "release_year", "1999" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE TELEPHONE", "has_genre", "COMEDY" ], [ "THE TELEPHONE", "starred_actors", "WHOOPI GOLDBERG" ], [ "TRUE STORY", "has_genre", "DRAMA" ], [ "TRUE STORY", "has_tags", "DRAMA" ], [ "YOU WILL BE MY SON", "has_genre", "DRAMA" ], [ "YOU WILL BE MY SON", "in_language", "FRENCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10825, 1973 17315, 2007 39289, ACTION 36348, AKIRA 9677, ANATOMY OF A MURDER 32828, BADLANDS 19131, BONNIE AND CLYDE 27059, CATCH ME IF YOU CAN 9201, CHARLEY VARRICK 14724, CRIME 7316, DANISH 23396, DIAL M FOR MURDER 23283, EDGE OF DARKNESS 21123, FARGO 1033, FRACTURE 23299, GET CARTER 22449, GOODFELLAS 4423, GUN CRAZY 12189, HARRY BROWN 25061, I AM A FUGITIVE FROM A CHAIN GANG 20430, IN THE BEDROOM 39264, JUST ANOTHER LOVE STORY 10706, MAMI KOYAMA 6267, MARTIN SHEEN 33561, MEAN STREETS 3487, MINORITY REPORT 27827, MONSTER 28476, MURDER 11311, MURDER ON THE ORIENT EXPRESS 37497, NATIONAL FILM REGISTRY 20417, NIGHTWATCH 3935, OLE BORNEDAL 22122, PRETTY POISON 31741, PRIMAL FEAR 12428, RAGE 16364, ROPE 22196, SERPICO 27807, SHAFT 29168, SISSY SPACEK 40046, STRANGERS ON A TRAIN 28619, SUMMER OF SAM 12, TAXI DRIVER 30951, THE CANDY SNATCHERS 22630, THE DON IS DEAD 31555, THE FRESHMAN 13245, THE FRIENDS OF EDDIE COYLE 35551, THE GODFATHER 27885, THE KILLERS 4827, THE MALTESE FALCON 34901, THE OUTFIT 37148, THE SECRET IN THEIR EYES 4294, THE SUBSTITUTE src, edge_attr, dst 36348, has_genre, 39289 36348, has_tags, 39289 36348, starred_actors, 10706 9677, has_genre, 14724 9677, has_tags, 14724 9677, has_tags, 28476 32828, has_genre, 14724 32828, has_tags, 14724 32828, has_tags, 6267 32828, has_tags, 28476 32828, has_tags, 37497 32828, has_tags, 29168 32828, release_year, 10825 32828, starred_actors, 6267 32828, starred_actors, 29168 19131, has_genre, 14724 19131, has_tags, 14724 19131, has_tags, 37497 27059, has_genre, 14724 27059, has_tags, 14724 27059, has_tags, 6267 27059, starred_actors, 6267 9201, has_genre, 14724 9201, release_year, 10825 23396, has_genre, 14724 23396, has_tags, 28476 23283, has_genre, 14724 23283, has_tags, 28476 21123, has_genre, 14724 21123, has_tags, 14724 21123, has_tags, 37497 1033, has_genre, 14724 1033, has_tags, 28476 23299, has_genre, 14724 23299, has_tags, 28476 22449, has_genre, 14724 22449, has_tags, 14724 22449, has_tags, 37497 4423, has_genre, 14724 4423, has_tags, 14724 4423, has_tags, 37497 12189, has_genre, 14724 12189, has_tags, 28476 25061, has_genre, 14724 25061, has_tags, 37497 20430, has_genre, 14724 20430, starred_actors, 29168 39264, directed_by, 3935 39264, in_language, 7316 39264, release_year, 17315 39264, written_by, 3935 33561, has_genre, 14724 33561, has_tags, 37497 33561, release_year, 10825 3487, has_tags, 14724 3487, has_tags, 28476 27827, has_genre, 14724 27827, has_tags, 14724 27827, has_tags, 28476 11311, has_genre, 14724 11311, has_tags, 28476 20417, directed_by, 3935 20417, in_language, 7316 20417, written_by, 3935 22122, has_genre, 14724 22122, has_tags, 28476 31741, has_genre, 14724 31741, has_tags, 14724 31741, has_tags, 28476 12428, has_genre, 14724 12428, has_tags, 14724 12428, starred_actors, 6267 16364, has_genre, 14724 16364, has_tags, 28476 22196, has_genre, 14724 22196, release_year, 10825 27807, has_genre, 14724 27807, has_tags, 37497 40046, has_genre, 14724 40046, has_tags, 28476 28619, has_genre, 14724 28619, has_tags, 28476 12, has_genre, 14724 12, has_tags, 37497 30951, has_genre, 14724 30951, release_year, 10825 22630, has_genre, 14724 22630, release_year, 10825 31555, has_genre, 14724 31555, has_tags, 37497 13245, has_genre, 14724 13245, release_year, 10825 35551, has_genre, 14724 35551, has_tags, 14724 35551, has_tags, 37497 27885, has_genre, 14724 27885, has_tags, 37497 4827, has_genre, 14724 4827, has_tags, 37497 34901, has_genre, 14724 34901, release_year, 10825 37148, has_tags, 14724 37148, has_tags, 28476 4294, directed_by, 3935 4294, has_genre, 39289 4294, has_genre, 14724 4294, in_language, 7316 4294, release_year, 17315 4294, written_by, 3935 Question: For what reason are BADLANDS, MAMI KOYAMA, and OLE BORNEDAL associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BADLANDS", "MAMI KOYAMA", "OLE BORNEDAL" ], "valid_edges": [ [ "AKIRA", "has_genre", "ACTION" ], [ "AKIRA", "has_tags", "ACTION" ], [ "AKIRA", "starred_actors", "MAMI KOYAMA" ], [ "ANATOMY OF A MURDER", "has_genre", "CRIME" ], [ "ANATOMY OF A MURDER", "has_tags", "CRIME" ], [ "ANATOMY OF A MURDER", "has_tags", "MURDER" ], [ "BADLANDS", "has_genre", "CRIME" ], [ "BADLANDS", "has_tags", "CRIME" ], [ "BADLANDS", "has_tags", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "MURDER" ], [ "BADLANDS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BADLANDS", "has_tags", "SISSY SPACEK" ], [ "BADLANDS", "release_year", "1973" ], [ "BADLANDS", "starred_actors", "MARTIN SHEEN" ], [ "BADLANDS", "starred_actors", "SISSY SPACEK" ], [ "BONNIE AND CLYDE", "has_genre", "CRIME" ], [ "BONNIE AND CLYDE", "has_tags", "CRIME" ], [ "BONNIE AND CLYDE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "MARTIN SHEEN" ], [ "CATCH ME IF YOU CAN", "starred_actors", "MARTIN SHEEN" ], [ "CHARLEY VARRICK", "has_genre", "CRIME" ], [ "CHARLEY VARRICK", "release_year", "1973" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "has_tags", "MURDER" ], [ "EDGE OF DARKNESS", "has_genre", "CRIME" ], [ "EDGE OF DARKNESS", "has_tags", "MURDER" ], [ "FARGO", "has_genre", "CRIME" ], [ "FARGO", "has_tags", "CRIME" ], [ "FARGO", "has_tags", "NATIONAL FILM REGISTRY" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_tags", "MURDER" ], [ "GET CARTER", "has_genre", "CRIME" ], [ "GET CARTER", "has_tags", "MURDER" ], [ "GOODFELLAS", "has_genre", "CRIME" ], [ "GOODFELLAS", "has_tags", "CRIME" ], [ "GOODFELLAS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "GUN CRAZY", "has_genre", "CRIME" ], [ "GUN CRAZY", "has_tags", "CRIME" ], [ "GUN CRAZY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "HARRY BROWN", "has_genre", "CRIME" ], [ "HARRY BROWN", "has_tags", "MURDER" ], [ "I AM A FUGITIVE FROM A CHAIN GANG", "has_genre", "CRIME" ], [ "I AM A FUGITIVE FROM A CHAIN GANG", "has_tags", "NATIONAL FILM REGISTRY" ], [ "IN THE BEDROOM", "has_genre", "CRIME" ], [ "IN THE BEDROOM", "starred_actors", "SISSY SPACEK" ], [ "JUST ANOTHER LOVE STORY", "directed_by", "OLE BORNEDAL" ], [ "JUST ANOTHER LOVE STORY", "in_language", "DANISH" ], [ "JUST ANOTHER LOVE STORY", "release_year", "2007" ], [ "JUST ANOTHER LOVE STORY", "written_by", "OLE BORNEDAL" ], [ "MEAN STREETS", "has_genre", "CRIME" ], [ "MEAN STREETS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "MEAN STREETS", "release_year", "1973" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "MURDER" ], [ "MONSTER", "has_genre", "CRIME" ], [ "MONSTER", "has_tags", "CRIME" ], [ "MONSTER", "has_tags", "MURDER" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "CRIME" ], [ "MURDER ON THE ORIENT EXPRESS", "has_tags", "MURDER" ], [ "NIGHTWATCH", "directed_by", "OLE BORNEDAL" ], [ "NIGHTWATCH", "in_language", "DANISH" ], [ "NIGHTWATCH", "written_by", "OLE BORNEDAL" ], [ "PRETTY POISON", "has_genre", "CRIME" ], [ "PRETTY POISON", "has_tags", "MURDER" ], [ "PRIMAL FEAR", "has_genre", "CRIME" ], [ "PRIMAL FEAR", "has_tags", "CRIME" ], [ "PRIMAL FEAR", "has_tags", "MURDER" ], [ "RAGE", "has_genre", "CRIME" ], [ "RAGE", "has_tags", "CRIME" ], [ "RAGE", "starred_actors", "MARTIN SHEEN" ], [ "ROPE", "has_genre", "CRIME" ], [ "ROPE", "has_tags", "MURDER" ], [ "SERPICO", "has_genre", "CRIME" ], [ "SERPICO", "release_year", "1973" ], [ "SHAFT", "has_genre", "CRIME" ], [ "SHAFT", "has_tags", "NATIONAL FILM REGISTRY" ], [ "STRANGERS ON A TRAIN", "has_genre", "CRIME" ], [ "STRANGERS ON A TRAIN", "has_tags", "MURDER" ], [ "SUMMER OF SAM", "has_genre", "CRIME" ], [ "SUMMER OF SAM", "has_tags", "MURDER" ], [ "TAXI DRIVER", "has_genre", "CRIME" ], [ "TAXI DRIVER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE CANDY SNATCHERS", "has_genre", "CRIME" ], [ "THE CANDY SNATCHERS", "release_year", "1973" ], [ "THE DON IS DEAD", "has_genre", "CRIME" ], [ "THE DON IS DEAD", "release_year", "1973" ], [ "THE FRESHMAN", "has_genre", "CRIME" ], [ "THE FRESHMAN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE FRIENDS OF EDDIE COYLE", "has_genre", "CRIME" ], [ "THE FRIENDS OF EDDIE COYLE", "release_year", "1973" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "CRIME" ], [ "THE GODFATHER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE KILLERS", "has_genre", "CRIME" ], [ "THE KILLERS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MALTESE FALCON", "has_genre", "CRIME" ], [ "THE MALTESE FALCON", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE OUTFIT", "has_genre", "CRIME" ], [ "THE OUTFIT", "release_year", "1973" ], [ "THE SECRET IN THEIR EYES", "has_tags", "CRIME" ], [ "THE SECRET IN THEIR EYES", "has_tags", "MURDER" ], [ "THE SUBSTITUTE", "directed_by", "OLE BORNEDAL" ], [ "THE SUBSTITUTE", "has_genre", "ACTION" ], [ "THE SUBSTITUTE", "has_genre", "CRIME" ], [ "THE SUBSTITUTE", "in_language", "DANISH" ], [ "THE SUBSTITUTE", "release_year", "2007" ], [ "THE SUBSTITUTE", "written_by", "OLE BORNEDAL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 14896, 3 IDIOTS 319, A BUG'S LIFE 30146, A CHRISTMAS CAROL 24039, A GOOD YEAR 8198, A PRAIRIE HOME COMPANION 6476, A WALK IN THE WOODS 4763, ADVENTURE 30985, ADVENTURELAND 16054, ADVENTURES IN BABYSITTING 28412, AFRICA SCREAMS 16486, AGENT CODY BANKS 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 35485, ALMOST HEROES 38447, ALWAYS LEAVE THEM LAUGHING 39876, ANNIE 35941, ANTZ 18310, AROUND THE WORLD IN 80 DAYS 2385, AROUND THE WORLD IN EIGHTY DAYS 1822, AWAY WE GO 35639, BABY'S DAY OUT 38657, BEAT THE DEVIL 32479, BEWITCHED 18646, BIG SHOTS 11779, BIG TOP PEE-WEE 7314, BOLT 11066, BOMBER 31957, BOY 12910, BRIEF INTERVIEWS WITH HIDEOUS MEN 5823, BROTHER BEAR 2 14480, BUDDIES 10356, BUNTY AUR BABLI 1587, BUSHWHACKED 30039, CAPTAIN JANUARY 33196, CARS 16795, CASANOVA'S BIG NIGHT 524, CHARLIE'S ANGELS 10349, CHICAGO 21479, CITY ISLAND 28503, CLOUDBURST 38556, COLD SOULS 30463, COMEDY 29904, CONDORMAN 30802, CUTTHROAT ISLAND 22663, DAN IN REAL LIFE 32301, DEFENDOR 25657, DELHI-6 36212, DRAMA 5881, ELEPHANT BOY 1329, ENVY 19367, ESCAPE TO ATHENA 2449, EUROTRIP 18031, FAR AND AWAY 15349, FINDING NEMO 2287, FLUSHED AWAY 5287, FROZEN 5514, FUNNY PEOPLE 2320, GRIND 17440, GULLIVER'S TRAVELS 20263, HAIR 4649, HAPPY TEARS 11014, HE'S JUST NOT THAT INTO YOU 1292, HEDWIG AND THE ANGRY INCH 20008, HELP! 39494, HOLES 7811, HORTON HEARS A WHO! 5617, HOT TUB TIME MACHINE 358, HOWARD THE DUCK 38457, I CAN DO BAD ALL BY MYSELF 16371, ICE AGE 38176, IDIOT'S DELIGHT 5747, IMAGINE THAT 32383, JOE DIRT 2368, KANGAROO JACK 32995, LAND HO! 25097, LAND OF THE LOST 17903, LEAVES OF GRASS 19667, LIFE DURING WARTIME 16814, LITTLE WHITE LIES 35457, MADEA GOES TO JAIL 7813, MARY AND MAX 10378, MAURY YESTON 25283, MAVERICK 13873, MIDDLE MEN 17135, MOM AND DAD SAVE THE WORLD 34451, MOTHERHOOD 11444, MR. ROBINSON CRUSOE 32058, MUPPET TREASURE ISLAND 3027, NIGHT AT THE MUSEUM 17860, NINE 32358, NORTH 14797, O BROTHER, WHERE ART THOU? 8108, PAPER MAN 25824, PARADISE 30055, PEE-WEE'S BIG ADVENTURE 23964, PENNIES FROM HEAVEN 2391, PIRATES 31703, PUSS IN BOOTS 30475, RIO 10686, RIO 2 28221, ROMANCING THE STONE 35586, SAHARA 10371, SAINT JOHN OF LAS VEGAS 5629, SCOOBY-DOO! THE MYSTERY BEGINS 4945, SEPARATION CITY 38231, SHANGHAI NOON 29832, SHOW BOAT 23608, SIX DAYS SEVEN NIGHTS 24506, SPACE CHIMPS 18657, SPIES LIKE US 38596, SPREAD 20689, STARSTRUCK 25480, SUPER MARIO BROS. 26790, SWEPT AWAY 32312, TAKING WOODSTOCK 2584, THE ADVENTURES OF BARON MUNCHAUSEN 36394, THE ADVENTURES OF ELMO IN GROUCHLAND 13521, THE ADVENTURES OF FORD FAIRLANE 27549, THE BOOK OF LIFE 22479, THE BOXTROLLS 10194, THE BRAVE LITTLE TOASTER 21330, THE CRIMSON PIRATE 33846, THE CROODS 2102, THE DARWIN AWARDS 18263, THE DUKES OF HAZZARD 4068, THE GENERAL 5518, THE GOONIES 32102, THE HARD WAY 5080, THE HOUSE OF BRANCHING LOVE 18150, THE JEWEL OF THE NILE 32856, THE KING AND FOUR QUEENS 15588, THE LAST REMAKE OF BEAU GESTE 39875, THE LEGO MOVIE 18874, THE MAID 6999, THE MISFORTUNATES 9262, THE MISSING PERSON 9886, THE OPEN ROAD 3765, THE OTHER WOMAN 29641, THE PRINCESS BRIDE 31851, THE PRISONER OF ZENDA 23530, THE ROAD TO EL DORADO 17460, THE RUGRATS MOVIE 2739, THE SAPPHIRES 30746, THE SECRET LIFE OF WALTER MITTY 15608, THE SPONGEBOB SQUAREPANTS MOVIE 23400, THE STUPIDS 7816, THE THREE MUSKETEERS 1772, THE WILD 20291, THE WIZARD 17209, THERE'S NO BUSINESS LIKE SHOW BUSINESS 37331, TO DIE FOR 25443, TOM JONES 9450, TOY STORY 14499, TOY STORY 2 30747, TROOP BEVERLY HILLS 5574, UP 38723, VIBES 11659, VIVA MARIA! 1486, WAKE 11010, WILD AMERICA 12576, YOUTH IN REVOLT 2542, ZAMBEZIA 29480, ZEUS AND ROXANNE src, edge_attr, dst 25221, has_genre, 30463 25221, has_genre, 36212 14896, has_genre, 30463 14896, has_genre, 36212 319, has_genre, 4763 319, has_genre, 30463 319, has_tags, 30463 30146, has_genre, 30463 30146, has_genre, 36212 24039, has_genre, 30463 24039, has_genre, 36212 8198, has_genre, 30463 8198, has_genre, 36212 6476, has_genre, 4763 6476, has_genre, 30463 30985, has_genre, 30463 30985, has_genre, 36212 16054, has_genre, 4763 16054, has_genre, 30463 16054, has_tags, 4763 28412, has_genre, 4763 28412, has_genre, 30463 16486, has_genre, 4763 16486, has_genre, 30463 22412, has_genre, 4763 22412, has_genre, 30463 22412, has_tags, 4763 35485, has_genre, 4763 35485, has_genre, 30463 38447, has_genre, 30463 38447, has_genre, 36212 39876, has_genre, 30463 39876, has_genre, 36212 35941, has_genre, 4763 35941, has_genre, 30463 35941, has_tags, 4763 18310, has_genre, 4763 18310, has_genre, 30463 2385, has_genre, 4763 2385, has_genre, 30463 1822, has_genre, 30463 1822, has_genre, 36212 35639, has_genre, 4763 35639, has_genre, 30463 38657, has_genre, 4763 38657, has_genre, 30463 32479, has_genre, 30463 32479, has_genre, 36212 32479, has_tags, 30463 18646, has_genre, 4763 18646, has_genre, 30463 11779, has_genre, 4763 11779, has_genre, 30463 7314, has_genre, 4763 7314, has_genre, 30463 11066, has_genre, 30463 11066, has_genre, 36212 31957, has_genre, 30463 31957, has_genre, 36212 12910, has_genre, 30463 12910, has_genre, 36212 5823, has_genre, 4763 5823, has_genre, 30463 14480, has_genre, 4763 14480, has_genre, 30463 10356, has_genre, 4763 10356, has_genre, 30463 1587, has_genre, 4763 1587, has_genre, 30463 30039, has_genre, 30463 30039, has_genre, 36212 33196, has_genre, 4763 33196, has_genre, 30463 33196, has_tags, 30463 16795, has_genre, 4763 16795, has_genre, 30463 524, has_genre, 4763 524, has_genre, 30463 10349, has_genre, 30463 10349, has_genre, 36212 21479, has_genre, 30463 21479, has_genre, 36212 28503, has_genre, 4763 28503, has_genre, 30463 28503, has_genre, 36212 38556, has_genre, 30463 38556, has_genre, 36212 29904, has_genre, 4763 29904, has_genre, 30463 30802, has_genre, 4763 30802, has_genre, 30463 30802, has_tags, 4763 22663, has_genre, 30463 22663, has_genre, 36212 32301, has_genre, 30463 32301, has_genre, 36212 25657, has_genre, 30463 25657, has_genre, 36212 5881, has_genre, 4763 1329, has_genre, 30463 1329, has_genre, 36212 19367, has_genre, 4763 19367, has_genre, 30463 2449, has_genre, 4763 2449, has_genre, 30463 2449, has_tags, 30463 18031, has_genre, 4763 18031, has_genre, 36212 15349, has_genre, 4763 15349, has_genre, 30463 15349, has_tags, 30463 2287, has_genre, 4763 2287, has_genre, 30463 5287, has_genre, 30463 5287, has_genre, 36212 5514, has_genre, 30463 5514, has_genre, 36212 5514, has_tags, 30463 5514, has_tags, 36212 2320, has_genre, 4763 2320, has_genre, 30463 17440, has_genre, 4763 17440, has_genre, 30463 17440, has_tags, 30463 20263, has_genre, 30463 20263, has_genre, 36212 4649, has_genre, 30463 4649, has_genre, 36212 11014, has_genre, 30463 11014, has_genre, 36212 1292, has_genre, 30463 1292, has_genre, 36212 20008, has_genre, 4763 20008, has_genre, 30463 39494, has_genre, 4763 39494, has_genre, 30463 39494, has_genre, 36212 7811, has_genre, 4763 7811, has_genre, 30463 7811, has_tags, 30463 5617, has_genre, 4763 5617, has_genre, 30463 5617, has_tags, 30463 358, has_genre, 4763 358, has_genre, 30463 38457, has_genre, 30463 38457, has_genre, 36212 16371, has_genre, 4763 16371, has_genre, 30463 16371, has_tags, 30463 38176, has_genre, 30463 38176, has_genre, 36212 5747, has_genre, 30463 5747, has_genre, 36212 32383, has_genre, 4763 32383, has_genre, 30463 2368, has_genre, 4763 2368, has_genre, 30463 2368, has_tags, 30463 32995, has_genre, 4763 32995, has_genre, 30463 25097, has_genre, 4763 25097, has_genre, 30463 25097, has_tags, 30463 17903, has_genre, 30463 17903, has_genre, 36212 19667, has_genre, 30463 19667, has_genre, 36212 16814, has_genre, 30463 16814, has_genre, 36212 35457, has_genre, 30463 35457, has_genre, 36212 35457, has_tags, 30463 7813, has_genre, 30463 7813, has_genre, 36212 25283, has_genre, 4763 25283, has_genre, 30463 25283, has_tags, 30463 13873, has_genre, 30463 13873, has_genre, 36212 17135, has_genre, 4763 17135, has_genre, 30463 34451, has_genre, 30463 34451, has_genre, 36212 11444, has_genre, 4763 11444, has_genre, 30463 32058, has_genre, 4763 32058, has_genre, 30463 3027, has_genre, 4763 3027, has_genre, 30463 17860, has_genre, 36212 17860, written_by, 10378 32358, has_genre, 4763 32358, has_genre, 30463 32358, has_genre, 36212 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 8108, has_genre, 30463 8108, has_genre, 36212 25824, has_genre, 4763 25824, has_genre, 30463 25824, has_genre, 36212 30055, has_genre, 4763 30055, has_genre, 30463 23964, has_genre, 30463 23964, has_genre, 36212 2391, has_genre, 4763 2391, has_genre, 30463 31703, has_genre, 4763 31703, has_genre, 30463 30475, has_genre, 4763 30475, has_genre, 30463 30475, has_tags, 4763 30475, has_tags, 30463 10686, has_genre, 4763 10686, has_genre, 30463 28221, has_genre, 4763 28221, has_genre, 30463 28221, has_tags, 4763 35586, has_genre, 4763 35586, has_genre, 30463 35586, has_genre, 36212 10371, has_genre, 30463 10371, has_genre, 36212 5629, has_genre, 4763 5629, has_genre, 30463 4945, has_genre, 30463 4945, has_genre, 36212 38231, has_genre, 4763 38231, has_genre, 30463 29832, has_genre, 30463 29832, has_genre, 36212 23608, has_genre, 4763 23608, has_genre, 30463 23608, has_tags, 4763 23608, has_tags, 30463 24506, has_genre, 4763 24506, has_genre, 30463 18657, has_genre, 4763 18657, has_genre, 30463 38596, has_genre, 30463 38596, has_genre, 36212 20689, has_genre, 30463 20689, has_genre, 36212 25480, has_genre, 4763 25480, has_genre, 30463 25480, has_tags, 30463 26790, has_genre, 4763 26790, has_genre, 30463 26790, has_genre, 36212 32312, has_genre, 30463 32312, has_genre, 36212 2584, has_genre, 4763 2584, has_genre, 30463 36394, has_genre, 4763 36394, has_genre, 30463 13521, has_genre, 4763 13521, has_genre, 30463 13521, has_tags, 30463 27549, has_genre, 4763 27549, has_genre, 30463 22479, has_genre, 4763 22479, has_genre, 30463 22479, has_tags, 4763 10194, has_genre, 4763 10194, has_genre, 30463 21330, has_genre, 4763 21330, has_genre, 30463 33846, has_genre, 4763 33846, has_genre, 30463 33846, has_tags, 30463 2102, has_genre, 4763 2102, has_genre, 30463 18263, has_genre, 4763 18263, has_genre, 30463 4068, has_genre, 4763 4068, has_genre, 30463 4068, has_tags, 30463 5518, has_genre, 4763 5518, has_genre, 30463 5518, has_tags, 4763 32102, has_genre, 30463 32102, has_genre, 36212 5080, has_genre, 30463 5080, has_genre, 36212 18150, has_genre, 4763 18150, has_genre, 30463 18150, has_tags, 4763 18150, has_tags, 30463 32856, has_genre, 4763 32856, has_genre, 30463 15588, has_genre, 4763 15588, has_genre, 30463 39875, has_genre, 4763 39875, has_genre, 30463 18874, has_genre, 30463 18874, has_genre, 36212 6999, has_genre, 30463 6999, has_genre, 36212 9262, has_genre, 30463 9262, has_genre, 36212 9886, has_genre, 30463 9886, has_genre, 36212 3765, has_genre, 30463 3765, has_genre, 36212 29641, has_genre, 4763 29641, has_genre, 30463 29641, has_tags, 30463 31851, has_genre, 4763 31851, has_genre, 30463 31851, has_genre, 36212 23530, has_genre, 4763 23530, has_genre, 30463 17460, has_genre, 4763 17460, has_genre, 30463 2739, has_genre, 30463 2739, has_genre, 36212 30746, has_genre, 4763 30746, has_genre, 30463 30746, has_genre, 36212 15608, has_genre, 4763 15608, has_genre, 30463 23400, has_genre, 4763 23400, has_genre, 30463 7816, has_genre, 4763 7816, has_genre, 30463 7816, has_genre, 36212 1772, has_genre, 4763 1772, has_genre, 30463 20291, has_genre, 4763 20291, has_genre, 30463 20291, has_genre, 36212 17209, has_genre, 30463 17209, has_genre, 36212 37331, has_genre, 30463 37331, has_genre, 36212 25443, has_genre, 4763 25443, has_genre, 30463 9450, has_genre, 4763 9450, has_genre, 30463 9450, has_tags, 4763 9450, has_tags, 30463 14499, has_genre, 4763 14499, has_genre, 30463 30747, has_genre, 4763 30747, has_genre, 30463 5574, has_genre, 4763 5574, has_genre, 30463 5574, has_tags, 4763 5574, has_tags, 30463 38723, has_genre, 4763 38723, has_genre, 30463 11659, has_genre, 4763 11659, has_genre, 30463 1486, has_genre, 30463 1486, has_genre, 36212 11010, has_genre, 4763 11010, has_genre, 30463 12576, has_genre, 30463 12576, has_genre, 36212 2542, has_genre, 4763 2542, has_genre, 30463 29480, has_genre, 4763 29480, has_genre, 30463 Question: For what reason are DAN IN REAL LIFE, ELEPHANT BOY, and MAURY YESTON associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAN IN REAL LIFE", "ELEPHANT BOY", "MAURY YESTON" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "has_genre", "DRAMA" ], [ "3 IDIOTS", "has_genre", "COMEDY" ], [ "3 IDIOTS", "has_genre", "DRAMA" ], [ "A BUG'S LIFE", "has_genre", "ADVENTURE" ], [ "A BUG'S LIFE", "has_genre", "COMEDY" ], [ "A BUG'S LIFE", "has_tags", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "has_genre", "DRAMA" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "DRAMA" ], [ "A WALK IN THE WOODS", "has_genre", "ADVENTURE" ], [ "A WALK IN THE WOODS", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "DRAMA" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "AFRICA SCREAMS", "has_genre", "ADVENTURE" ], [ "AFRICA SCREAMS", "has_genre", "COMEDY" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "ALMOST HEROES", "has_genre", "ADVENTURE" ], [ "ALMOST HEROES", "has_genre", "COMEDY" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "COMEDY" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "DRAMA" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANTZ", "has_genre", "ADVENTURE" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "has_tags", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "COMEDY" ], [ "AROUND THE WORLD IN EIGHTY DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN EIGHTY DAYS", "has_genre", "COMEDY" ], [ "AWAY WE GO", "has_genre", "COMEDY" ], [ "AWAY WE GO", "has_genre", "DRAMA" ], [ "BABY'S DAY OUT", "has_genre", "ADVENTURE" ], [ "BABY'S DAY OUT", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_genre", "DRAMA" ], [ "BEWITCHED", "has_tags", "COMEDY" ], [ "BIG SHOTS", "has_genre", "ADVENTURE" ], [ "BIG SHOTS", "has_genre", "COMEDY" ], [ "BIG TOP PEE-WEE", "has_genre", "ADVENTURE" ], [ "BIG TOP PEE-WEE", "has_genre", "COMEDY" ], [ "BOLT", "has_genre", "ADVENTURE" ], [ "BOLT", "has_genre", "COMEDY" ], [ "BOMBER", "has_genre", "COMEDY" ], [ "BOMBER", "has_genre", "DRAMA" ], [ "BOY", "has_genre", "COMEDY" ], [ "BOY", "has_genre", "DRAMA" ], [ "BRIEF INTERVIEWS WITH HIDEOUS MEN", "has_genre", "COMEDY" ], [ "BRIEF INTERVIEWS WITH HIDEOUS MEN", "has_genre", "DRAMA" ], [ "BROTHER BEAR 2", "has_genre", "ADVENTURE" ], [ "BROTHER BEAR 2", "has_genre", "COMEDY" ], [ "BUDDIES", "has_genre", "ADVENTURE" ], [ "BUDDIES", "has_genre", "COMEDY" ], [ "BUNTY AUR BABLI", "has_genre", "ADVENTURE" ], [ "BUNTY AUR BABLI", "has_genre", "COMEDY" ], [ "BUSHWHACKED", "has_genre", "ADVENTURE" ], [ "BUSHWHACKED", "has_genre", "COMEDY" ], [ "CAPTAIN JANUARY", "has_genre", "COMEDY" ], [ "CAPTAIN JANUARY", "has_genre", "DRAMA" ], [ "CARS", "has_genre", "ADVENTURE" ], [ "CARS", "has_genre", "COMEDY" ], [ "CARS", "has_tags", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "ADVENTURE" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CITY ISLAND", "has_genre", "COMEDY" ], [ "CITY ISLAND", "has_genre", "DRAMA" ], [ "CLOUDBURST", "has_genre", "ADVENTURE" ], [ "CLOUDBURST", "has_genre", "COMEDY" ], [ "CLOUDBURST", "has_genre", "DRAMA" ], [ "COLD SOULS", "has_genre", "COMEDY" ], [ "COLD SOULS", "has_genre", "DRAMA" ], [ "CONDORMAN", "has_genre", "ADVENTURE" ], [ "CONDORMAN", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "DAN IN REAL LIFE", "has_genre", "COMEDY" ], [ "DAN IN REAL LIFE", "has_genre", "DRAMA" ], [ "DEFENDOR", "has_genre", "COMEDY" ], [ "DEFENDOR", "has_genre", "DRAMA" ], [ "DELHI-6", "has_genre", "COMEDY" ], [ "DELHI-6", "has_genre", "DRAMA" ], [ "ELEPHANT BOY", "has_genre", "ADVENTURE" ], [ "ENVY", "has_genre", "COMEDY" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ESCAPE TO ATHENA", "has_genre", "ADVENTURE" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_genre", "ADVENTURE" ], [ "EUROTRIP", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_tags", "COMEDY" ], [ "FAR AND AWAY", "has_genre", "ADVENTURE" ], [ "FAR AND AWAY", "has_genre", "DRAMA" ], [ "FINDING NEMO", "has_genre", "ADVENTURE" ], [ "FINDING NEMO", "has_genre", "COMEDY" ], [ "FINDING NEMO", "has_tags", "COMEDY" ], [ "FLUSHED AWAY", "has_genre", "ADVENTURE" ], [ "FLUSHED AWAY", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_genre", "COMEDY" ], [ "FUNNY PEOPLE", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "COMEDY" ], [ "FUNNY PEOPLE", "has_tags", "DRAMA" ], [ "GRIND", "has_genre", "ADVENTURE" ], [ "GRIND", "has_genre", "COMEDY" ], [ "GULLIVER'S TRAVELS", "has_genre", "ADVENTURE" ], [ "GULLIVER'S TRAVELS", "has_genre", "COMEDY" ], [ "GULLIVER'S TRAVELS", "has_tags", "COMEDY" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "has_genre", "DRAMA" ], [ "HAPPY TEARS", "has_genre", "COMEDY" ], [ "HAPPY TEARS", "has_genre", "DRAMA" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "COMEDY" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HELP!", "has_genre", "ADVENTURE" ], [ "HELP!", "has_genre", "COMEDY" ], [ "HOLES", "has_genre", "ADVENTURE" ], [ "HOLES", "has_genre", "COMEDY" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HORTON HEARS A WHO!", "has_genre", "ADVENTURE" ], [ "HORTON HEARS A WHO!", "has_genre", "COMEDY" ], [ "HORTON HEARS A WHO!", "has_tags", "COMEDY" ], [ "HOT TUB TIME MACHINE", "has_genre", "ADVENTURE" ], [ "HOT TUB TIME MACHINE", "has_genre", "COMEDY" ], [ "HOT TUB TIME MACHINE", "has_tags", "COMEDY" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "I CAN DO BAD ALL BY MYSELF", "has_genre", "COMEDY" ], [ "I CAN DO BAD ALL BY MYSELF", "has_genre", "DRAMA" ], [ "ICE AGE", "has_genre", "ADVENTURE" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "IDIOT'S DELIGHT", "has_genre", "COMEDY" ], [ "IDIOT'S DELIGHT", "has_genre", "DRAMA" ], [ "IMAGINE THAT", "has_genre", "COMEDY" ], [ "IMAGINE THAT", "has_genre", "DRAMA" ], [ "JOE DIRT", "has_genre", "ADVENTURE" ], [ "JOE DIRT", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_genre", "ADVENTURE" ], [ "KANGAROO JACK", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_tags", "COMEDY" ], [ "LAND HO!", "has_genre", "ADVENTURE" ], [ "LAND HO!", "has_genre", "COMEDY" ], [ "LAND OF THE LOST", "has_genre", "ADVENTURE" ], [ "LAND OF THE LOST", "has_genre", "COMEDY" ], [ "LAND OF THE LOST", "has_tags", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "DRAMA" ], [ "LIFE DURING WARTIME", "has_genre", "COMEDY" ], [ "LIFE DURING WARTIME", "has_genre", "DRAMA" ], [ "LITTLE WHITE LIES", "has_genre", "COMEDY" ], [ "LITTLE WHITE LIES", "has_genre", "DRAMA" ], [ "MADEA GOES TO JAIL", "has_genre", "COMEDY" ], [ "MADEA GOES TO JAIL", "has_genre", "DRAMA" ], [ "MADEA GOES TO JAIL", "has_tags", "COMEDY" ], [ "MARY AND MAX", "has_genre", "COMEDY" ], [ "MARY AND MAX", "has_genre", "DRAMA" ], [ "MAVERICK", "has_genre", "ADVENTURE" ], [ "MAVERICK", "has_genre", "COMEDY" ], [ "MAVERICK", "has_tags", "COMEDY" ], [ "MIDDLE MEN", "has_genre", "COMEDY" ], [ "MIDDLE MEN", "has_genre", "DRAMA" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "ADVENTURE" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "COMEDY" ], [ "MOTHERHOOD", "has_genre", "COMEDY" ], [ "MOTHERHOOD", "has_genre", "DRAMA" ], [ "MR. ROBINSON CRUSOE", "has_genre", "ADVENTURE" ], [ "MR. ROBINSON CRUSOE", "has_genre", "COMEDY" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "has_genre", "ADVENTURE" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NINE", "has_genre", "DRAMA" ], [ "NINE", "written_by", "MAURY YESTON" ], [ "NORTH", "has_genre", "ADVENTURE" ], [ "NORTH", "has_genre", "COMEDY" ], [ "NORTH", "has_genre", "DRAMA" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "PAPER MAN", "has_genre", "COMEDY" ], [ "PAPER MAN", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "ADVENTURE" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PEE-WEE'S BIG ADVENTURE", "has_genre", "ADVENTURE" ], [ "PEE-WEE'S BIG ADVENTURE", "has_genre", "COMEDY" ], [ "PENNIES FROM HEAVEN", "has_genre", "COMEDY" ], [ "PENNIES FROM HEAVEN", "has_genre", "DRAMA" ], [ "PIRATES", "has_genre", "ADVENTURE" ], [ "PIRATES", "has_genre", "COMEDY" ], [ "PUSS IN BOOTS", "has_genre", "ADVENTURE" ], [ "PUSS IN BOOTS", "has_genre", "COMEDY" ], [ "RIO", "has_genre", "ADVENTURE" ], [ "RIO", "has_genre", "COMEDY" ], [ "RIO", "has_tags", "ADVENTURE" ], [ "RIO", "has_tags", "COMEDY" ], [ "RIO 2", "has_genre", "ADVENTURE" ], [ "RIO 2", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAINT JOHN OF LAS VEGAS", "has_genre", "COMEDY" ], [ "SAINT JOHN OF LAS VEGAS", "has_genre", "DRAMA" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "ADVENTURE" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "COMEDY" ], [ "SEPARATION CITY", "has_genre", "COMEDY" ], [ "SEPARATION CITY", "has_genre", "DRAMA" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHANGHAI NOON", "has_genre", "COMEDY" ], [ "SHOW BOAT", "has_genre", "COMEDY" ], [ "SHOW BOAT", "has_genre", "DRAMA" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "ADVENTURE" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "ADVENTURE" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "COMEDY" ], [ "SPACE CHIMPS", "has_genre", "ADVENTURE" ], [ "SPACE CHIMPS", "has_genre", "COMEDY" ], [ "SPIES LIKE US", "has_genre", "ADVENTURE" ], [ "SPIES LIKE US", "has_genre", "COMEDY" ], [ "SPREAD", "has_genre", "COMEDY" ], [ "SPREAD", "has_genre", "DRAMA" ], [ "STARSTRUCK", "has_genre", "COMEDY" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "SUPER MARIO BROS.", "has_genre", "ADVENTURE" ], [ "SUPER MARIO BROS.", "has_genre", "COMEDY" ], [ "SUPER MARIO BROS.", "has_tags", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "TAKING WOODSTOCK", "has_genre", "COMEDY" ], [ "TAKING WOODSTOCK", "has_genre", "DRAMA" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF ELMO IN GROUCHLAND", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF ELMO IN GROUCHLAND", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE BOOK OF LIFE", "has_genre", "ADVENTURE" ], [ "THE BOOK OF LIFE", "has_genre", "COMEDY" ], [ "THE BOXTROLLS", "has_genre", "ADVENTURE" ], [ "THE BOXTROLLS", "has_genre", "COMEDY" ], [ "THE BOXTROLLS", "has_tags", "ADVENTURE" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "ADVENTURE" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "COMEDY" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_genre", "COMEDY" ], [ "THE CROODS", "has_genre", "ADVENTURE" ], [ "THE CROODS", "has_genre", "COMEDY" ], [ "THE CROODS", "has_tags", "COMEDY" ], [ "THE DARWIN AWARDS", "has_genre", "ADVENTURE" ], [ "THE DARWIN AWARDS", "has_genre", "COMEDY" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE DUKES OF HAZZARD", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE GOONIES", "has_genre", "ADVENTURE" ], [ "THE GOONIES", "has_genre", "COMEDY" ], [ "THE GOONIES", "has_tags", "ADVENTURE" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HOUSE OF BRANCHING LOVE", "has_genre", "COMEDY" ], [ "THE HOUSE OF BRANCHING LOVE", "has_genre", "DRAMA" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_genre", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "COMEDY" ], [ "THE KING AND FOUR QUEENS", "has_genre", "ADVENTURE" ], [ "THE KING AND FOUR QUEENS", "has_genre", "COMEDY" ], [ "THE LAST REMAKE OF BEAU GESTE", "has_genre", "ADVENTURE" ], [ "THE LAST REMAKE OF BEAU GESTE", "has_genre", "COMEDY" ], [ "THE LEGO MOVIE", "has_genre", "ADVENTURE" ], [ "THE LEGO MOVIE", "has_genre", "COMEDY" ], [ "THE MAID", "has_genre", "COMEDY" ], [ "THE MAID", "has_genre", "DRAMA" ], [ "THE MISFORTUNATES", "has_genre", "COMEDY" ], [ "THE MISFORTUNATES", "has_genre", "DRAMA" ], [ "THE MISSING PERSON", "has_genre", "COMEDY" ], [ "THE MISSING PERSON", "has_genre", "DRAMA" ], [ "THE OPEN ROAD", "has_genre", "COMEDY" ], [ "THE OPEN ROAD", "has_genre", "DRAMA" ], [ "THE OTHER WOMAN", "has_genre", "COMEDY" ], [ "THE OTHER WOMAN", "has_genre", "DRAMA" ], [ "THE PRINCESS BRIDE", "has_genre", "ADVENTURE" ], [ "THE PRINCESS BRIDE", "has_genre", "COMEDY" ], [ "THE PRINCESS BRIDE", "has_tags", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE ROAD TO EL DORADO", "has_genre", "ADVENTURE" ], [ "THE ROAD TO EL DORADO", "has_genre", "COMEDY" ], [ "THE RUGRATS MOVIE", "has_genre", "ADVENTURE" ], [ "THE RUGRATS MOVIE", "has_genre", "COMEDY" ], [ "THE SAPPHIRES", "has_genre", "COMEDY" ], [ "THE SAPPHIRES", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "ADVENTURE" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "COMEDY" ], [ "THE STUPIDS", "has_genre", "ADVENTURE" ], [ "THE STUPIDS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE WILD", "has_genre", "ADVENTURE" ], [ "THE WILD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "ADVENTURE" ], [ "THE WIZARD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "DRAMA" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "COMEDY" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "DRAMA" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_genre", "COMEDY" ], [ "TOY STORY", "has_genre", "ADVENTURE" ], [ "TOY STORY", "has_genre", "COMEDY" ], [ "TOY STORY", "has_tags", "ADVENTURE" ], [ "TOY STORY", "has_tags", "COMEDY" ], [ "TOY STORY 2", "has_genre", "ADVENTURE" ], [ "TOY STORY 2", "has_genre", "COMEDY" ], [ "TROOP BEVERLY HILLS", "has_genre", "ADVENTURE" ], [ "TROOP BEVERLY HILLS", "has_genre", "COMEDY" ], [ "UP", "has_genre", "ADVENTURE" ], [ "UP", "has_genre", "COMEDY" ], [ "UP", "has_tags", "ADVENTURE" ], [ "UP", "has_tags", "COMEDY" ], [ "VIBES", "has_genre", "ADVENTURE" ], [ "VIBES", "has_genre", "COMEDY" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "WAKE", "has_genre", "COMEDY" ], [ "WAKE", "has_genre", "DRAMA" ], [ "WILD AMERICA", "has_genre", "ADVENTURE" ], [ "WILD AMERICA", "has_genre", "COMEDY" ], [ "YOUTH IN REVOLT", "has_genre", "COMEDY" ], [ "YOUTH IN REVOLT", "has_genre", "DRAMA" ], [ "ZAMBEZIA", "has_genre", "ADVENTURE" ], [ "ZAMBEZIA", "has_genre", "COMEDY" ], [ "ZEUS AND ROXANNE", "has_genre", "ADVENTURE" ], [ "ZEUS AND ROXANNE", "has_genre", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 29170, BREATHING FIRE 30463, COMEDY 16978, DON'T TELL MOM THE BABYSITTER'S DEAD 21745, EDDIE SAAVEDRA 25973, HITCH 2745, JOSH CHARLES 670, KEVIN BISCH 1053, PIE IN THE SKY 16762, THREESOME src, edge_attr, dst 29170, release_year, 10702 29170, starred_actors, 21745 16978, has_genre, 30463 16978, release_year, 10702 16978, starred_actors, 2745 25973, has_genre, 30463 25973, has_tags, 30463 25973, written_by, 670 1053, has_genre, 30463 1053, starred_actors, 2745 16762, has_genre, 30463 16762, has_tags, 30463 16762, starred_actors, 2745 Question: For what reason are EDDIE SAAVEDRA, JOSH CHARLES, and KEVIN BISCH associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EDDIE SAAVEDRA", "JOSH CHARLES", "KEVIN BISCH" ], "valid_edges": [ [ "BREATHING FIRE", "release_year", "1991" ], [ "BREATHING FIRE", "starred_actors", "EDDIE SAAVEDRA" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "has_genre", "COMEDY" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "release_year", "1991" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "starred_actors", "JOSH CHARLES" ], [ "HITCH", "has_genre", "COMEDY" ], [ "HITCH", "has_tags", "COMEDY" ], [ "HITCH", "written_by", "KEVIN BISCH" ], [ "PIE IN THE SKY", "has_genre", "COMEDY" ], [ "PIE IN THE SKY", "starred_actors", "JOSH CHARLES" ], [ "THREESOME", "has_genre", "COMEDY" ], [ "THREESOME", "has_tags", "COMEDY" ], [ "THREESOME", "starred_actors", "JOSH CHARLES" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 10045, BD-R 398, LOST HIGHWAY 22121, LUST FOR LIFE 20417, NIGHTWATCH 34619, NORMAN CORWIN 28554, PATRICIA ARQUETTE 14254, RICHARD CONDON 29773, THE MANCHURIAN CANDIDATE 24811, THRILLER src, edge_attr, dst 398, has_genre, 24811 398, has_tags, 28554 398, release_year, 14259 398, starred_actors, 28554 22121, has_tags, 10045 22121, written_by, 34619 20417, has_genre, 24811 20417, release_year, 14259 20417, starred_actors, 28554 29773, has_genre, 24811 29773, has_tags, 10045 29773, has_tags, 24811 29773, written_by, 14254 Question: How are NORMAN CORWIN, PATRICIA ARQUETTE, and RICHARD CONDON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "NORMAN CORWIN", "PATRICIA ARQUETTE", "RICHARD CONDON" ], "valid_edges": [ [ "LOST HIGHWAY", "has_genre", "THRILLER" ], [ "LOST HIGHWAY", "has_tags", "PATRICIA ARQUETTE" ], [ "LOST HIGHWAY", "release_year", "1997" ], [ "LOST HIGHWAY", "starred_actors", "PATRICIA ARQUETTE" ], [ "LUST FOR LIFE", "has_tags", "BD-R" ], [ "LUST FOR LIFE", "written_by", "NORMAN CORWIN" ], [ "NIGHTWATCH", "has_genre", "THRILLER" ], [ "NIGHTWATCH", "release_year", "1997" ], [ "NIGHTWATCH", "starred_actors", "PATRICIA ARQUETTE" ], [ "THE MANCHURIAN CANDIDATE", "has_genre", "THRILLER" ], [ "THE MANCHURIAN CANDIDATE", "has_tags", "BD-R" ], [ "THE MANCHURIAN CANDIDATE", "has_tags", "THRILLER" ], [ "THE MANCHURIAN CANDIDATE", "written_by", "RICHARD CONDON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39289, ACTION 34158, AMERICAN YAKUZA 39730, CHUCK LOGAN 9711, HOMEFRONT 5005, JAMES GARNER 36694, JOHN ALLEN NELSON 40018, SUNSET 10952, TANK src, edge_attr, dst 34158, has_genre, 39289 34158, written_by, 36694 9711, has_genre, 39289 9711, written_by, 39730 40018, has_genre, 39289 40018, starred_actors, 5005 10952, has_genre, 39289 10952, starred_actors, 5005 Question: For what reason are CHUCK LOGAN, JAMES GARNER, and JOHN ALLEN NELSON associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHUCK LOGAN", "JAMES GARNER", "JOHN ALLEN NELSON" ], "valid_edges": [ [ "AMERICAN YAKUZA", "has_genre", "ACTION" ], [ "AMERICAN YAKUZA", "written_by", "JOHN ALLEN NELSON" ], [ "HOMEFRONT", "has_genre", "ACTION" ], [ "HOMEFRONT", "written_by", "CHUCK LOGAN" ], [ "SUNSET", "has_genre", "ACTION" ], [ "SUNSET", "starred_actors", "JAMES GARNER" ], [ "TANK", "has_genre", "ACTION" ], [ "TANK", "starred_actors", "JAMES GARNER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 28175, ANDRÉS MUSCHIETTI 19888, ANNA THOMAS 36403, EL NORTE 31648, FRIGHT NIGHT 5870, HORROR 29898, MAMA 37497, NATIONAL FILM REGISTRY 27643, PLANET OF THE APES 28729, REMAKE 18518, RODDY MCDOWALL 8623, THE LEGEND OF HELL HOUSE src, edge_attr, dst 36403, has_tags, 37497 36403, written_by, 19888 31648, has_genre, 5870 31648, has_tags, 28729 31648, has_tags, 18518 31648, starred_actors, 18518 29898, directed_by, 28175 29898, has_genre, 5870 29898, has_tags, 5870 29898, written_by, 28175 27643, has_tags, 37497 27643, has_tags, 28729 27643, starred_actors, 18518 8623, has_genre, 5870 8623, has_tags, 18518 8623, starred_actors, 18518 Question: How are ANDRÉS MUSCHIETTI, ANNA THOMAS, and RODDY MCDOWALL related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANDRÉS MUSCHIETTI", "ANNA THOMAS", "RODDY MCDOWALL" ], "valid_edges": [ [ "EL NORTE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "EL NORTE", "written_by", "ANNA THOMAS" ], [ "FRIGHT NIGHT", "has_genre", "HORROR" ], [ "FRIGHT NIGHT", "has_tags", "REMAKE" ], [ "FRIGHT NIGHT", "has_tags", "RODDY MCDOWALL" ], [ "FRIGHT NIGHT", "starred_actors", "RODDY MCDOWALL" ], [ "MAMA", "directed_by", "ANDRÉS MUSCHIETTI" ], [ "MAMA", "has_genre", "HORROR" ], [ "MAMA", "has_tags", "HORROR" ], [ "MAMA", "written_by", "ANDRÉS MUSCHIETTI" ], [ "PLANET OF THE APES", "has_tags", "NATIONAL FILM REGISTRY" ], [ "PLANET OF THE APES", "has_tags", "REMAKE" ], [ "PLANET OF THE APES", "starred_actors", "RODDY MCDOWALL" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "RODDY MCDOWALL" ], [ "THE LEGEND OF HELL HOUSE", "starred_actors", "RODDY MCDOWALL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36212, DRAMA 29176, FOUR FRIENDS 26579, ISABEL JEWELL 15908, JODI THELEN 18688, MARKED WOMAN 37681, OMAR NAIM 19685, THE FINAL CUT src, edge_attr, dst 29176, has_genre, 36212 29176, starred_actors, 15908 18688, has_genre, 36212 18688, starred_actors, 26579 19685, directed_by, 37681 19685, has_genre, 36212 19685, written_by, 37681 Question: In what context are ISABEL JEWELL, JODI THELEN, and OMAR NAIM connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ISABEL JEWELL", "JODI THELEN", "OMAR NAIM" ], "valid_edges": [ [ "FOUR FRIENDS", "has_genre", "DRAMA" ], [ "FOUR FRIENDS", "starred_actors", "JODI THELEN" ], [ "MARKED WOMAN", "has_genre", "DRAMA" ], [ "MARKED WOMAN", "starred_actors", "ISABEL JEWELL" ], [ "THE FINAL CUT", "directed_by", "OMAR NAIM" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "written_by", "OMAR NAIM" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30463, COMEDY 27897, DOCTOR DOLITTLE 7982, PLASTIC 18159, SAMANTHA EGGAR 28213, SEBASTIAN DE SOUZA 10940, THE LOVE BUG 29169, VOLKSWAGEN src, edge_attr, dst 27897, has_genre, 30463 27897, starred_actors, 18159 7982, has_genre, 30463 7982, starred_actors, 28213 10940, has_genre, 30463 10940, has_tags, 29169 Question: For what reason are SAMANTHA EGGAR, SEBASTIAN DE SOUZA, and VOLKSWAGEN associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "SAMANTHA EGGAR", "SEBASTIAN DE SOUZA", "VOLKSWAGEN" ], "valid_edges": [ [ "DOCTOR DOLITTLE", "has_genre", "COMEDY" ], [ "DOCTOR DOLITTLE", "starred_actors", "SAMANTHA EGGAR" ], [ "PLASTIC", "has_genre", "COMEDY" ], [ "PLASTIC", "starred_actors", "SEBASTIAN DE SOUZA" ], [ "THE LOVE BUG", "has_genre", "COMEDY" ], [ "THE LOVE BUG", "has_tags", "VOLKSWAGEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 27879, 8 MILE 37548, A COUNTESS FROM HONG KONG 23328, APPALOOSA 10516, BANG BANG YOU'RE DEAD 16969, BETWEEN STRANGERS 28723, BLOODY SUNDAY 16230, BROKEN WINGS 33360, CANDY 33362, CARLITO'S WAY 33387, CITY OF GOD 6116, CYPHER 9641, DIRTY PRETTY THINGS 12628, EASTERN PROMISES 14926, EQUILIBRIUM 11422, FAR FROM HEAVEN 17400, GANGS OF NEW YORK 33545, HART'S WAR 23081, HEAVEN 25271, IN THIS WORLD 978, INFERNAL AFFAIRS 18277, JOHN HILLCOAT 21474, MARLON BRANDO 25269, NINE LIVES 14744, PEOPLE I KNOW 13081, R 32512, RAISING VICTOR VARGAS 4523, RED DRAGON 1749, SOPHIA LOREN 33414, SWEET SIXTEEN 23906, TENSE 35551, THE GODFATHER 12614, THE PIANIST 22294, THE PROPHECY 27029, THE PROPOSITION 20850, THE QUIET AMERICAN 15562, THE ROAD 26916, VIGGO MORTENSEN src, edge_attr, dst 4310, has_tags, 13081 4310, release_year, 35935 9408, has_tags, 13081 9408, release_year, 35935 27879, has_tags, 13081 27879, release_year, 35935 37548, starred_actors, 21474 37548, starred_actors, 1749 23328, has_tags, 13081 23328, has_tags, 26916 10516, has_tags, 13081 10516, release_year, 35935 16969, release_year, 35935 16969, starred_actors, 1749 28723, has_tags, 13081 28723, release_year, 35935 16230, has_tags, 13081 16230, release_year, 35935 33360, has_tags, 13081 33360, starred_actors, 21474 33362, has_tags, 13081 33362, has_tags, 26916 33387, has_tags, 13081 33387, release_year, 35935 6116, has_tags, 13081 6116, release_year, 35935 9641, has_tags, 13081 9641, release_year, 35935 12628, has_tags, 13081 12628, has_tags, 23906 12628, has_tags, 26916 14926, has_tags, 13081 14926, release_year, 35935 11422, has_tags, 13081 11422, release_year, 35935 17400, has_tags, 13081 17400, release_year, 35935 33545, has_tags, 13081 33545, release_year, 35935 23081, has_tags, 13081 23081, release_year, 35935 25271, has_tags, 13081 25271, release_year, 35935 978, has_tags, 13081 978, release_year, 35935 25269, has_tags, 13081 25269, release_year, 35935 14744, has_tags, 13081 14744, release_year, 35935 32512, has_tags, 13081 32512, release_year, 35935 4523, has_tags, 13081 4523, release_year, 35935 33414, has_tags, 13081 33414, release_year, 35935 35551, has_tags, 21474 35551, has_tags, 13081 35551, starred_actors, 21474 12614, has_tags, 13081 12614, release_year, 35935 22294, has_tags, 13081 22294, has_tags, 26916 27029, directed_by, 18277 27029, has_tags, 18277 27029, has_tags, 13081 20850, has_tags, 13081 20850, release_year, 35935 15562, directed_by, 18277 15562, has_tags, 18277 15562, has_tags, 23906 15562, has_tags, 26916 15562, starred_actors, 26916 Question: How are A COUNTESS FROM HONG KONG, IN THIS WORLD, and THE ROAD related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A COUNTESS FROM HONG KONG", "IN THIS WORLD", "THE ROAD" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_tags", "R" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "R" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 MILE", "has_tags", "R" ], [ "8 MILE", "release_year", "2002" ], [ "A COUNTESS FROM HONG KONG", "starred_actors", "MARLON BRANDO" ], [ "A COUNTESS FROM HONG KONG", "starred_actors", "SOPHIA LOREN" ], [ "APPALOOSA", "has_tags", "R" ], [ "APPALOOSA", "has_tags", "VIGGO MORTENSEN" ], [ "BANG BANG YOU'RE DEAD", "has_tags", "R" ], [ "BANG BANG YOU'RE DEAD", "release_year", "2002" ], [ "BETWEEN STRANGERS", "release_year", "2002" ], [ "BETWEEN STRANGERS", "starred_actors", "SOPHIA LOREN" ], [ "BLOODY SUNDAY", "has_tags", "R" ], [ "BLOODY SUNDAY", "release_year", "2002" ], [ "BROKEN WINGS", "has_tags", "R" ], [ "BROKEN WINGS", "release_year", "2002" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "starred_actors", "MARLON BRANDO" ], [ "CARLITO'S WAY", "has_tags", "R" ], [ "CARLITO'S WAY", "has_tags", "VIGGO MORTENSEN" ], [ "CITY OF GOD", "has_tags", "R" ], [ "CITY OF GOD", "release_year", "2002" ], [ "CYPHER", "has_tags", "R" ], [ "CYPHER", "release_year", "2002" ], [ "DIRTY PRETTY THINGS", "has_tags", "R" ], [ "DIRTY PRETTY THINGS", "release_year", "2002" ], [ "EASTERN PROMISES", "has_tags", "R" ], [ "EASTERN PROMISES", "has_tags", "TENSE" ], [ "EASTERN PROMISES", "has_tags", "VIGGO MORTENSEN" ], [ "EQUILIBRIUM", "has_tags", "R" ], [ "EQUILIBRIUM", "release_year", "2002" ], [ "FAR FROM HEAVEN", "has_tags", "R" ], [ "FAR FROM HEAVEN", "release_year", "2002" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "HART'S WAR", "has_tags", "R" ], [ "HART'S WAR", "release_year", "2002" ], [ "HEAVEN", "has_tags", "R" ], [ "HEAVEN", "release_year", "2002" ], [ "IN THIS WORLD", "has_tags", "R" ], [ "IN THIS WORLD", "release_year", "2002" ], [ "INFERNAL AFFAIRS", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "release_year", "2002" ], [ "NINE LIVES", "has_tags", "R" ], [ "NINE LIVES", "release_year", "2002" ], [ "PEOPLE I KNOW", "has_tags", "R" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "RAISING VICTOR VARGAS", "has_tags", "R" ], [ "RAISING VICTOR VARGAS", "release_year", "2002" ], [ "RED DRAGON", "has_tags", "R" ], [ "RED DRAGON", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_tags", "R" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "THE GODFATHER", "has_tags", "MARLON BRANDO" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "starred_actors", "MARLON BRANDO" ], [ "THE PIANIST", "has_tags", "R" ], [ "THE PIANIST", "release_year", "2002" ], [ "THE PROPHECY", "has_tags", "R" ], [ "THE PROPHECY", "has_tags", "VIGGO MORTENSEN" ], [ "THE PROPOSITION", "directed_by", "JOHN HILLCOAT" ], [ "THE PROPOSITION", "has_tags", "JOHN HILLCOAT" ], [ "THE PROPOSITION", "has_tags", "R" ], [ "THE QUIET AMERICAN", "has_tags", "R" ], [ "THE QUIET AMERICAN", "release_year", "2002" ], [ "THE ROAD", "directed_by", "JOHN HILLCOAT" ], [ "THE ROAD", "has_tags", "JOHN HILLCOAT" ], [ "THE ROAD", "has_tags", "TENSE" ], [ "THE ROAD", "has_tags", "VIGGO MORTENSEN" ], [ "THE ROAD", "starred_actors", "VIGGO MORTENSEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 7411, ATSUYA UKI 36031, CENCOROLL 36874, JAPANESE 14772, KING KONG ESCAPES 11279, MIE HAMA 6722, THE TEMPTATION OF ST. TONY 8683, VEIKO ÕUNPUU src, edge_attr, dst 36031, directed_by, 7411 36031, in_language, 36874 36031, release_year, 27261 36031, written_by, 7411 14772, has_tags, 36874 14772, in_language, 36874 14772, starred_actors, 11279 6722, directed_by, 8683 6722, release_year, 27261 6722, written_by, 8683 Question: In what context are ATSUYA UKI, MIE HAMA, and VEIKO ÕUNPUU connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ATSUYA UKI", "MIE HAMA", "VEIKO ÕUNPUU" ], "valid_edges": [ [ "CENCOROLL", "directed_by", "ATSUYA UKI" ], [ "CENCOROLL", "in_language", "JAPANESE" ], [ "CENCOROLL", "release_year", "2009" ], [ "CENCOROLL", "written_by", "ATSUYA UKI" ], [ "KING KONG ESCAPES", "has_tags", "JAPANESE" ], [ "KING KONG ESCAPES", "in_language", "JAPANESE" ], [ "KING KONG ESCAPES", "starred_actors", "MIE HAMA" ], [ "THE TEMPTATION OF ST. TONY", "directed_by", "VEIKO ÕUNPUU" ], [ "THE TEMPTATION OF ST. TONY", "release_year", "2009" ], [ "THE TEMPTATION OF ST. TONY", "written_by", "VEIKO ÕUNPUU" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 12501, A COMPLETE HISTORY OF MY SEXUAL FAILURES 37725, A FILM UNFINISHED 25969, ALIEN RAIDERS 15162, AMERICAN TEEN 10045, BD-R 21206, BETWEEN THE FOLDS 36248, BURDEN OF DREAMS 31264, CAVE OF FORGOTTEN DREAMS 1930, CHELSEA ON THE ROCKS 14657, CSNY/DÉJÀ VU 12841, DOCUMENTARY 17682, EXAMINED LIFE 21393, FIEND WITHOUT A FACE 36306, FOOD, INC. 17291, I.O.U.S.A. 12892, LET'S MAKE MONEY 14834, MAN ON WIRE 23408, OF TIME AND THE CITY 28248, PAGEANT 18482, PRIMARY 24066, REEL INJUN 26777, REMBRANDT'S J'ACCUSE 10160, STANLEY KUBRICK'S BOXES 20580, STONEWALL UPRISING 24721, THAT'S ENTERTAINMENT! III 31138, THAT'S ENTERTAINMENT, PART II 38592, THE BEACHES OF AGNÈS 10103, THE COOL SCHOOL 33467, THE END OF AMERICA 25520, THE END OF POVERTY? 34736, THE ENDLESS SUMMER 2448, THE FORGOTTEN WOMAN 19165, THE LAST PLAY AT SHEA 29471, THE QUEEN AND I 15823, THE RECRUITER 735, THE REVISIONARIES 22610, THE SOVIET STORY 9266, THE TIMES OF HARVEY MILK 28674, TREK NATION 12757, TYSON 10212, UNMISTAKEN CHILD 3016, WALTZ WITH BASHIR 31247, WHERE IN THE WORLD IS OSAMA BIN LADEN? 19574, WISHFUL DRINKING src, edge_attr, dst 12501, has_genre, 12841 12501, release_year, 26762 37725, has_genre, 12841 37725, has_tags, 10045 25969, release_year, 26762 15162, has_genre, 12841 15162, release_year, 26762 21206, has_genre, 12841 21206, release_year, 26762 36248, has_genre, 12841 36248, has_tags, 10045 31264, has_genre, 12841 31264, has_tags, 10045 31264, has_tags, 12841 1930, has_genre, 12841 1930, release_year, 26762 14657, has_genre, 12841 14657, release_year, 26762 17682, has_genre, 12841 17682, release_year, 26762 21393, has_tags, 10045 36306, has_genre, 12841 36306, has_tags, 12841 36306, release_year, 26762 17291, has_genre, 12841 17291, has_tags, 12841 17291, release_year, 26762 12892, has_genre, 12841 12892, has_tags, 12841 12892, release_year, 26762 14834, has_genre, 12841 14834, has_tags, 12841 14834, release_year, 26762 23408, has_genre, 12841 23408, release_year, 26762 28248, has_genre, 12841 28248, release_year, 26762 18482, has_genre, 12841 18482, has_tags, 10045 24066, has_genre, 12841 24066, has_tags, 10045 26777, has_genre, 12841 26777, release_year, 26762 10160, has_genre, 12841 10160, release_year, 26762 20580, has_genre, 12841 20580, has_tags, 10045 24721, has_genre, 12841 24721, has_tags, 10045 31138, has_genre, 12841 31138, has_tags, 10045 38592, has_genre, 12841 38592, release_year, 26762 10103, has_genre, 12841 10103, release_year, 26762 33467, has_genre, 12841 33467, release_year, 26762 25520, has_genre, 12841 25520, release_year, 26762 34736, has_genre, 12841 34736, has_tags, 10045 2448, has_genre, 12841 2448, release_year, 26762 19165, has_genre, 12841 19165, has_tags, 10045 29471, has_genre, 12841 29471, release_year, 26762 15823, has_genre, 12841 15823, release_year, 26762 735, has_genre, 12841 735, has_tags, 10045 22610, has_genre, 12841 22610, release_year, 26762 9266, has_genre, 12841 9266, has_tags, 10045 9266, has_tags, 12841 28674, has_genre, 12841 28674, has_tags, 10045 12757, has_genre, 12841 12757, release_year, 26762 10212, has_genre, 12841 10212, release_year, 26762 3016, has_genre, 12841 3016, has_tags, 12841 3016, release_year, 26762 31247, has_genre, 12841 31247, release_year, 26762 19574, has_genre, 12841 Question: For what reason are ALIEN RAIDERS, FIEND WITHOUT A FACE, and WISHFUL DRINKING associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALIEN RAIDERS", "FIEND WITHOUT A FACE", "WISHFUL DRINKING" ], "valid_edges": [ [ "A COMPLETE HISTORY OF MY SEXUAL FAILURES", "has_genre", "DOCUMENTARY" ], [ "A COMPLETE HISTORY OF MY SEXUAL FAILURES", "release_year", "2008" ], [ "A FILM UNFINISHED", "has_genre", "DOCUMENTARY" ], [ "A FILM UNFINISHED", "has_tags", "BD-R" ], [ "ALIEN RAIDERS", "release_year", "2008" ], [ "AMERICAN TEEN", "has_genre", "DOCUMENTARY" ], [ "AMERICAN TEEN", "release_year", "2008" ], [ "BETWEEN THE FOLDS", "has_genre", "DOCUMENTARY" ], [ "BETWEEN THE FOLDS", "release_year", "2008" ], [ "BURDEN OF DREAMS", "has_genre", "DOCUMENTARY" ], [ "BURDEN OF DREAMS", "has_tags", "BD-R" ], [ "CAVE OF FORGOTTEN DREAMS", "has_genre", "DOCUMENTARY" ], [ "CAVE OF FORGOTTEN DREAMS", "has_tags", "BD-R" ], [ "CAVE OF FORGOTTEN DREAMS", "has_tags", "DOCUMENTARY" ], [ "CHELSEA ON THE ROCKS", "has_genre", "DOCUMENTARY" ], [ "CHELSEA ON THE ROCKS", "release_year", "2008" ], [ "CSNY/DÉJÀ VU", "has_genre", "DOCUMENTARY" ], [ "CSNY/DÉJÀ VU", "release_year", "2008" ], [ "EXAMINED LIFE", "has_genre", "DOCUMENTARY" ], [ "EXAMINED LIFE", "release_year", "2008" ], [ "FIEND WITHOUT A FACE", "has_tags", "BD-R" ], [ "FOOD, INC.", "has_genre", "DOCUMENTARY" ], [ "FOOD, INC.", "has_tags", "DOCUMENTARY" ], [ "FOOD, INC.", "release_year", "2008" ], [ "I.O.U.S.A.", "has_genre", "DOCUMENTARY" ], [ "I.O.U.S.A.", "has_tags", "DOCUMENTARY" ], [ "I.O.U.S.A.", "release_year", "2008" ], [ "LET'S MAKE MONEY", "has_genre", "DOCUMENTARY" ], [ "LET'S MAKE MONEY", "has_tags", "DOCUMENTARY" ], [ "LET'S MAKE MONEY", "release_year", "2008" ], [ "MAN ON WIRE", "has_genre", "DOCUMENTARY" ], [ "MAN ON WIRE", "has_tags", "DOCUMENTARY" ], [ "MAN ON WIRE", "release_year", "2008" ], [ "OF TIME AND THE CITY", "has_genre", "DOCUMENTARY" ], [ "OF TIME AND THE CITY", "release_year", "2008" ], [ "PAGEANT", "has_genre", "DOCUMENTARY" ], [ "PAGEANT", "release_year", "2008" ], [ "PRIMARY", "has_genre", "DOCUMENTARY" ], [ "PRIMARY", "has_tags", "BD-R" ], [ "REEL INJUN", "has_genre", "DOCUMENTARY" ], [ "REEL INJUN", "has_tags", "BD-R" ], [ "REMBRANDT'S J'ACCUSE", "has_genre", "DOCUMENTARY" ], [ "REMBRANDT'S J'ACCUSE", "release_year", "2008" ], [ "STANLEY KUBRICK'S BOXES", "has_genre", "DOCUMENTARY" ], [ "STANLEY KUBRICK'S BOXES", "release_year", "2008" ], [ "STONEWALL UPRISING", "has_genre", "DOCUMENTARY" ], [ "STONEWALL UPRISING", "has_tags", "BD-R" ], [ "THAT'S ENTERTAINMENT! III", "has_genre", "DOCUMENTARY" ], [ "THAT'S ENTERTAINMENT! III", "has_tags", "BD-R" ], [ "THAT'S ENTERTAINMENT, PART II", "has_genre", "DOCUMENTARY" ], [ "THAT'S ENTERTAINMENT, PART II", "has_tags", "BD-R" ], [ "THE BEACHES OF AGNÈS", "has_genre", "DOCUMENTARY" ], [ "THE BEACHES OF AGNÈS", "release_year", "2008" ], [ "THE COOL SCHOOL", "has_genre", "DOCUMENTARY" ], [ "THE COOL SCHOOL", "release_year", "2008" ], [ "THE END OF AMERICA", "has_genre", "DOCUMENTARY" ], [ "THE END OF AMERICA", "release_year", "2008" ], [ "THE END OF POVERTY?", "has_genre", "DOCUMENTARY" ], [ "THE END OF POVERTY?", "release_year", "2008" ], [ "THE ENDLESS SUMMER", "has_genre", "DOCUMENTARY" ], [ "THE ENDLESS SUMMER", "has_tags", "BD-R" ], [ "THE FORGOTTEN WOMAN", "has_genre", "DOCUMENTARY" ], [ "THE FORGOTTEN WOMAN", "release_year", "2008" ], [ "THE LAST PLAY AT SHEA", "has_genre", "DOCUMENTARY" ], [ "THE LAST PLAY AT SHEA", "has_tags", "BD-R" ], [ "THE QUEEN AND I", "has_genre", "DOCUMENTARY" ], [ "THE QUEEN AND I", "release_year", "2008" ], [ "THE RECRUITER", "has_genre", "DOCUMENTARY" ], [ "THE RECRUITER", "release_year", "2008" ], [ "THE REVISIONARIES", "has_genre", "DOCUMENTARY" ], [ "THE REVISIONARIES", "has_tags", "BD-R" ], [ "THE SOVIET STORY", "has_genre", "DOCUMENTARY" ], [ "THE SOVIET STORY", "release_year", "2008" ], [ "THE TIMES OF HARVEY MILK", "has_genre", "DOCUMENTARY" ], [ "THE TIMES OF HARVEY MILK", "has_tags", "BD-R" ], [ "THE TIMES OF HARVEY MILK", "has_tags", "DOCUMENTARY" ], [ "TREK NATION", "has_genre", "DOCUMENTARY" ], [ "TREK NATION", "has_tags", "BD-R" ], [ "TYSON", "has_genre", "DOCUMENTARY" ], [ "TYSON", "release_year", "2008" ], [ "UNMISTAKEN CHILD", "has_genre", "DOCUMENTARY" ], [ "UNMISTAKEN CHILD", "release_year", "2008" ], [ "WALTZ WITH BASHIR", "has_genre", "DOCUMENTARY" ], [ "WALTZ WITH BASHIR", "has_tags", "DOCUMENTARY" ], [ "WALTZ WITH BASHIR", "release_year", "2008" ], [ "WHERE IN THE WORLD IS OSAMA BIN LADEN?", "has_genre", "DOCUMENTARY" ], [ "WHERE IN THE WORLD IS OSAMA BIN LADEN?", "release_year", "2008" ], [ "WISHFUL DRINKING", "has_genre", "DOCUMENTARY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 35845, 2006 39257, BARNYARD 19500, FIRST SNOW 6012, FRENCH 7930, GUY PEARCE 10034, L.A. CONFIDENTIAL 8530, MARTIN LASALLE 29071, MEMENTO 913, NOTHING TO LOSE 29693, PICKPOCKET 13081, R 18757, REVENGE 13567, STEVE OEDEKERK 16219, STORY 19351, THE COUNT OF MONTE CRISTO src, edge_attr, dst 39257, directed_by, 13567 39257, release_year, 35845 39257, written_by, 13567 19500, release_year, 35845 19500, starred_actors, 7930 10034, has_tags, 7930 10034, has_tags, 13081 10034, has_tags, 16219 10034, release_year, 14259 10034, starred_actors, 7930 29071, has_tags, 7930 29071, has_tags, 13081 29071, has_tags, 18757 29071, has_tags, 16219 29071, starred_actors, 7930 913, directed_by, 13567 913, has_tags, 13567 913, release_year, 14259 913, written_by, 13567 29693, in_language, 6012 29693, starred_actors, 8530 19351, has_tags, 7930 19351, has_tags, 18757 19351, has_tags, 16219 19351, in_language, 6012 19351, starred_actors, 7930 Question: How are GUY PEARCE, MARTIN LASALLE, and STEVE OEDEKERK related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GUY PEARCE", "MARTIN LASALLE", "STEVE OEDEKERK" ], "valid_edges": [ [ "BARNYARD", "directed_by", "STEVE OEDEKERK" ], [ "BARNYARD", "release_year", "2006" ], [ "BARNYARD", "written_by", "STEVE OEDEKERK" ], [ "FIRST SNOW", "release_year", "2006" ], [ "FIRST SNOW", "starred_actors", "GUY PEARCE" ], [ "L.A. CONFIDENTIAL", "has_tags", "GUY PEARCE" ], [ "L.A. CONFIDENTIAL", "has_tags", "R" ], [ "L.A. CONFIDENTIAL", "has_tags", "STORY" ], [ "L.A. CONFIDENTIAL", "release_year", "1997" ], [ "L.A. CONFIDENTIAL", "starred_actors", "GUY PEARCE" ], [ "MEMENTO", "has_tags", "GUY PEARCE" ], [ "MEMENTO", "has_tags", "R" ], [ "MEMENTO", "has_tags", "REVENGE" ], [ "MEMENTO", "has_tags", "STORY" ], [ "MEMENTO", "starred_actors", "GUY PEARCE" ], [ "NOTHING TO LOSE", "directed_by", "STEVE OEDEKERK" ], [ "NOTHING TO LOSE", "has_tags", "STEVE OEDEKERK" ], [ "NOTHING TO LOSE", "release_year", "1997" ], [ "NOTHING TO LOSE", "written_by", "STEVE OEDEKERK" ], [ "PICKPOCKET", "in_language", "FRENCH" ], [ "PICKPOCKET", "starred_actors", "MARTIN LASALLE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "GUY PEARCE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "REVENGE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "STORY" ], [ "THE COUNT OF MONTE CRISTO", "in_language", "FRENCH" ], [ "THE COUNT OF MONTE CRISTO", "starred_actors", "GUY PEARCE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36522, 1934 19407, 8½ 38636, A BRIEF VACATION 37315, A BRONX TALE 16090, A FIVE STAR LIFE 21572, ACCATTONE 21413, AMARCORD 34352, AN AVERAGE LITTLE MAN 39876, ANNIE 6309, BABY TAKE A BOW 12954, BEAR'S KISS 27226, BORN TO BE BAD 35916, BREAD AND CHOCOLATE 34243, BRIGHT EYES 13164, BROADWAY 8442, CABIRIA 33711, CAESAR MUST DIE 5140, CHRIS PRATT 33774, CINEMA PARADISO 19510, CLEOPATRA 30463, COMEDY 37882, DAYS AND CLOUDS 30126, DEATH IN VENICE 29309, DELIVERY MAN 31550, DILLINGER IS DEAD 36212, DRAMA 37267, DREAMGIRLS 5924, EROS 31799, EVA 23387, EVERYBODY'S FINE 23071, EVERYBODY'S WOMAN 409, FARINELLI 26507, FIORILE 32706, FIRST LOVE 15161, FORSAKING ALL OTHERS 34091, FROM THE CLOUDS TO THE RESISTANCE 15135, GINGER AND FRED 33338, I GIORNI CONTATI 17344, I VITELLONI 37734, IDENTIFICATION OF A WOMAN 33242, IL GRIDO 5921, IMITATION OF LIFE 38662, IN THE NAME OF THE LAW 31900, INCANTATO 24167, INFERNO 37110, INVESTIGATION OF A CITIZEN ABOVE SUSPICION 16200, ITALIAN 20654, JAMIE FOXX 15012, JARHEAD 38160, JOURNEY TO ITALY 7754, JULIA AND JULIA 18699, JULIET OF THE SPIRITS 38326, L'ECLISSE 25104, LA DOLCE VITA 32844, LA NOTTE 20913, LA STRADA 19966, LE PLAISIR 14601, LES MISÉRABLES 24419, LIFE IS BEAUTIFUL 28130, LITTLE MISS MARKER 34628, MALÈNA 4193, MANHATTAN MELODRAMA 32293, MAX OPHÜLS 34611, ME AND YOU 34359, MELISSA P. 19216, MID-AUGUST LUNCH 7050, MONEYBALL 22845, MUSIC 24593, MUSICAL 32993, MY BROTHER IS AN ONLY CHILD 39242, NOW AND FOREVER 4435, OF HUMAN BONDAGE 17528, ONCE UPON A TIME IN AMERICA 32186, ONE MAN UP 9036, PAISAN 1197, PASSION OF LOVE 3781, QUO VADIS, BABY? 35746, REALITY 21719, ROMANZO CRIMINALE 29931, ROME, OPEN CITY 35586, SAHARA 40001, SCENT OF A WOMAN 26687, SENSO 25009, SHUN LI AND THE POET 15777, STORY OF A LOVE AFFAIR 15312, STRANGER ON THE PROWL 37032, STROMBOLI 38027, SUNFLOWER 26790, SWEPT AWAY 23395, TERRAFERMA 36088, THAT NIGHT IN VARENNES 27310, THE AGE OF INNOCENCE 4157, THE BEST MAN 36932, THE CAIMAN 14219, THE CHILDREN ARE WATCHING US 39333, THE CLAIRVOYANT 2356, THE CONFORMIST 19351, THE COUNT OF MONTE CRISTO 10860, THE DAMNED 32637, THE EARRINGS OF MADAME DE... 27253, THE FIRST BEAUTIFUL THING 6723, THE FLOWER IN HIS MOUTH 11668, THE GOSPEL ACCORDING TO ST. MATTHEW 35165, THE ITALIAN 8435, THE KEYS TO THE HOUSE 28107, THE LAST KISS 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 19600, THE MISSING STAR 18105, THE MOMENT OF TRUTH 15155, THE NIGHT OF THE SHOOTING STARS 12999, THE ORGANIZER 3967, THE OVERCOAT 23084, THE PAINTED VEIL 242, THE PRIVATE LIFE OF DON JUAN 7592, THE RECKLESS MOMENT 18274, THE ROSE TATTOO 40069, THE SCARLET EMPRESS 7725, THE SOLITUDE OF PRIME NUMBERS 19294, THE SOLOIST 20293, THE WEDDING DIRECTOR 34649, THE WONDERS 19429, TONI 32079, ULYSSES 17093, UNFAIR COMPETITION 31942, VARIETY LIGHTS 28264, VESNA VA VELOCE 27749, WALKING, WALKING 4325, WE ALL LOVED EACH OTHER SO MUCH 35511, WE HAVE A POPE src, edge_attr, dst 19407, has_genre, 36212 19407, in_language, 16200 38636, has_genre, 36212 38636, in_language, 16200 37315, has_genre, 36212 37315, has_tags, 16200 37315, in_language, 16200 16090, has_genre, 36212 16090, in_language, 16200 21572, has_genre, 36212 21572, in_language, 16200 21413, has_genre, 36212 21413, in_language, 16200 34352, has_genre, 36212 34352, in_language, 16200 39876, has_genre, 30463 39876, has_genre, 36212 39876, has_tags, 13164 39876, has_tags, 24593 39876, starred_actors, 20654 6309, has_genre, 36212 6309, release_year, 36522 12954, has_genre, 36212 12954, in_language, 16200 27226, has_genre, 36212 27226, release_year, 36522 35916, has_genre, 36212 35916, in_language, 16200 34243, has_genre, 36212 34243, release_year, 36522 8442, has_genre, 36212 8442, in_language, 16200 33711, has_genre, 36212 33711, in_language, 16200 33774, has_genre, 36212 33774, has_tags, 16200 33774, in_language, 16200 19510, has_genre, 36212 19510, release_year, 36522 37882, has_genre, 36212 37882, in_language, 16200 30126, has_genre, 36212 30126, in_language, 16200 29309, has_genre, 30463 29309, has_genre, 36212 29309, has_tags, 36212 29309, starred_actors, 5140 31550, has_genre, 36212 31550, in_language, 16200 37267, has_genre, 36212 37267, has_genre, 22845 37267, has_genre, 24593 37267, has_tags, 13164 37267, has_tags, 20654 37267, has_tags, 24593 37267, starred_actors, 20654 5924, has_genre, 36212 5924, in_language, 16200 31799, has_genre, 36212 31799, in_language, 16200 23387, has_genre, 36212 23387, in_language, 16200 23071, directed_by, 32293 23071, has_genre, 36212 23071, in_language, 16200 23071, release_year, 36522 23071, written_by, 32293 409, has_genre, 36212 409, in_language, 16200 26507, has_genre, 36212 26507, in_language, 16200 32706, has_genre, 36212 32706, in_language, 16200 15161, has_genre, 36212 15161, release_year, 36522 34091, has_genre, 36212 34091, in_language, 16200 15135, has_genre, 36212 15135, in_language, 16200 33338, has_genre, 36212 33338, in_language, 16200 17344, has_genre, 36212 17344, has_tags, 16200 17344, in_language, 16200 37734, has_genre, 36212 37734, in_language, 16200 33242, has_genre, 36212 33242, in_language, 16200 5921, has_genre, 36212 5921, release_year, 36522 38662, has_genre, 36212 38662, in_language, 16200 31900, has_genre, 36212 31900, in_language, 16200 24167, has_genre, 36212 24167, in_language, 16200 37110, has_genre, 36212 37110, in_language, 16200 15012, has_genre, 36212 15012, has_tags, 20654 15012, starred_actors, 20654 38160, has_genre, 36212 38160, in_language, 16200 7754, has_genre, 36212 7754, in_language, 16200 18699, has_genre, 36212 18699, has_tags, 16200 18699, in_language, 16200 38326, has_genre, 36212 38326, in_language, 16200 25104, has_genre, 36212 25104, has_tags, 16200 25104, in_language, 16200 32844, has_genre, 36212 32844, in_language, 16200 20913, has_genre, 36212 20913, has_tags, 16200 20913, in_language, 16200 19966, directed_by, 32293 19966, has_genre, 36212 19966, has_tags, 32293 19966, written_by, 32293 14601, has_genre, 36212 14601, release_year, 36522 24419, has_genre, 36212 24419, has_tags, 16200 24419, in_language, 16200 28130, has_genre, 36212 28130, release_year, 36522 34628, has_genre, 36212 34628, has_tags, 36212 34628, has_tags, 16200 34628, in_language, 16200 4193, has_genre, 36212 4193, release_year, 36522 34611, has_genre, 36212 34611, in_language, 16200 34359, has_genre, 36212 34359, in_language, 16200 19216, has_genre, 36212 19216, in_language, 16200 7050, has_genre, 36212 7050, has_tags, 5140 7050, has_tags, 36212 32993, has_genre, 36212 32993, in_language, 16200 39242, has_genre, 36212 39242, release_year, 36522 4435, has_genre, 36212 4435, release_year, 36522 17528, has_genre, 36212 17528, in_language, 16200 32186, has_genre, 36212 32186, in_language, 16200 9036, has_genre, 36212 9036, in_language, 16200 1197, has_genre, 36212 1197, in_language, 16200 3781, has_genre, 36212 3781, in_language, 16200 35746, has_genre, 36212 35746, in_language, 16200 21719, has_genre, 36212 21719, in_language, 16200 29931, has_genre, 36212 29931, in_language, 16200 35586, has_genre, 36212 35586, in_language, 16200 40001, has_genre, 36212 40001, has_tags, 36212 40001, in_language, 16200 26687, has_genre, 36212 26687, in_language, 16200 25009, has_genre, 36212 25009, in_language, 16200 15777, has_genre, 36212 15777, in_language, 16200 15312, has_genre, 36212 15312, in_language, 16200 37032, has_genre, 36212 37032, in_language, 16200 38027, has_genre, 36212 38027, in_language, 16200 26790, has_genre, 36212 26790, in_language, 16200 23395, has_genre, 36212 23395, in_language, 16200 36088, has_genre, 36212 36088, in_language, 16200 27310, has_genre, 36212 27310, release_year, 36522 4157, has_genre, 36212 4157, in_language, 16200 36932, has_genre, 36212 36932, in_language, 16200 14219, has_genre, 36212 14219, in_language, 16200 39333, has_genre, 36212 39333, release_year, 36522 2356, has_genre, 36212 2356, in_language, 16200 19351, has_genre, 36212 19351, release_year, 36522 10860, has_genre, 36212 10860, in_language, 16200 32637, directed_by, 32293 32637, has_genre, 36212 32637, has_tags, 32293 32637, written_by, 32293 27253, has_genre, 36212 27253, in_language, 16200 6723, has_genre, 36212 6723, in_language, 16200 11668, has_genre, 36212 11668, in_language, 16200 35165, has_genre, 36212 35165, in_language, 16200 8435, has_genre, 36212 8435, in_language, 16200 28107, has_genre, 36212 28107, in_language, 16200 28217, has_genre, 36212 28217, in_language, 16200 19600, has_genre, 36212 19600, in_language, 16200 18105, has_genre, 36212 18105, in_language, 16200 15155, has_genre, 36212 15155, in_language, 16200 12999, has_genre, 36212 12999, in_language, 16200 3967, has_genre, 36212 3967, in_language, 16200 23084, has_genre, 36212 23084, release_year, 36522 242, has_genre, 36212 242, release_year, 36522 7592, directed_by, 32293 7592, has_genre, 36212 18274, has_genre, 36212 18274, in_language, 16200 40069, has_genre, 36212 40069, release_year, 36522 7725, has_genre, 36212 7725, in_language, 16200 19294, has_genre, 36212 19294, has_genre, 22845 19294, has_tags, 20654 19294, starred_actors, 20654 20293, has_genre, 36212 20293, in_language, 16200 34649, has_genre, 36212 34649, in_language, 16200 19429, has_genre, 36212 19429, in_language, 16200 32079, has_genre, 36212 32079, in_language, 16200 17093, has_genre, 36212 17093, in_language, 16200 31942, has_genre, 36212 31942, in_language, 16200 28264, has_genre, 36212 28264, has_tags, 36212 28264, has_tags, 16200 28264, in_language, 16200 27749, has_genre, 36212 27749, in_language, 16200 4325, has_genre, 36212 4325, in_language, 16200 35511, has_genre, 36212 35511, has_tags, 16200 35511, in_language, 16200 Question: In what context are CHRIS PRATT, EVERYBODY'S WOMAN, and JAMIE FOXX connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHRIS PRATT", "EVERYBODY'S WOMAN", "JAMIE FOXX" ], "valid_edges": [ [ "8½", "has_genre", "DRAMA" ], [ "8½", "in_language", "ITALIAN" ], [ "A BRIEF VACATION", "has_genre", "DRAMA" ], [ "A BRIEF VACATION", "in_language", "ITALIAN" ], [ "A BRONX TALE", "has_genre", "DRAMA" ], [ "A BRONX TALE", "has_tags", "ITALIAN" ], [ "A BRONX TALE", "in_language", "ITALIAN" ], [ "A FIVE STAR LIFE", "has_genre", "DRAMA" ], [ "A FIVE STAR LIFE", "in_language", "ITALIAN" ], [ "ACCATTONE", "has_genre", "DRAMA" ], [ "ACCATTONE", "in_language", "ITALIAN" ], [ "AMARCORD", "has_genre", "DRAMA" ], [ "AMARCORD", "in_language", "ITALIAN" ], [ "AN AVERAGE LITTLE MAN", "has_genre", "DRAMA" ], [ "AN AVERAGE LITTLE MAN", "in_language", "ITALIAN" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "has_tags", "BROADWAY" ], [ "ANNIE", "has_tags", "MUSICAL" ], [ "ANNIE", "starred_actors", "JAMIE FOXX" ], [ "BABY TAKE A BOW", "has_genre", "DRAMA" ], [ "BABY TAKE A BOW", "release_year", "1934" ], [ "BEAR'S KISS", "has_genre", "DRAMA" ], [ "BEAR'S KISS", "in_language", "ITALIAN" ], [ "BORN TO BE BAD", "has_genre", "DRAMA" ], [ "BORN TO BE BAD", "release_year", "1934" ], [ "BREAD AND CHOCOLATE", "has_genre", "DRAMA" ], [ "BREAD AND CHOCOLATE", "in_language", "ITALIAN" ], [ "BRIGHT EYES", "has_genre", "DRAMA" ], [ "BRIGHT EYES", "release_year", "1934" ], [ "CABIRIA", "has_genre", "DRAMA" ], [ "CABIRIA", "in_language", "ITALIAN" ], [ "CAESAR MUST DIE", "has_genre", "DRAMA" ], [ "CAESAR MUST DIE", "in_language", "ITALIAN" ], [ "CINEMA PARADISO", "has_genre", "DRAMA" ], [ "CINEMA PARADISO", "has_tags", "ITALIAN" ], [ "CINEMA PARADISO", "in_language", "ITALIAN" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "1934" ], [ "DAYS AND CLOUDS", "has_genre", "DRAMA" ], [ "DAYS AND CLOUDS", "in_language", "ITALIAN" ], [ "DEATH IN VENICE", "has_genre", "DRAMA" ], [ "DEATH IN VENICE", "in_language", "ITALIAN" ], [ "DELIVERY MAN", "has_genre", "COMEDY" ], [ "DELIVERY MAN", "has_genre", "DRAMA" ], [ "DELIVERY MAN", "has_tags", "DRAMA" ], [ "DELIVERY MAN", "starred_actors", "CHRIS PRATT" ], [ "DILLINGER IS DEAD", "has_genre", "DRAMA" ], [ "DILLINGER IS DEAD", "in_language", "ITALIAN" ], [ "DREAMGIRLS", "has_genre", "DRAMA" ], [ "DREAMGIRLS", "has_genre", "MUSIC" ], [ "DREAMGIRLS", "has_genre", "MUSICAL" ], [ "DREAMGIRLS", "has_tags", "BROADWAY" ], [ "DREAMGIRLS", "has_tags", "JAMIE FOXX" ], [ "DREAMGIRLS", "has_tags", "MUSICAL" ], [ "DREAMGIRLS", "starred_actors", "JAMIE FOXX" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "in_language", "ITALIAN" ], [ "EVA", "has_genre", "DRAMA" ], [ "EVA", "in_language", "ITALIAN" ], [ "EVERYBODY'S FINE", "has_genre", "DRAMA" ], [ "EVERYBODY'S FINE", "in_language", "ITALIAN" ], [ "EVERYBODY'S WOMAN", "directed_by", "MAX OPHÜLS" ], [ "EVERYBODY'S WOMAN", "has_genre", "DRAMA" ], [ "EVERYBODY'S WOMAN", "in_language", "ITALIAN" ], [ "EVERYBODY'S WOMAN", "release_year", "1934" ], [ "EVERYBODY'S WOMAN", "written_by", "MAX OPHÜLS" ], [ "FARINELLI", "has_genre", "DRAMA" ], [ "FARINELLI", "in_language", "ITALIAN" ], [ "FIORILE", "has_genre", "DRAMA" ], [ "FIORILE", "in_language", "ITALIAN" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "in_language", "ITALIAN" ], [ "FORSAKING ALL OTHERS", "has_genre", "DRAMA" ], [ "FORSAKING ALL OTHERS", "release_year", "1934" ], [ "FROM THE CLOUDS TO THE RESISTANCE", "has_genre", "DRAMA" ], [ "FROM THE CLOUDS TO THE RESISTANCE", "in_language", "ITALIAN" ], [ "GINGER AND FRED", "has_genre", "DRAMA" ], [ "GINGER AND FRED", "in_language", "ITALIAN" ], [ "I GIORNI CONTATI", "has_genre", "DRAMA" ], [ "I GIORNI CONTATI", "in_language", "ITALIAN" ], [ "I VITELLONI", "has_genre", "DRAMA" ], [ "I VITELLONI", "has_tags", "ITALIAN" ], [ "I VITELLONI", "in_language", "ITALIAN" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "in_language", "ITALIAN" ], [ "IL GRIDO", "has_genre", "DRAMA" ], [ "IL GRIDO", "in_language", "ITALIAN" ], [ "IMITATION OF LIFE", "has_genre", "DRAMA" ], [ "IMITATION OF LIFE", "release_year", "1934" ], [ "IN THE NAME OF THE LAW", "has_genre", "DRAMA" ], [ "IN THE NAME OF THE LAW", "in_language", "ITALIAN" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "in_language", "ITALIAN" ], [ "INFERNO", "has_genre", "DRAMA" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "INVESTIGATION OF A CITIZEN ABOVE SUSPICION", "has_genre", "DRAMA" ], [ "INVESTIGATION OF A CITIZEN ABOVE SUSPICION", "in_language", "ITALIAN" ], [ "JARHEAD", "has_genre", "DRAMA" ], [ "JARHEAD", "has_tags", "JAMIE FOXX" ], [ "JARHEAD", "starred_actors", "JAMIE FOXX" ], [ "JOURNEY TO ITALY", "has_genre", "DRAMA" ], [ "JOURNEY TO ITALY", "in_language", "ITALIAN" ], [ "JULIA AND JULIA", "has_genre", "DRAMA" ], [ "JULIA AND JULIA", "in_language", "ITALIAN" ], [ "JULIET OF THE SPIRITS", "has_genre", "DRAMA" ], [ "JULIET OF THE SPIRITS", "has_tags", "ITALIAN" ], [ "JULIET OF THE SPIRITS", "in_language", "ITALIAN" ], [ "L'ECLISSE", "has_genre", "DRAMA" ], [ "L'ECLISSE", "in_language", "ITALIAN" ], [ "LA DOLCE VITA", "has_genre", "DRAMA" ], [ "LA DOLCE VITA", "has_tags", "ITALIAN" ], [ "LA DOLCE VITA", "in_language", "ITALIAN" ], [ "LA NOTTE", "has_genre", "DRAMA" ], [ "LA NOTTE", "in_language", "ITALIAN" ], [ "LA STRADA", "has_genre", "DRAMA" ], [ "LA STRADA", "has_tags", "ITALIAN" ], [ "LA STRADA", "in_language", "ITALIAN" ], [ "LE PLAISIR", "directed_by", "MAX OPHÜLS" ], [ "LE PLAISIR", "has_genre", "DRAMA" ], [ "LE PLAISIR", "has_tags", "MAX OPHÜLS" ], [ "LE PLAISIR", "written_by", "MAX OPHÜLS" ], [ "LES MISÉRABLES", "has_genre", "DRAMA" ], [ "LES MISÉRABLES", "release_year", "1934" ], [ "LIFE IS BEAUTIFUL", "has_genre", "DRAMA" ], [ "LIFE IS BEAUTIFUL", "has_tags", "ITALIAN" ], [ "LIFE IS BEAUTIFUL", "in_language", "ITALIAN" ], [ "LITTLE MISS MARKER", "has_genre", "DRAMA" ], [ "LITTLE MISS MARKER", "release_year", "1934" ], [ "MALÈNA", "has_genre", "DRAMA" ], [ "MALÈNA", "has_tags", "DRAMA" ], [ "MALÈNA", "has_tags", "ITALIAN" ], [ "MALÈNA", "in_language", "ITALIAN" ], [ "MANHATTAN MELODRAMA", "has_genre", "DRAMA" ], [ "MANHATTAN MELODRAMA", "release_year", "1934" ], [ "ME AND YOU", "has_genre", "DRAMA" ], [ "ME AND YOU", "in_language", "ITALIAN" ], [ "MELISSA P.", "has_genre", "DRAMA" ], [ "MELISSA P.", "in_language", "ITALIAN" ], [ "MID-AUGUST LUNCH", "has_genre", "DRAMA" ], [ "MID-AUGUST LUNCH", "in_language", "ITALIAN" ], [ "MONEYBALL", "has_genre", "DRAMA" ], [ "MONEYBALL", "has_tags", "CHRIS PRATT" ], [ "MONEYBALL", "has_tags", "DRAMA" ], [ "MY BROTHER IS AN ONLY CHILD", "has_genre", "DRAMA" ], [ "MY BROTHER IS AN ONLY CHILD", "in_language", "ITALIAN" ], [ "NOW AND FOREVER", "has_genre", "DRAMA" ], [ "NOW AND FOREVER", "release_year", "1934" ], [ "OF HUMAN BONDAGE", "has_genre", "DRAMA" ], [ "OF HUMAN BONDAGE", "release_year", "1934" ], [ "ONCE UPON A TIME IN AMERICA", "has_genre", "DRAMA" ], [ "ONCE UPON A TIME IN AMERICA", "in_language", "ITALIAN" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "in_language", "ITALIAN" ], [ "PAISAN", "has_genre", "DRAMA" ], [ "PAISAN", "in_language", "ITALIAN" ], [ "PASSION OF LOVE", "has_genre", "DRAMA" ], [ "PASSION OF LOVE", "in_language", "ITALIAN" ], [ "QUO VADIS, BABY?", "has_genre", "DRAMA" ], [ "QUO VADIS, BABY?", "in_language", "ITALIAN" ], [ "REALITY", "has_genre", "DRAMA" ], [ "REALITY", "in_language", "ITALIAN" ], [ "ROMANZO CRIMINALE", "has_genre", "DRAMA" ], [ "ROMANZO CRIMINALE", "in_language", "ITALIAN" ], [ "ROME, OPEN CITY", "has_genre", "DRAMA" ], [ "ROME, OPEN CITY", "in_language", "ITALIAN" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "in_language", "ITALIAN" ], [ "SCENT OF A WOMAN", "has_genre", "DRAMA" ], [ "SCENT OF A WOMAN", "has_tags", "DRAMA" ], [ "SCENT OF A WOMAN", "in_language", "ITALIAN" ], [ "SENSO", "has_genre", "DRAMA" ], [ "SENSO", "in_language", "ITALIAN" ], [ "SHUN LI AND THE POET", "has_genre", "DRAMA" ], [ "SHUN LI AND THE POET", "in_language", "ITALIAN" ], [ "STORY OF A LOVE AFFAIR", "has_genre", "DRAMA" ], [ "STORY OF A LOVE AFFAIR", "in_language", "ITALIAN" ], [ "STRANGER ON THE PROWL", "has_genre", "DRAMA" ], [ "STRANGER ON THE PROWL", "in_language", "ITALIAN" ], [ "STROMBOLI", "has_genre", "DRAMA" ], [ "STROMBOLI", "in_language", "ITALIAN" ], [ "SUNFLOWER", "has_genre", "DRAMA" ], [ "SUNFLOWER", "in_language", "ITALIAN" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "in_language", "ITALIAN" ], [ "TERRAFERMA", "has_genre", "DRAMA" ], [ "TERRAFERMA", "in_language", "ITALIAN" ], [ "THAT NIGHT IN VARENNES", "has_genre", "DRAMA" ], [ "THAT NIGHT IN VARENNES", "in_language", "ITALIAN" ], [ "THE AGE OF INNOCENCE", "has_genre", "DRAMA" ], [ "THE AGE OF INNOCENCE", "release_year", "1934" ], [ "THE BEST MAN", "has_genre", "DRAMA" ], [ "THE BEST MAN", "in_language", "ITALIAN" ], [ "THE CAIMAN", "has_genre", "DRAMA" ], [ "THE CAIMAN", "in_language", "ITALIAN" ], [ "THE CHILDREN ARE WATCHING US", "has_genre", "DRAMA" ], [ "THE CHILDREN ARE WATCHING US", "in_language", "ITALIAN" ], [ "THE CLAIRVOYANT", "has_genre", "DRAMA" ], [ "THE CLAIRVOYANT", "release_year", "1934" ], [ "THE CONFORMIST", "has_genre", "DRAMA" ], [ "THE CONFORMIST", "in_language", "ITALIAN" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "1934" ], [ "THE DAMNED", "has_genre", "DRAMA" ], [ "THE DAMNED", "in_language", "ITALIAN" ], [ "THE EARRINGS OF MADAME DE...", "directed_by", "MAX OPHÜLS" ], [ "THE EARRINGS OF MADAME DE...", "has_genre", "DRAMA" ], [ "THE EARRINGS OF MADAME DE...", "has_tags", "MAX OPHÜLS" ], [ "THE EARRINGS OF MADAME DE...", "written_by", "MAX OPHÜLS" ], [ "THE FIRST BEAUTIFUL THING", "has_genre", "DRAMA" ], [ "THE FIRST BEAUTIFUL THING", "in_language", "ITALIAN" ], [ "THE FLOWER IN HIS MOUTH", "has_genre", "DRAMA" ], [ "THE FLOWER IN HIS MOUTH", "in_language", "ITALIAN" ], [ "THE GOSPEL ACCORDING TO ST. MATTHEW", "has_genre", "DRAMA" ], [ "THE GOSPEL ACCORDING TO ST. MATTHEW", "in_language", "ITALIAN" ], [ "THE ITALIAN", "has_genre", "DRAMA" ], [ "THE ITALIAN", "in_language", "ITALIAN" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "in_language", "ITALIAN" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "in_language", "ITALIAN" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "in_language", "ITALIAN" ], [ "THE MISSING STAR", "has_genre", "DRAMA" ], [ "THE MISSING STAR", "in_language", "ITALIAN" ], [ "THE MOMENT OF TRUTH", "has_genre", "DRAMA" ], [ "THE MOMENT OF TRUTH", "in_language", "ITALIAN" ], [ "THE NIGHT OF THE SHOOTING STARS", "has_genre", "DRAMA" ], [ "THE NIGHT OF THE SHOOTING STARS", "in_language", "ITALIAN" ], [ "THE ORGANIZER", "has_genre", "DRAMA" ], [ "THE ORGANIZER", "in_language", "ITALIAN" ], [ "THE OVERCOAT", "has_genre", "DRAMA" ], [ "THE OVERCOAT", "in_language", "ITALIAN" ], [ "THE PAINTED VEIL", "has_genre", "DRAMA" ], [ "THE PAINTED VEIL", "release_year", "1934" ], [ "THE PRIVATE LIFE OF DON JUAN", "has_genre", "DRAMA" ], [ "THE PRIVATE LIFE OF DON JUAN", "release_year", "1934" ], [ "THE RECKLESS MOMENT", "directed_by", "MAX OPHÜLS" ], [ "THE RECKLESS MOMENT", "has_genre", "DRAMA" ], [ "THE ROSE TATTOO", "has_genre", "DRAMA" ], [ "THE ROSE TATTOO", "in_language", "ITALIAN" ], [ "THE SCARLET EMPRESS", "has_genre", "DRAMA" ], [ "THE SCARLET EMPRESS", "release_year", "1934" ], [ "THE SOLITUDE OF PRIME NUMBERS", "has_genre", "DRAMA" ], [ "THE SOLITUDE OF PRIME NUMBERS", "in_language", "ITALIAN" ], [ "THE SOLOIST", "has_genre", "DRAMA" ], [ "THE SOLOIST", "has_genre", "MUSIC" ], [ "THE SOLOIST", "has_tags", "JAMIE FOXX" ], [ "THE SOLOIST", "starred_actors", "JAMIE FOXX" ], [ "THE WEDDING DIRECTOR", "has_genre", "DRAMA" ], [ "THE WEDDING DIRECTOR", "in_language", "ITALIAN" ], [ "THE WONDERS", "has_genre", "DRAMA" ], [ "THE WONDERS", "in_language", "ITALIAN" ], [ "TONI", "has_genre", "DRAMA" ], [ "TONI", "in_language", "ITALIAN" ], [ "ULYSSES", "has_genre", "DRAMA" ], [ "ULYSSES", "in_language", "ITALIAN" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "in_language", "ITALIAN" ], [ "VARIETY LIGHTS", "has_genre", "DRAMA" ], [ "VARIETY LIGHTS", "in_language", "ITALIAN" ], [ "VESNA VA VELOCE", "has_genre", "DRAMA" ], [ "VESNA VA VELOCE", "has_tags", "DRAMA" ], [ "VESNA VA VELOCE", "has_tags", "ITALIAN" ], [ "VESNA VA VELOCE", "in_language", "ITALIAN" ], [ "WALKING, WALKING", "has_genre", "DRAMA" ], [ "WALKING, WALKING", "in_language", "ITALIAN" ], [ "WE ALL LOVED EACH OTHER SO MUCH", "has_genre", "DRAMA" ], [ "WE ALL LOVED EACH OTHER SO MUCH", "in_language", "ITALIAN" ], [ "WE HAVE A POPE", "has_genre", "DRAMA" ], [ "WE HAVE A POPE", "has_tags", "ITALIAN" ], [ "WE HAVE A POPE", "in_language", "ITALIAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 14062, ALL THE BOYS LOVE MANDY LANE 6012, FRENCH 33456, HE LOVES ME... HE LOVES ME NOT 5870, HORROR 6894, JACK HANNAH 25761, JONATHAN LEVINE 8379, ROMANCE 6603, SEX IS COMEDY 19351, THE COUNT OF MONTE CRISTO 17409, TRICK OR TREAT 32933, WARM BODIES src, edge_attr, dst 14062, directed_by, 25761 14062, has_genre, 5870 14062, has_tags, 5870 33456, has_tags, 6012 33456, in_language, 6012 33456, release_year, 35935 8379, in_language, 6012 6603, in_language, 6012 6603, release_year, 35935 19351, in_language, 6012 19351, release_year, 35935 17409, directed_by, 6894 17409, has_genre, 5870 32933, directed_by, 25761 32933, has_genre, 8379 32933, has_tags, 25761 32933, has_tags, 8379 32933, written_by, 25761 Question: How are HE LOVES ME... HE LOVES ME NOT, JACK HANNAH, and JONATHAN LEVINE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HE LOVES ME... HE LOVES ME NOT", "JACK HANNAH", "JONATHAN LEVINE" ], "valid_edges": [ [ "ALL THE BOYS LOVE MANDY LANE", "directed_by", "JONATHAN LEVINE" ], [ "ALL THE BOYS LOVE MANDY LANE", "has_genre", "HORROR" ], [ "ALL THE BOYS LOVE MANDY LANE", "has_tags", "HORROR" ], [ "HE LOVES ME... HE LOVES ME NOT", "has_tags", "FRENCH" ], [ "HE LOVES ME... HE LOVES ME NOT", "in_language", "FRENCH" ], [ "HE LOVES ME... HE LOVES ME NOT", "release_year", "2002" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "THE COUNT OF MONTE CRISTO", "in_language", "FRENCH" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "2002" ], [ "TRICK OR TREAT", "directed_by", "JACK HANNAH" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "WARM BODIES", "directed_by", "JONATHAN LEVINE" ], [ "WARM BODIES", "has_genre", "ROMANCE" ], [ "WARM BODIES", "has_tags", "JONATHAN LEVINE" ], [ "WARM BODIES", "has_tags", "ROMANCE" ], [ "WARM BODIES", "written_by", "JONATHAN LEVINE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21950, 'R XMAS 2452, 13 ASSASSINS 13408, 2001 37484, 2004 33218, ABEL FERRARA 29800, ACE ATTORNEY 35189, ALL ABOUT LILY CHOU-CHOU 18598, APPLESEED 7908, AUDITION 2182, BLOOD AND BONES 5856, BLUE SPRING 6395, BLUES HARP 231, CASSHERN 38311, CHAOS 1930, CHELSEA ON THE ROCKS 26635, CROWS ZERO 5113, DEAD LEAVES 36380, DEAD OR ALIVE 5951, ELECTRIC DRAGON 80.000 V 12298, GOZU 2982, HALLOWEENTOWN HIGH 13409, HANA AND ALICE 12087, HOWL'S MOVING CASTLE 22330, HUSH! 4215, ICHI THE KILLER 13174, INFECTION 8164, IZO 36874, JAPANESE 15150, KAMIKAZE GIRLS 7892, LESSON OF THE EVIL 35621, MILLENNIUM ACTRESS 30532, MIND GAME 25709, NOBODY KNOWS 36326, ONE MISSED CALL 36532, OVER YOUR DEAD BODY 234, PEARL HARBOR 29748, PISTOL OPERA 13237, PULSE 29919, RAINY DOG 6260, SPIRITED AWAY 31842, SURVIVE STYLE 5+ 4651, TAKASHI MIIKE 38882, THE BIRD PEOPLE IN CHINA 23910, THE CITY OF LOST SOULS 24493, THE FUNERAL 11297, THE GREAT YOKAI WAR 786, THE GRUDGE 3644, THE PRINCESS BLADE 9554, THROW DOWN 28132, TONY TAKITANI 3137, VISITOR Q 12437, VITAL 29077, WASABI 25414, WATERBOYS 7762, YATTERMAN 34399, ZEBRAMAN src, edge_attr, dst 21950, directed_by, 33218 21950, release_year, 13408 21950, written_by, 33218 2452, directed_by, 4651 2452, has_tags, 4651 2452, in_language, 36874 29800, directed_by, 4651 29800, has_tags, 4651 29800, in_language, 36874 35189, in_language, 36874 35189, release_year, 13408 18598, in_language, 36874 18598, release_year, 37484 7908, directed_by, 4651 7908, has_tags, 4651 7908, in_language, 36874 2182, in_language, 36874 2182, release_year, 37484 5856, in_language, 36874 5856, release_year, 13408 6395, directed_by, 4651 6395, has_tags, 4651 6395, in_language, 36874 231, has_tags, 36874 231, in_language, 36874 231, release_year, 37484 38311, in_language, 36874 38311, release_year, 13408 1930, directed_by, 33218 1930, written_by, 33218 26635, directed_by, 4651 26635, has_tags, 4651 26635, in_language, 36874 5113, in_language, 36874 5113, release_year, 37484 36380, directed_by, 4651 36380, has_tags, 4651 36380, in_language, 36874 5951, in_language, 36874 5951, release_year, 13408 12298, directed_by, 4651 12298, has_tags, 4651 12298, in_language, 36874 2982, release_year, 37484 13409, in_language, 36874 13409, release_year, 37484 12087, in_language, 36874 12087, release_year, 37484 22330, in_language, 36874 22330, release_year, 13408 4215, directed_by, 4651 4215, has_tags, 4651 4215, in_language, 36874 4215, release_year, 13408 13174, in_language, 36874 13174, release_year, 37484 8164, directed_by, 4651 8164, has_tags, 4651 8164, in_language, 36874 8164, release_year, 37484 15150, has_tags, 36874 15150, in_language, 36874 15150, release_year, 37484 7892, directed_by, 4651 7892, in_language, 36874 7892, written_by, 4651 35621, in_language, 36874 35621, release_year, 13408 30532, in_language, 36874 30532, release_year, 37484 25709, in_language, 36874 25709, release_year, 37484 36326, directed_by, 4651 36326, in_language, 36874 36532, directed_by, 4651 36532, in_language, 36874 234, in_language, 36874 234, release_year, 13408 29748, in_language, 36874 29748, release_year, 13408 13237, has_tags, 36874 13237, in_language, 36874 13237, release_year, 13408 29919, directed_by, 4651 29919, has_tags, 4651 29919, in_language, 36874 6260, has_tags, 36874 6260, in_language, 36874 6260, release_year, 13408 31842, has_tags, 36874 31842, in_language, 36874 31842, release_year, 37484 38882, directed_by, 4651 38882, has_tags, 4651 38882, in_language, 36874 23910, directed_by, 4651 23910, has_tags, 4651 23910, in_language, 36874 24493, directed_by, 33218 24493, in_language, 36874 11297, directed_by, 4651 11297, has_tags, 4651 11297, in_language, 36874 11297, written_by, 4651 786, in_language, 36874 786, release_year, 37484 3644, in_language, 36874 3644, release_year, 13408 9554, in_language, 36874 9554, release_year, 37484 28132, in_language, 36874 28132, release_year, 37484 3137, directed_by, 4651 3137, has_tags, 4651 3137, in_language, 36874 3137, release_year, 13408 12437, in_language, 36874 12437, release_year, 37484 29077, in_language, 36874 29077, release_year, 13408 25414, in_language, 36874 25414, release_year, 13408 7762, directed_by, 4651 7762, in_language, 36874 34399, directed_by, 4651 34399, has_tags, 4651 34399, release_year, 37484 Question: For what reason are CHELSEA ON THE ROCKS, HALLOWEENTOWN HIGH, and ICHI THE KILLER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHELSEA ON THE ROCKS", "HALLOWEENTOWN HIGH", "ICHI THE KILLER" ], "valid_edges": [ [ "'R XMAS", "directed_by", "ABEL FERRARA" ], [ "'R XMAS", "release_year", "2001" ], [ "'R XMAS", "written_by", "ABEL FERRARA" ], [ "13 ASSASSINS", "directed_by", "TAKASHI MIIKE" ], [ "13 ASSASSINS", "has_tags", "TAKASHI MIIKE" ], [ "13 ASSASSINS", "in_language", "JAPANESE" ], [ "ACE ATTORNEY", "directed_by", "TAKASHI MIIKE" ], [ "ACE ATTORNEY", "has_tags", "TAKASHI MIIKE" ], [ "ACE ATTORNEY", "in_language", "JAPANESE" ], [ "ALL ABOUT LILY CHOU-CHOU", "in_language", "JAPANESE" ], [ "ALL ABOUT LILY CHOU-CHOU", "release_year", "2001" ], [ "APPLESEED", "in_language", "JAPANESE" ], [ "APPLESEED", "release_year", "2004" ], [ "AUDITION", "directed_by", "TAKASHI MIIKE" ], [ "AUDITION", "has_tags", "TAKASHI MIIKE" ], [ "AUDITION", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "release_year", "2004" ], [ "BLUE SPRING", "in_language", "JAPANESE" ], [ "BLUE SPRING", "release_year", "2001" ], [ "BLUES HARP", "directed_by", "TAKASHI MIIKE" ], [ "BLUES HARP", "has_tags", "TAKASHI MIIKE" ], [ "BLUES HARP", "in_language", "JAPANESE" ], [ "CASSHERN", "has_tags", "JAPANESE" ], [ "CASSHERN", "in_language", "JAPANESE" ], [ "CASSHERN", "release_year", "2004" ], [ "CHAOS", "in_language", "JAPANESE" ], [ "CHAOS", "release_year", "2001" ], [ "CHELSEA ON THE ROCKS", "directed_by", "ABEL FERRARA" ], [ "CHELSEA ON THE ROCKS", "written_by", "ABEL FERRARA" ], [ "CROWS ZERO", "directed_by", "TAKASHI MIIKE" ], [ "CROWS ZERO", "has_tags", "TAKASHI MIIKE" ], [ "CROWS ZERO", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "release_year", "2004" ], [ "DEAD OR ALIVE", "directed_by", "TAKASHI MIIKE" ], [ "DEAD OR ALIVE", "has_tags", "TAKASHI MIIKE" ], [ "DEAD OR ALIVE", "in_language", "JAPANESE" ], [ "ELECTRIC DRAGON 80.000 V", "in_language", "JAPANESE" ], [ "ELECTRIC DRAGON 80.000 V", "release_year", "2001" ], [ "GOZU", "directed_by", "TAKASHI MIIKE" ], [ "GOZU", "has_tags", "TAKASHI MIIKE" ], [ "GOZU", "in_language", "JAPANESE" ], [ "HALLOWEENTOWN HIGH", "release_year", "2004" ], [ "HANA AND ALICE", "in_language", "JAPANESE" ], [ "HANA AND ALICE", "release_year", "2004" ], [ "HOWL'S MOVING CASTLE", "in_language", "JAPANESE" ], [ "HOWL'S MOVING CASTLE", "release_year", "2004" ], [ "HUSH!", "in_language", "JAPANESE" ], [ "HUSH!", "release_year", "2001" ], [ "ICHI THE KILLER", "directed_by", "TAKASHI MIIKE" ], [ "ICHI THE KILLER", "has_tags", "TAKASHI MIIKE" ], [ "ICHI THE KILLER", "in_language", "JAPANESE" ], [ "ICHI THE KILLER", "release_year", "2001" ], [ "INFECTION", "in_language", "JAPANESE" ], [ "INFECTION", "release_year", "2004" ], [ "IZO", "directed_by", "TAKASHI MIIKE" ], [ "IZO", "has_tags", "TAKASHI MIIKE" ], [ "IZO", "in_language", "JAPANESE" ], [ "IZO", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "has_tags", "JAPANESE" ], [ "KAMIKAZE GIRLS", "in_language", "JAPANESE" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "LESSON OF THE EVIL", "directed_by", "TAKASHI MIIKE" ], [ "LESSON OF THE EVIL", "in_language", "JAPANESE" ], [ "LESSON OF THE EVIL", "written_by", "TAKASHI MIIKE" ], [ "MILLENNIUM ACTRESS", "in_language", "JAPANESE" ], [ "MILLENNIUM ACTRESS", "release_year", "2001" ], [ "MIND GAME", "in_language", "JAPANESE" ], [ "MIND GAME", "release_year", "2004" ], [ "NOBODY KNOWS", "in_language", "JAPANESE" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "ONE MISSED CALL", "directed_by", "TAKASHI MIIKE" ], [ "ONE MISSED CALL", "in_language", "JAPANESE" ], [ "OVER YOUR DEAD BODY", "directed_by", "TAKASHI MIIKE" ], [ "OVER YOUR DEAD BODY", "in_language", "JAPANESE" ], [ "PEARL HARBOR", "in_language", "JAPANESE" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PISTOL OPERA", "in_language", "JAPANESE" ], [ "PISTOL OPERA", "release_year", "2001" ], [ "PULSE", "has_tags", "JAPANESE" ], [ "PULSE", "in_language", "JAPANESE" ], [ "PULSE", "release_year", "2001" ], [ "RAINY DOG", "directed_by", "TAKASHI MIIKE" ], [ "RAINY DOG", "has_tags", "TAKASHI MIIKE" ], [ "RAINY DOG", "in_language", "JAPANESE" ], [ "SPIRITED AWAY", "has_tags", "JAPANESE" ], [ "SPIRITED AWAY", "in_language", "JAPANESE" ], [ "SPIRITED AWAY", "release_year", "2001" ], [ "SURVIVE STYLE 5+", "has_tags", "JAPANESE" ], [ "SURVIVE STYLE 5+", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "release_year", "2004" ], [ "THE BIRD PEOPLE IN CHINA", "directed_by", "TAKASHI MIIKE" ], [ "THE BIRD PEOPLE IN CHINA", "has_tags", "TAKASHI MIIKE" ], [ "THE BIRD PEOPLE IN CHINA", "in_language", "JAPANESE" ], [ "THE CITY OF LOST SOULS", "directed_by", "TAKASHI MIIKE" ], [ "THE CITY OF LOST SOULS", "has_tags", "TAKASHI MIIKE" ], [ "THE CITY OF LOST SOULS", "in_language", "JAPANESE" ], [ "THE FUNERAL", "directed_by", "ABEL FERRARA" ], [ "THE FUNERAL", "in_language", "JAPANESE" ], [ "THE GREAT YOKAI WAR", "directed_by", "TAKASHI MIIKE" ], [ "THE GREAT YOKAI WAR", "has_tags", "TAKASHI MIIKE" ], [ "THE GREAT YOKAI WAR", "in_language", "JAPANESE" ], [ "THE GREAT YOKAI WAR", "written_by", "TAKASHI MIIKE" ], [ "THE GRUDGE", "in_language", "JAPANESE" ], [ "THE GRUDGE", "release_year", "2004" ], [ "THE PRINCESS BLADE", "in_language", "JAPANESE" ], [ "THE PRINCESS BLADE", "release_year", "2001" ], [ "THROW DOWN", "in_language", "JAPANESE" ], [ "THROW DOWN", "release_year", "2004" ], [ "TONY TAKITANI", "in_language", "JAPANESE" ], [ "TONY TAKITANI", "release_year", "2004" ], [ "VISITOR Q", "directed_by", "TAKASHI MIIKE" ], [ "VISITOR Q", "has_tags", "TAKASHI MIIKE" ], [ "VISITOR Q", "in_language", "JAPANESE" ], [ "VISITOR Q", "release_year", "2001" ], [ "VITAL", "in_language", "JAPANESE" ], [ "VITAL", "release_year", "2004" ], [ "WASABI", "in_language", "JAPANESE" ], [ "WASABI", "release_year", "2001" ], [ "WATERBOYS", "in_language", "JAPANESE" ], [ "WATERBOYS", "release_year", "2001" ], [ "YATTERMAN", "directed_by", "TAKASHI MIIKE" ], [ "YATTERMAN", "in_language", "JAPANESE" ], [ "ZEBRAMAN", "directed_by", "TAKASHI MIIKE" ], [ "ZEBRAMAN", "has_tags", "TAKASHI MIIKE" ], [ "ZEBRAMAN", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18616, AMY ADAMS 15948, CALLING DR. GILLESPIE 36212, DRAMA 18908, DROP DEAD GORGEOUS 20422, HAROLD S. BUCQUET 22867, MICHAEL PATRICK JANN 27316, ROBERT LORENZ 17451, TROUBLE WITH THE CURVE src, edge_attr, dst 15948, directed_by, 20422 15948, has_genre, 36212 18908, directed_by, 22867 18908, has_tags, 18616 17451, directed_by, 27316 17451, has_genre, 36212 17451, has_tags, 18616 Question: In what context are HAROLD S. BUCQUET, MICHAEL PATRICK JANN, and ROBERT LORENZ connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HAROLD S. BUCQUET", "MICHAEL PATRICK JANN", "ROBERT LORENZ" ], "valid_edges": [ [ "CALLING DR. GILLESPIE", "directed_by", "HAROLD S. BUCQUET" ], [ "CALLING DR. GILLESPIE", "has_genre", "DRAMA" ], [ "DROP DEAD GORGEOUS", "directed_by", "MICHAEL PATRICK JANN" ], [ "DROP DEAD GORGEOUS", "has_tags", "AMY ADAMS" ], [ "TROUBLE WITH THE CURVE", "directed_by", "ROBERT LORENZ" ], [ "TROUBLE WITH THE CURVE", "has_genre", "DRAMA" ], [ "TROUBLE WITH THE CURVE", "has_tags", "AMY ADAMS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 16150, A CHRISTMAS STORY 12827, ACQUA E SAPONE 12144, BAD BOYS 7761, CAT AND DOG 4608, CLASS 30463, COMEDY 33111, COPPER MOUNTAIN 30019, CROSSROADS 38648, CURSE OF THE PINK PANTHER 1284, D.C. CAB 10162, DARK HABITS 4737, DEAL OF THE CENTURY 21558, DOCTOR DETROIT 36212, DRAMA 25445, EASY MONEY 38216, EDUCATING RITA 28117, ERÉNDIRA 10648, EVEN COWGIRLS GET THE BLUES 29593, GET CRAZY 15135, GINGER AND FRED 9054, GO FOR IT 12555, GOING BERSERK 1937, HANNAH AND HER SISTERS 2625, JOYSTICKS 29879, LOCAL HERO 37927, LOSIN' IT 39468, LOVESICK 29318, MALA NOCHE 31940, MAX DUGAN RETURNS 5699, MR. MOM 38932, MY TUTOR 36027, NATIONAL LAMPOON'S VACATION 4398, NOBODY'S FOOL 2654, NOTHING IN COMMON 20473, PEGGY SUE GOT MARRIED 31652, PRETTY IN PINK 4332, PRIVATE SCHOOL 23617, PROJECT A 14786, REUBEN, REUBEN 31054, RISKY BUSINESS 10066, ROMANTIC COMEDY 35586, SAHARA 9270, SEEMS LIKE OLD TIMES 37803, SHADOWS IN PARADISE 34888, SOMETHING WILD 19149, SPRING BREAK 32032, STRANGE BREW 10577, STROKER ACE 1328, TERMS OF ENDEARMENT 6667, THE BIG CHILL 4694, THE CREATURE WASN'T NICE 13316, THE DECLINE OF THE AMERICAN EMPIRE 33513, THE MAN WHO LOVED WOMEN 17006, THE MAN WITH TWO BRAINS 13058, THE SEX AND VIOLENCE FAMILY HOUR 30092, THE SURVIVORS 3640, TO BE OR NOT TO BE 37331, TO DIE FOR 18863, TRADING PLACES 19528, TWO OF A KIND 20647, VALLEY GIRL 25043, WALT CURTIS 30387, YELLOWBEARD src, edge_attr, dst 16150, has_genre, 30463 16150, release_year, 16055 12827, has_genre, 30463 12827, release_year, 16055 12144, has_genre, 30463 12144, has_genre, 36212 12144, has_tags, 30463 12144, release_year, 16055 7761, has_genre, 30463 7761, release_year, 16055 4608, has_genre, 30463 4608, has_genre, 36212 4608, release_year, 16055 33111, has_genre, 30463 33111, release_year, 16055 30019, has_genre, 30463 30019, has_genre, 36212 38648, has_genre, 30463 38648, release_year, 16055 1284, has_genre, 30463 1284, release_year, 16055 10162, has_genre, 30463 10162, release_year, 16055 4737, has_genre, 30463 4737, release_year, 16055 21558, has_genre, 30463 21558, release_year, 16055 25445, has_genre, 30463 25445, release_year, 16055 38216, has_genre, 30463 38216, has_genre, 36212 38216, release_year, 16055 28117, has_genre, 36212 28117, release_year, 16055 10648, has_genre, 30463 10648, has_genre, 36212 29593, has_genre, 30463 29593, release_year, 16055 15135, has_genre, 30463 15135, has_genre, 36212 9054, has_genre, 30463 9054, release_year, 16055 12555, has_genre, 30463 12555, has_tags, 30463 12555, release_year, 16055 1937, has_genre, 30463 1937, has_genre, 36212 1937, has_tags, 30463 2625, has_genre, 30463 2625, release_year, 16055 29879, has_genre, 30463 29879, has_genre, 36212 29879, release_year, 16055 37927, has_genre, 30463 37927, release_year, 16055 39468, has_genre, 30463 39468, release_year, 16055 29318, has_genre, 36212 29318, written_by, 25043 31940, has_genre, 30463 31940, has_genre, 36212 31940, release_year, 16055 5699, has_genre, 30463 5699, release_year, 16055 38932, has_genre, 30463 38932, release_year, 16055 36027, has_genre, 30463 36027, has_tags, 30463 36027, release_year, 16055 4398, has_genre, 30463 4398, has_genre, 36212 2654, has_genre, 30463 2654, has_genre, 36212 20473, has_genre, 30463 20473, has_genre, 36212 20473, has_tags, 36212 31652, has_genre, 30463 31652, has_genre, 36212 31652, has_tags, 30463 4332, has_genre, 30463 4332, release_year, 16055 23617, has_genre, 30463 23617, release_year, 16055 14786, has_genre, 30463 14786, has_genre, 36212 14786, release_year, 16055 31054, has_genre, 30463 31054, has_genre, 36212 31054, release_year, 16055 10066, has_genre, 30463 10066, release_year, 16055 35586, has_genre, 30463 35586, has_genre, 36212 35586, release_year, 16055 9270, has_genre, 30463 37803, has_genre, 30463 37803, has_genre, 36212 34888, has_genre, 30463 34888, has_genre, 36212 19149, has_genre, 30463 19149, release_year, 16055 32032, has_genre, 30463 32032, release_year, 16055 10577, has_genre, 30463 10577, release_year, 16055 1328, has_genre, 30463 1328, has_genre, 36212 1328, release_year, 16055 6667, has_genre, 30463 6667, has_genre, 36212 6667, release_year, 16055 4694, has_genre, 30463 4694, release_year, 16055 13316, has_genre, 30463 13316, has_genre, 36212 33513, has_genre, 30463 33513, has_genre, 36212 33513, release_year, 16055 17006, has_genre, 30463 17006, release_year, 16055 13058, has_genre, 30463 13058, release_year, 16055 30092, has_genre, 30463 30092, release_year, 16055 3640, has_genre, 30463 3640, has_tags, 30463 3640, release_year, 16055 37331, has_genre, 30463 37331, has_genre, 36212 18863, has_genre, 30463 18863, has_tags, 30463 18863, release_year, 16055 19528, has_genre, 30463 19528, release_year, 16055 20647, has_genre, 30463 20647, release_year, 16055 30387, has_genre, 30463 30387, release_year, 16055 Question: How are ERÉNDIRA, SEEMS LIKE OLD TIMES, and WALT CURTIS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ERÉNDIRA", "SEEMS LIKE OLD TIMES", "WALT CURTIS" ], "valid_edges": [ [ "A CHRISTMAS STORY", "has_genre", "COMEDY" ], [ "A CHRISTMAS STORY", "release_year", "1983" ], [ "ACQUA E SAPONE", "has_genre", "COMEDY" ], [ "ACQUA E SAPONE", "release_year", "1983" ], [ "BAD BOYS", "has_genre", "COMEDY" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_tags", "COMEDY" ], [ "BAD BOYS", "release_year", "1983" ], [ "CAT AND DOG", "has_genre", "COMEDY" ], [ "CAT AND DOG", "release_year", "1983" ], [ "CLASS", "has_genre", "COMEDY" ], [ "CLASS", "has_genre", "DRAMA" ], [ "CLASS", "release_year", "1983" ], [ "COPPER MOUNTAIN", "has_genre", "COMEDY" ], [ "COPPER MOUNTAIN", "release_year", "1983" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "DRAMA" ], [ "CURSE OF THE PINK PANTHER", "has_genre", "COMEDY" ], [ "CURSE OF THE PINK PANTHER", "release_year", "1983" ], [ "D.C. CAB", "has_genre", "COMEDY" ], [ "D.C. CAB", "release_year", "1983" ], [ "DARK HABITS", "has_genre", "COMEDY" ], [ "DARK HABITS", "release_year", "1983" ], [ "DEAL OF THE CENTURY", "has_genre", "COMEDY" ], [ "DEAL OF THE CENTURY", "release_year", "1983" ], [ "DOCTOR DETROIT", "has_genre", "COMEDY" ], [ "DOCTOR DETROIT", "release_year", "1983" ], [ "EASY MONEY", "has_genre", "COMEDY" ], [ "EASY MONEY", "release_year", "1983" ], [ "EDUCATING RITA", "has_genre", "COMEDY" ], [ "EDUCATING RITA", "has_genre", "DRAMA" ], [ "EDUCATING RITA", "release_year", "1983" ], [ "ERÉNDIRA", "has_genre", "DRAMA" ], [ "ERÉNDIRA", "release_year", "1983" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "COMEDY" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "DRAMA" ], [ "GET CRAZY", "has_genre", "COMEDY" ], [ "GET CRAZY", "release_year", "1983" ], [ "GINGER AND FRED", "has_genre", "COMEDY" ], [ "GINGER AND FRED", "has_genre", "DRAMA" ], [ "GO FOR IT", "has_genre", "COMEDY" ], [ "GO FOR IT", "release_year", "1983" ], [ "GOING BERSERK", "has_genre", "COMEDY" ], [ "GOING BERSERK", "has_tags", "COMEDY" ], [ "GOING BERSERK", "release_year", "1983" ], [ "HANNAH AND HER SISTERS", "has_genre", "COMEDY" ], [ "HANNAH AND HER SISTERS", "has_genre", "DRAMA" ], [ "HANNAH AND HER SISTERS", "has_tags", "COMEDY" ], [ "JOYSTICKS", "has_genre", "COMEDY" ], [ "JOYSTICKS", "release_year", "1983" ], [ "LOCAL HERO", "has_genre", "COMEDY" ], [ "LOCAL HERO", "has_genre", "DRAMA" ], [ "LOCAL HERO", "release_year", "1983" ], [ "LOSIN' IT", "has_genre", "COMEDY" ], [ "LOSIN' IT", "release_year", "1983" ], [ "LOVESICK", "has_genre", "COMEDY" ], [ "LOVESICK", "release_year", "1983" ], [ "MALA NOCHE", "has_genre", "DRAMA" ], [ "MALA NOCHE", "written_by", "WALT CURTIS" ], [ "MAX DUGAN RETURNS", "has_genre", "COMEDY" ], [ "MAX DUGAN RETURNS", "has_genre", "DRAMA" ], [ "MAX DUGAN RETURNS", "release_year", "1983" ], [ "MR. MOM", "has_genre", "COMEDY" ], [ "MR. MOM", "release_year", "1983" ], [ "MY TUTOR", "has_genre", "COMEDY" ], [ "MY TUTOR", "release_year", "1983" ], [ "NATIONAL LAMPOON'S VACATION", "has_genre", "COMEDY" ], [ "NATIONAL LAMPOON'S VACATION", "has_tags", "COMEDY" ], [ "NATIONAL LAMPOON'S VACATION", "release_year", "1983" ], [ "NOBODY'S FOOL", "has_genre", "COMEDY" ], [ "NOBODY'S FOOL", "has_genre", "DRAMA" ], [ "NOTHING IN COMMON", "has_genre", "COMEDY" ], [ "NOTHING IN COMMON", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "COMEDY" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_tags", "DRAMA" ], [ "PRETTY IN PINK", "has_genre", "COMEDY" ], [ "PRETTY IN PINK", "has_genre", "DRAMA" ], [ "PRETTY IN PINK", "has_tags", "COMEDY" ], [ "PRIVATE SCHOOL", "has_genre", "COMEDY" ], [ "PRIVATE SCHOOL", "release_year", "1983" ], [ "PROJECT A", "has_genre", "COMEDY" ], [ "PROJECT A", "release_year", "1983" ], [ "REUBEN, REUBEN", "has_genre", "COMEDY" ], [ "REUBEN, REUBEN", "has_genre", "DRAMA" ], [ "REUBEN, REUBEN", "release_year", "1983" ], [ "RISKY BUSINESS", "has_genre", "COMEDY" ], [ "RISKY BUSINESS", "has_genre", "DRAMA" ], [ "RISKY BUSINESS", "release_year", "1983" ], [ "ROMANTIC COMEDY", "has_genre", "COMEDY" ], [ "ROMANTIC COMEDY", "release_year", "1983" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "release_year", "1983" ], [ "SEEMS LIKE OLD TIMES", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "DRAMA" ], [ "SOMETHING WILD", "has_genre", "COMEDY" ], [ "SOMETHING WILD", "has_genre", "DRAMA" ], [ "SPRING BREAK", "has_genre", "COMEDY" ], [ "SPRING BREAK", "release_year", "1983" ], [ "STRANGE BREW", "has_genre", "COMEDY" ], [ "STRANGE BREW", "release_year", "1983" ], [ "STROKER ACE", "has_genre", "COMEDY" ], [ "STROKER ACE", "release_year", "1983" ], [ "TERMS OF ENDEARMENT", "has_genre", "COMEDY" ], [ "TERMS OF ENDEARMENT", "has_genre", "DRAMA" ], [ "TERMS OF ENDEARMENT", "release_year", "1983" ], [ "THE BIG CHILL", "has_genre", "COMEDY" ], [ "THE BIG CHILL", "has_genre", "DRAMA" ], [ "THE BIG CHILL", "release_year", "1983" ], [ "THE CREATURE WASN'T NICE", "has_genre", "COMEDY" ], [ "THE CREATURE WASN'T NICE", "release_year", "1983" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "COMEDY" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "DRAMA" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "COMEDY" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "DRAMA" ], [ "THE MAN WHO LOVED WOMEN", "release_year", "1983" ], [ "THE MAN WITH TWO BRAINS", "has_genre", "COMEDY" ], [ "THE MAN WITH TWO BRAINS", "release_year", "1983" ], [ "THE SEX AND VIOLENCE FAMILY HOUR", "has_genre", "COMEDY" ], [ "THE SEX AND VIOLENCE FAMILY HOUR", "release_year", "1983" ], [ "THE SURVIVORS", "has_genre", "COMEDY" ], [ "THE SURVIVORS", "release_year", "1983" ], [ "TO BE OR NOT TO BE", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "has_tags", "COMEDY" ], [ "TO BE OR NOT TO BE", "release_year", "1983" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TRADING PLACES", "has_genre", "COMEDY" ], [ "TRADING PLACES", "has_tags", "COMEDY" ], [ "TRADING PLACES", "release_year", "1983" ], [ "TWO OF A KIND", "has_genre", "COMEDY" ], [ "TWO OF A KIND", "release_year", "1983" ], [ "VALLEY GIRL", "has_genre", "COMEDY" ], [ "VALLEY GIRL", "release_year", "1983" ], [ "YELLOWBEARD", "has_genre", "COMEDY" ], [ "YELLOWBEARD", "release_year", "1983" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 11746, ANDREW BUJALSKI 18069, BEESWAX 25618, CHANNING TATUM 27633, FIGHTING 32615, THE TREASURE HUNTER 20619, TREASURE HUNT src, edge_attr, dst 18069, directed_by, 11746 18069, has_tags, 11746 18069, release_year, 27261 18069, written_by, 11746 27633, release_year, 27261 27633, starred_actors, 25618 32615, has_tags, 20619 32615, release_year, 27261 Question: In what context are ANDREW BUJALSKI, CHANNING TATUM, and TREASURE HUNT connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANDREW BUJALSKI", "CHANNING TATUM", "TREASURE HUNT" ], "valid_edges": [ [ "BEESWAX", "directed_by", "ANDREW BUJALSKI" ], [ "BEESWAX", "has_tags", "ANDREW BUJALSKI" ], [ "BEESWAX", "release_year", "2009" ], [ "BEESWAX", "written_by", "ANDREW BUJALSKI" ], [ "FIGHTING", "release_year", "2009" ], [ "FIGHTING", "starred_actors", "CHANNING TATUM" ], [ "THE TREASURE HUNTER", "has_tags", "TREASURE HUNT" ], [ "THE TREASURE HUNTER", "release_year", "2009" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 35935, 2002 37304, 21 JUMP STREET 26646, 3000 MILES TO GRACELAND 6094, A CLOCKWORK ORANGE 19635, A TRUE MOB STORY 6938, ALPHA DOG 20584, AMERICAN GANGSTER 551, AMERICAN GIGOLO 26048, AMERICAN HUSTLE 24342, AMY IRVING 19544, ANDY LAU 23328, APPALOOSA 23513, ASH WEDNESDAY 27270, ASSASSINATION TANGO 30795, ATLANTIC CITY 8402, BANGKOK DANGEROUS 23466, BEFORE THE DEVIL KNOWS YOU'RE DEAD 12228, BETTER LUCK TOMORROW 19633, BIRTHDAY GIRL 6837, BOSSA NOVA 33252, BROOKLYN'S FINEST 25849, BRUBAKER 15986, BUS 174 33362, CARLITO'S WAY 10790, CARRIED AWAY 27059, CATCH ME IF YOU CAN 33387, CITY OF GOD 13888, CITY OF THE LIVING DEAD 38098, CODE OF SILENCE 32049, CRASH 14724, CRIME 7393, CRIME AND PUNISHMENT 17819, DARK BLUE 14292, DEAD IN THE WATER 11826, DEEP COVER 9986, DELITTO A PORTA ROMANA 23027, DEUCES WILD 23396, DIAL M FOR MURDER 5795, DINNER RUSH 21021, DRIVE 12628, EASTERN PROMISES 26193, ELECTION 31254, ELITE SQUAD 8026, END OF THE GAME 31783, ENGLISH 19728, EVILENKO 11021, EYE IN THE SKY 21123, FARGO 16516, FIFTY DEAD MEN WALKING 18217, FIND ME GUILTY 4372, FORCE OF EXECUTION 29332, FOREIGN LANGUAGE 1033, FRACTURE 8690, FROZEN RIVER 17400, GANGS OF NEW YORK 23299, GET CARTER 35657, GLORIA 17938, HANNIBAL 36322, HARD BOILED 13846, HARSH TIMES 33673, HEAT 20659, HIGH AND LOW 26297, HIGH CRIMES 39349, HONEYSUCKLE ROSE 26001, HONG KONG 22006, I WANT YOU 34072, I'M NOT SCARED 978, INFERNAL AFFAIRS 7264, INSIDE MAN 24305, JCVD 13853, JUDGE DREDD 11346, KISS KISS BANG BANG 3854, LAYER CAKE 38120, LORD OF WAR 33950, LUCKY NUMBER SLEVIN 33561, MEAN STREETS 38677, MIAMI VICE 33280, MICHAEL BLACK 1454, MICKEY BLUE EYES 3487, MINORITY REPORT 13217, NARC 1922, NINE QUEENS 29893, NO GOOD DEED 22991, OUT OF THE BLUE 32999, PAID IN FULL 8509, PASSION 8869, PAYBACK 14744, PEOPLE I KNOW 29620, POLICE 26716, PRIDE AND GLORY 26174, PULP FICTION 38043, PUSHER 13081, R 2169, RANSOM 4523, RED DRAGON 31756, REMADE 32357, RESERVOIR DOGS 35872, RICH AND FAMOUS 25098, RICOCHET 5844, RIGHTEOUS KILL 1643, RISE OF THE FOOTSOLDIER 1507, ROAD TO PERDITION 8516, ROBOCOP 9206, ROCKNROLLA 31913, ROMEO IS BLEEDING 15500, ROMEO MUST DIE 33108, RUNNING SCARED 32607, RUSH HOUR 35808, SAFE 8020, SAFE MEN 32487, SAPPHIRE 6056, SCARFACE 5832, SCUM 22196, SERPICO 1472, SHOTTAS 12333, SMOKIN' ACES 7083, SONNY 35843, SPUN 4722, STATE PROPERTY 5170, STEALING HARVARD 16219, STORY 33414, SWEET SIXTEEN 30932, SWORDFISH 2512, THE BANK JOB 26674, THE BIG EASY 11948, THE BLACK DAHLIA 34875, THE COMPETITION 32597, THE DANCER UPSTAIRS 18997, THE DEPARTED 22234, THE ELEPHANT MAN 24501, THE EXTERMINATOR 38918, THE FAMILY 16151, THE FIENDISH PLOT OF DR. FU MANCHU 35551, THE GODFATHER 17518, THE GOOD THIEF 13052, THE HARD WORD 29952, THE INTERNATIONAL 28177, THE KRAYS 16288, THE LARAMIE PROJECT 11559, THE LOOKOUT 21696, THE MAN FROM LONDON 38433, THE MERCHANT OF VENICE 12887, THE MIRROR CRACK'D 37490, THE PERFECT MURDER 40086, THE PLACE BEYOND THE PINES 30014, THE RAID 2 13761, THE ROOKIE 14250, THE SALTON SEA 37148, THE SECRET IN THEIR EYES 19084, THE TOWN 22820, THE UNITED STATES OF LELAND 9390, THE UNTOUCHABLES 20880, THE USUAL SUSPECTS 19255, THE VALACHI PAPERS 14962, THE WATCHER IN THE WOODS 26758, THICK AS THIEVES 37331, TO DIE FOR 2879, TONY LEUNG 33836, TRAFFIC 17169, TRAINING DAY 27559, TRAINSPOTTING 24487, TRAPPED 10720, TRIGGERMEN 10238, UNDERWORLD 10133, UNKNOWN 22588, WANTED 6770, WE OWN THE NIGHT 37210, ZODIAC 17777, ZULU src, edge_attr, dst 37304, has_genre, 14724 37304, has_tags, 29620 26646, has_genre, 14724 26646, has_tags, 13081 6094, has_genre, 14724 6094, has_tags, 13081 6094, in_language, 31783 19635, has_genre, 14724 19635, starred_actors, 19544 6938, has_genre, 14724 6938, has_tags, 13081 20584, has_genre, 14724 20584, has_tags, 14724 20584, has_tags, 13081 551, has_genre, 14724 551, release_year, 36268 26048, has_genre, 14724 26048, has_tags, 13081 23328, has_genre, 14724 23328, has_tags, 13081 23513, has_genre, 14724 23513, release_year, 35935 27270, has_genre, 14724 27270, release_year, 35935 30795, has_genre, 14724 30795, release_year, 36268 8402, has_genre, 14724 8402, has_tags, 14724 8402, has_tags, 13081 23466, has_genre, 14724 23466, has_tags, 13081 12228, has_genre, 14724 12228, release_year, 35935 19633, has_genre, 14724 19633, in_language, 31783 6837, in_language, 31783 6837, starred_actors, 24342 33252, has_genre, 14724 33252, has_tags, 29620 25849, has_genre, 14724 25849, release_year, 36268 15986, has_tags, 29620 15986, release_year, 35935 33362, has_genre, 14724 33362, has_tags, 14724 33362, has_tags, 13081 10790, in_language, 31783 10790, starred_actors, 24342 27059, has_genre, 14724 27059, has_tags, 14724 27059, release_year, 35935 33387, has_genre, 14724 33387, has_tags, 14724 33387, has_tags, 13081 33387, release_year, 35935 13888, in_language, 31783 13888, release_year, 36268 38098, has_genre, 14724 38098, has_tags, 29620 32049, has_tags, 14724 32049, has_tags, 29620 32049, has_tags, 13081 7393, has_genre, 14724 7393, release_year, 35935 17819, has_genre, 14724 17819, release_year, 35935 14292, has_genre, 14724 14292, release_year, 35935 11826, has_genre, 14724 11826, has_tags, 13081 9986, has_genre, 14724 9986, release_year, 36268 23027, has_genre, 14724 23027, release_year, 35935 23396, has_genre, 14724 23396, in_language, 31783 5795, has_genre, 14724 5795, has_tags, 13081 21021, has_genre, 14724 21021, has_tags, 14724 21021, has_tags, 13081 12628, has_genre, 14724 12628, has_tags, 13081 26193, has_genre, 14724 26193, has_tags, 26001 31254, has_genre, 14724 31254, has_tags, 29620 8026, has_genre, 14724 8026, in_language, 31783 19728, has_genre, 14724 19728, in_language, 31783 11021, has_genre, 14724 11021, has_tags, 26001 21123, has_genre, 14724 21123, has_tags, 14724 21123, has_tags, 29620 21123, has_tags, 13081 16516, has_tags, 14724 16516, in_language, 31783 18217, has_genre, 14724 18217, has_tags, 13081 4372, has_genre, 14724 4372, written_by, 33280 1033, has_genre, 14724 1033, has_tags, 13081 8690, has_genre, 14724 8690, has_tags, 13081 17400, has_genre, 14724 17400, has_tags, 13081 17400, has_tags, 16219 17400, release_year, 35935 23299, has_genre, 14724 23299, has_tags, 31756 23299, has_tags, 16219 35657, has_genre, 14724 35657, release_year, 36268 17938, has_genre, 14724 17938, has_tags, 13081 36322, has_genre, 14724 36322, has_tags, 26001 36322, has_tags, 2879 13846, has_genre, 14724 13846, has_tags, 13081 33673, has_genre, 14724 33673, has_tags, 14724 33673, has_tags, 29620 33673, has_tags, 13081 20659, has_genre, 14724 20659, has_tags, 29620 26297, has_genre, 14724 26297, release_year, 35935 39349, release_year, 36268 39349, starred_actors, 24342 22006, has_genre, 14724 22006, in_language, 31783 34072, has_genre, 14724 34072, has_tags, 14724 34072, has_tags, 13081 978, has_genre, 14724 978, has_tags, 19544 978, has_tags, 29332 978, has_tags, 26001 978, has_tags, 29620 978, has_tags, 13081 978, has_tags, 31756 978, has_tags, 16219 978, has_tags, 2879 978, in_language, 31783 978, release_year, 35935 978, starred_actors, 19544 7264, has_genre, 14724 7264, has_tags, 13081 24305, has_genre, 14724 24305, has_tags, 13081 13853, has_genre, 14724 13853, has_tags, 29620 11346, has_genre, 14724 11346, has_tags, 13081 3854, has_genre, 14724 3854, has_tags, 13081 38120, has_genre, 14724 38120, has_tags, 14724 38120, has_tags, 13081 33950, has_genre, 14724 33950, has_tags, 14724 33950, has_tags, 13081 33561, has_genre, 14724 33561, has_tags, 13081 38677, has_genre, 14724 38677, has_tags, 13081 1454, has_genre, 14724 1454, in_language, 31783 3487, has_tags, 14724 3487, has_tags, 29620 3487, release_year, 35935 13217, has_genre, 14724 13217, has_tags, 29620 13217, release_year, 35935 1922, has_genre, 14724 1922, has_tags, 14724 1922, has_tags, 13081 29893, has_genre, 14724 29893, release_year, 35935 22991, release_year, 36268 22991, release_year, 35935 32999, has_genre, 14724 32999, release_year, 35935 8509, has_genre, 14724 8509, in_language, 31783 8869, has_genre, 14724 8869, has_tags, 13081 14744, has_genre, 14724 14744, has_tags, 13081 14744, release_year, 35935 29620, has_genre, 14724 26716, has_genre, 14724 26716, has_tags, 29620 26716, has_tags, 13081 26174, has_genre, 14724 26174, has_tags, 14724 26174, has_tags, 13081 38043, has_genre, 14724 38043, in_language, 31783 2169, has_genre, 14724 2169, has_tags, 13081 4523, has_genre, 14724 4523, has_tags, 13081 4523, release_year, 35935 32357, has_genre, 14724 32357, has_tags, 14724 32357, has_tags, 16219 35872, has_genre, 14724 35872, has_tags, 19544 35872, starred_actors, 19544 25098, has_genre, 14724 25098, has_tags, 13081 5844, has_genre, 14724 5844, has_tags, 13081 1643, has_genre, 14724 1643, has_tags, 14724 1643, in_language, 31783 1507, has_genre, 14724 1507, release_year, 35935 8516, has_tags, 14724 8516, has_tags, 29620 9206, has_genre, 14724 9206, has_tags, 14724 9206, has_tags, 13081 31913, has_genre, 14724 31913, has_tags, 13081 15500, has_tags, 13081 15500, in_language, 31783 33108, has_genre, 14724 33108, has_tags, 29620 33108, release_year, 36268 32607, has_tags, 14724 32607, has_tags, 26001 32607, has_tags, 29620 35808, has_genre, 14724 35808, has_tags, 29620 8020, has_genre, 14724 8020, has_tags, 13081 32487, has_genre, 14724 32487, in_language, 31783 6056, has_genre, 14724 6056, has_tags, 14724 6056, has_tags, 16219 5832, has_genre, 14724 5832, has_tags, 16219 22196, has_genre, 14724 22196, has_tags, 29620 1472, has_genre, 14724 1472, release_year, 35935 12333, has_genre, 14724 12333, has_tags, 13081 7083, has_genre, 14724 7083, release_year, 35935 35843, has_genre, 14724 35843, release_year, 35935 4722, has_genre, 14724 4722, release_year, 35935 5170, has_genre, 14724 5170, release_year, 35935 33414, has_genre, 14724 33414, has_tags, 13081 33414, in_language, 31783 33414, release_year, 35935 30932, has_genre, 14724 30932, has_tags, 13081 2512, has_genre, 14724 2512, has_tags, 13081 26674, has_genre, 14724 26674, has_tags, 13081 11948, has_genre, 14724 11948, has_tags, 13081 34875, release_year, 36268 34875, starred_actors, 24342 32597, has_genre, 14724 32597, release_year, 35935 18997, has_genre, 14724 18997, has_tags, 14724 18997, has_tags, 29620 18997, has_tags, 13081 22234, in_language, 31783 22234, release_year, 36268 24501, has_genre, 14724 24501, release_year, 36268 38918, has_genre, 14724 38918, in_language, 31783 16151, in_language, 31783 16151, release_year, 36268 35551, has_genre, 14724 35551, has_tags, 14724 35551, has_tags, 13081 35551, has_tags, 16219 17518, has_genre, 14724 17518, release_year, 35935 13052, has_genre, 14724 13052, release_year, 35935 29952, has_genre, 14724 29952, has_tags, 13081 28177, has_genre, 14724 28177, in_language, 31783 16288, has_genre, 14724 16288, release_year, 35935 11559, has_genre, 14724 11559, has_tags, 13081 21696, has_genre, 14724 21696, in_language, 31783 38433, has_tags, 13081 38433, in_language, 31783 38433, release_year, 36268 12887, has_genre, 14724 12887, release_year, 36268 37490, has_tags, 14724 37490, in_language, 31783 40086, has_genre, 14724 40086, in_language, 31783 30014, has_genre, 14724 30014, in_language, 31783 13761, has_genre, 14724 13761, release_year, 35935 14250, has_genre, 14724 14250, release_year, 35935 37148, has_tags, 14724 37148, has_tags, 29332 37148, has_tags, 13081 19084, has_genre, 14724 19084, has_tags, 14724 19084, has_tags, 13081 22820, has_genre, 14724 22820, has_tags, 13081 9390, has_genre, 14724 9390, has_tags, 14724 9390, has_tags, 13081 20880, has_genre, 14724 20880, has_tags, 14724 20880, has_tags, 13081 19255, has_genre, 14724 19255, in_language, 31783 14962, in_language, 31783 14962, release_year, 36268 26758, has_genre, 14724 26758, has_tags, 13081 37331, has_genre, 14724 37331, has_tags, 13081 33836, has_genre, 14724 33836, has_tags, 13081 17169, has_genre, 14724 17169, has_tags, 13081 27559, has_tags, 14724 27559, has_tags, 13081 24487, has_genre, 14724 24487, release_year, 35935 10720, has_genre, 14724 10720, has_tags, 14724 10720, release_year, 35935 10238, has_genre, 14724 10238, in_language, 31783 10133, has_genre, 14724 10133, in_language, 31783 22588, has_genre, 14724 22588, has_tags, 13081 6770, has_genre, 14724 6770, has_tags, 13081 37210, has_genre, 14724 37210, has_tags, 14724 37210, has_tags, 29620 37210, has_tags, 13081 17777, has_genre, 14724 17777, in_language, 31783 Question: In what context are HONEYSUCKLE ROSE, INFERNAL AFFAIRS, and MICHAEL BLACK connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HONEYSUCKLE ROSE", "INFERNAL AFFAIRS", "MICHAEL BLACK" ], "valid_edges": [ [ "21 JUMP STREET", "has_genre", "CRIME" ], [ "21 JUMP STREET", "has_tags", "POLICE" ], [ "3000 MILES TO GRACELAND", "has_genre", "CRIME" ], [ "3000 MILES TO GRACELAND", "has_tags", "R" ], [ "A CLOCKWORK ORANGE", "has_genre", "CRIME" ], [ "A CLOCKWORK ORANGE", "has_tags", "R" ], [ "A CLOCKWORK ORANGE", "in_language", "ENGLISH" ], [ "A TRUE MOB STORY", "has_genre", "CRIME" ], [ "A TRUE MOB STORY", "starred_actors", "ANDY LAU" ], [ "ALPHA DOG", "has_genre", "CRIME" ], [ "ALPHA DOG", "has_tags", "R" ], [ "AMERICAN GANGSTER", "has_genre", "CRIME" ], [ "AMERICAN GANGSTER", "has_tags", "CRIME" ], [ "AMERICAN GANGSTER", "has_tags", "R" ], [ "AMERICAN GIGOLO", "has_genre", "CRIME" ], [ "AMERICAN GIGOLO", "release_year", "1980" ], [ "AMERICAN HUSTLE", "has_genre", "CRIME" ], [ "AMERICAN HUSTLE", "has_tags", "R" ], [ "APPALOOSA", "has_genre", "CRIME" ], [ "APPALOOSA", "has_tags", "R" ], [ "ASH WEDNESDAY", "has_genre", "CRIME" ], [ "ASH WEDNESDAY", "release_year", "2002" ], [ "ASSASSINATION TANGO", "has_genre", "CRIME" ], [ "ASSASSINATION TANGO", "release_year", "2002" ], [ "ATLANTIC CITY", "has_genre", "CRIME" ], [ "ATLANTIC CITY", "release_year", "1980" ], [ "BANGKOK DANGEROUS", "has_genre", "CRIME" ], [ "BANGKOK DANGEROUS", "has_tags", "CRIME" ], [ "BANGKOK DANGEROUS", "has_tags", "R" ], [ "BEFORE THE DEVIL KNOWS YOU'RE DEAD", "has_genre", "CRIME" ], [ "BEFORE THE DEVIL KNOWS YOU'RE DEAD", "has_tags", "R" ], [ "BETTER LUCK TOMORROW", "has_genre", "CRIME" ], [ "BETTER LUCK TOMORROW", "release_year", "2002" ], [ "BIRTHDAY GIRL", "has_genre", "CRIME" ], [ "BIRTHDAY GIRL", "in_language", "ENGLISH" ], [ "BOSSA NOVA", "in_language", "ENGLISH" ], [ "BOSSA NOVA", "starred_actors", "AMY IRVING" ], [ "BROOKLYN'S FINEST", "has_genre", "CRIME" ], [ "BROOKLYN'S FINEST", "has_tags", "POLICE" ], [ "BRUBAKER", "has_genre", "CRIME" ], [ "BRUBAKER", "release_year", "1980" ], [ "BUS 174", "has_tags", "POLICE" ], [ "BUS 174", "release_year", "2002" ], [ "CARLITO'S WAY", "has_genre", "CRIME" ], [ "CARLITO'S WAY", "has_tags", "CRIME" ], [ "CARLITO'S WAY", "has_tags", "R" ], [ "CARRIED AWAY", "in_language", "ENGLISH" ], [ "CARRIED AWAY", "starred_actors", "AMY IRVING" ], [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "release_year", "2002" ], [ "CITY OF GOD", "has_genre", "CRIME" ], [ "CITY OF GOD", "has_tags", "CRIME" ], [ "CITY OF GOD", "has_tags", "R" ], [ "CITY OF GOD", "release_year", "2002" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CODE OF SILENCE", "has_genre", "CRIME" ], [ "CODE OF SILENCE", "has_tags", "POLICE" ], [ "CRASH", "has_tags", "CRIME" ], [ "CRASH", "has_tags", "POLICE" ], [ "CRASH", "has_tags", "R" ], [ "CRIME AND PUNISHMENT", "has_genre", "CRIME" ], [ "CRIME AND PUNISHMENT", "release_year", "2002" ], [ "DARK BLUE", "has_genre", "CRIME" ], [ "DARK BLUE", "release_year", "2002" ], [ "DEAD IN THE WATER", "has_genre", "CRIME" ], [ "DEAD IN THE WATER", "release_year", "2002" ], [ "DEEP COVER", "has_genre", "CRIME" ], [ "DEEP COVER", "has_tags", "R" ], [ "DELITTO A PORTA ROMANA", "has_genre", "CRIME" ], [ "DELITTO A PORTA ROMANA", "release_year", "1980" ], [ "DEUCES WILD", "has_genre", "CRIME" ], [ "DEUCES WILD", "release_year", "2002" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DINNER RUSH", "has_genre", "CRIME" ], [ "DINNER RUSH", "has_tags", "R" ], [ "DRIVE", "has_genre", "CRIME" ], [ "DRIVE", "has_tags", "CRIME" ], [ "DRIVE", "has_tags", "R" ], [ "EASTERN PROMISES", "has_genre", "CRIME" ], [ "EASTERN PROMISES", "has_tags", "R" ], [ "ELECTION", "has_genre", "CRIME" ], [ "ELECTION", "has_tags", "HONG KONG" ], [ "ELITE SQUAD", "has_genre", "CRIME" ], [ "ELITE SQUAD", "has_tags", "POLICE" ], [ "END OF THE GAME", "has_genre", "CRIME" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "EVILENKO", "has_genre", "CRIME" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "EYE IN THE SKY", "has_genre", "CRIME" ], [ "EYE IN THE SKY", "has_tags", "HONG KONG" ], [ "FARGO", "has_genre", "CRIME" ], [ "FARGO", "has_tags", "CRIME" ], [ "FARGO", "has_tags", "POLICE" ], [ "FARGO", "has_tags", "R" ], [ "FIFTY DEAD MEN WALKING", "has_tags", "CRIME" ], [ "FIFTY DEAD MEN WALKING", "in_language", "ENGLISH" ], [ "FIND ME GUILTY", "has_genre", "CRIME" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FORCE OF EXECUTION", "has_genre", "CRIME" ], [ "FORCE OF EXECUTION", "written_by", "MICHAEL BLACK" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_tags", "R" ], [ "FROZEN RIVER", "has_genre", "CRIME" ], [ "FROZEN RIVER", "has_tags", "R" ], [ "GANGS OF NEW YORK", "has_genre", "CRIME" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "has_tags", "STORY" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "GET CARTER", "has_genre", "CRIME" ], [ "GET CARTER", "has_tags", "REMADE" ], [ "GET CARTER", "has_tags", "STORY" ], [ "GLORIA", "has_genre", "CRIME" ], [ "GLORIA", "release_year", "1980" ], [ "HANNIBAL", "has_genre", "CRIME" ], [ "HANNIBAL", "has_tags", "R" ], [ "HARD BOILED", "has_genre", "CRIME" ], [ "HARD BOILED", "has_tags", "HONG KONG" ], [ "HARD BOILED", "has_tags", "TONY LEUNG" ], [ "HARSH TIMES", "has_genre", "CRIME" ], [ "HARSH TIMES", "has_tags", "R" ], [ "HEAT", "has_genre", "CRIME" ], [ "HEAT", "has_tags", "CRIME" ], [ "HEAT", "has_tags", "POLICE" ], [ "HEAT", "has_tags", "R" ], [ "HIGH AND LOW", "has_genre", "CRIME" ], [ "HIGH AND LOW", "has_tags", "POLICE" ], [ "HIGH CRIMES", "has_genre", "CRIME" ], [ "HIGH CRIMES", "release_year", "2002" ], [ "HONEYSUCKLE ROSE", "release_year", "1980" ], [ "HONEYSUCKLE ROSE", "starred_actors", "AMY IRVING" ], [ "I WANT YOU", "has_genre", "CRIME" ], [ "I WANT YOU", "in_language", "ENGLISH" ], [ "I'M NOT SCARED", "has_genre", "CRIME" ], [ "I'M NOT SCARED", "has_tags", "CRIME" ], [ "I'M NOT SCARED", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "has_genre", "CRIME" ], [ "INFERNAL AFFAIRS", "has_tags", "ANDY LAU" ], [ "INFERNAL AFFAIRS", "has_tags", "FOREIGN LANGUAGE" ], [ "INFERNAL AFFAIRS", "has_tags", "HONG KONG" ], [ "INFERNAL AFFAIRS", "has_tags", "POLICE" ], [ "INFERNAL AFFAIRS", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "has_tags", "REMADE" ], [ "INFERNAL AFFAIRS", "has_tags", "STORY" ], [ "INFERNAL AFFAIRS", "has_tags", "TONY LEUNG" ], [ "INFERNAL AFFAIRS", "in_language", "ENGLISH" ], [ "INFERNAL AFFAIRS", "release_year", "2002" ], [ "INFERNAL AFFAIRS", "starred_actors", "ANDY LAU" ], [ "INSIDE MAN", "has_genre", "CRIME" ], [ "INSIDE MAN", "has_tags", "R" ], [ "JCVD", "has_genre", "CRIME" ], [ "JCVD", "has_tags", "R" ], [ "JUDGE DREDD", "has_genre", "CRIME" ], [ "JUDGE DREDD", "has_tags", "POLICE" ], [ "KISS KISS BANG BANG", "has_genre", "CRIME" ], [ "KISS KISS BANG BANG", "has_tags", "R" ], [ "LAYER CAKE", "has_genre", "CRIME" ], [ "LAYER CAKE", "has_tags", "R" ], [ "LORD OF WAR", "has_genre", "CRIME" ], [ "LORD OF WAR", "has_tags", "CRIME" ], [ "LORD OF WAR", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "has_genre", "CRIME" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "CRIME" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "MEAN STREETS", "has_genre", "CRIME" ], [ "MEAN STREETS", "has_tags", "R" ], [ "MIAMI VICE", "has_genre", "CRIME" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MICKEY BLUE EYES", "has_genre", "CRIME" ], [ "MICKEY BLUE EYES", "in_language", "ENGLISH" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "POLICE" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "NARC", "has_genre", "CRIME" ], [ "NARC", "has_tags", "POLICE" ], [ "NARC", "release_year", "2002" ], [ "NINE QUEENS", "has_genre", "CRIME" ], [ "NINE QUEENS", "has_tags", "CRIME" ], [ "NINE QUEENS", "has_tags", "R" ], [ "NO GOOD DEED", "has_genre", "CRIME" ], [ "NO GOOD DEED", "release_year", "2002" ], [ "OUT OF THE BLUE", "release_year", "1980" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PAID IN FULL", "has_genre", "CRIME" ], [ "PAID IN FULL", "release_year", "2002" ], [ "PASSION", "has_genre", "CRIME" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PAYBACK", "has_genre", "CRIME" ], [ "PAYBACK", "has_tags", "R" ], [ "PEOPLE I KNOW", "has_genre", "CRIME" ], [ "PEOPLE I KNOW", "has_tags", "R" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "POLICE", "has_genre", "CRIME" ], [ "PRIDE AND GLORY", "has_genre", "CRIME" ], [ "PRIDE AND GLORY", "has_tags", "POLICE" ], [ "PRIDE AND GLORY", "has_tags", "R" ], [ "PULP FICTION", "has_genre", "CRIME" ], [ "PULP FICTION", "has_tags", "CRIME" ], [ "PULP FICTION", "has_tags", "R" ], [ "PUSHER", "has_genre", "CRIME" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "RANSOM", "has_genre", "CRIME" ], [ "RANSOM", "has_tags", "R" ], [ "RED DRAGON", "has_genre", "CRIME" ], [ "RED DRAGON", "has_tags", "R" ], [ "RED DRAGON", "release_year", "2002" ], [ "RESERVOIR DOGS", "has_genre", "CRIME" ], [ "RESERVOIR DOGS", "has_tags", "CRIME" ], [ "RESERVOIR DOGS", "has_tags", "STORY" ], [ "RICH AND FAMOUS", "has_genre", "CRIME" ], [ "RICH AND FAMOUS", "has_tags", "ANDY LAU" ], [ "RICH AND FAMOUS", "starred_actors", "ANDY LAU" ], [ "RICOCHET", "has_genre", "CRIME" ], [ "RICOCHET", "has_tags", "R" ], [ "RIGHTEOUS KILL", "has_genre", "CRIME" ], [ "RIGHTEOUS KILL", "has_tags", "R" ], [ "RISE OF THE FOOTSOLDIER", "has_genre", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "has_tags", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "ROAD TO PERDITION", "has_genre", "CRIME" ], [ "ROAD TO PERDITION", "release_year", "2002" ], [ "ROBOCOP", "has_tags", "CRIME" ], [ "ROBOCOP", "has_tags", "POLICE" ], [ "ROCKNROLLA", "has_genre", "CRIME" ], [ "ROCKNROLLA", "has_tags", "CRIME" ], [ "ROCKNROLLA", "has_tags", "R" ], [ "ROMEO IS BLEEDING", "has_genre", "CRIME" ], [ "ROMEO IS BLEEDING", "has_tags", "R" ], [ "ROMEO MUST DIE", "has_tags", "R" ], [ "ROMEO MUST DIE", "in_language", "ENGLISH" ], [ "RUNNING SCARED", "has_genre", "CRIME" ], [ "RUNNING SCARED", "has_tags", "POLICE" ], [ "RUNNING SCARED", "release_year", "1980" ], [ "RUSH HOUR", "has_tags", "CRIME" ], [ "RUSH HOUR", "has_tags", "HONG KONG" ], [ "RUSH HOUR", "has_tags", "POLICE" ], [ "SAFE", "has_genre", "CRIME" ], [ "SAFE", "has_tags", "POLICE" ], [ "SAFE MEN", "has_genre", "CRIME" ], [ "SAFE MEN", "has_tags", "R" ], [ "SAPPHIRE", "has_genre", "CRIME" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SCARFACE", "has_genre", "CRIME" ], [ "SCARFACE", "has_tags", "CRIME" ], [ "SCARFACE", "has_tags", "STORY" ], [ "SCUM", "has_genre", "CRIME" ], [ "SCUM", "has_tags", "STORY" ], [ "SERPICO", "has_genre", "CRIME" ], [ "SERPICO", "has_tags", "POLICE" ], [ "SHOTTAS", "has_genre", "CRIME" ], [ "SHOTTAS", "release_year", "2002" ], [ "SMOKIN' ACES", "has_genre", "CRIME" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SONNY", "has_genre", "CRIME" ], [ "SONNY", "release_year", "2002" ], [ "SPUN", "has_genre", "CRIME" ], [ "SPUN", "release_year", "2002" ], [ "STATE PROPERTY", "has_genre", "CRIME" ], [ "STATE PROPERTY", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "CRIME" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_genre", "CRIME" ], [ "SWEET SIXTEEN", "has_tags", "R" ], [ "SWEET SIXTEEN", "in_language", "ENGLISH" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "SWORDFISH", "has_genre", "CRIME" ], [ "SWORDFISH", "has_tags", "R" ], [ "THE BANK JOB", "has_genre", "CRIME" ], [ "THE BANK JOB", "has_tags", "R" ], [ "THE BIG EASY", "has_genre", "CRIME" ], [ "THE BIG EASY", "has_tags", "R" ], [ "THE BLACK DAHLIA", "has_genre", "CRIME" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE COMPETITION", "release_year", "1980" ], [ "THE COMPETITION", "starred_actors", "AMY IRVING" ], [ "THE DANCER UPSTAIRS", "has_genre", "CRIME" ], [ "THE DANCER UPSTAIRS", "release_year", "2002" ], [ "THE DEPARTED", "has_genre", "CRIME" ], [ "THE DEPARTED", "has_tags", "CRIME" ], [ "THE DEPARTED", "has_tags", "POLICE" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE ELEPHANT MAN", "in_language", "ENGLISH" ], [ "THE ELEPHANT MAN", "release_year", "1980" ], [ "THE EXTERMINATOR", "has_genre", "CRIME" ], [ "THE EXTERMINATOR", "release_year", "1980" ], [ "THE FAMILY", "has_genre", "CRIME" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FIENDISH PLOT OF DR. FU MANCHU", "in_language", "ENGLISH" ], [ "THE FIENDISH PLOT OF DR. FU MANCHU", "release_year", "1980" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "CRIME" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "has_tags", "STORY" ], [ "THE GOOD THIEF", "has_genre", "CRIME" ], [ "THE GOOD THIEF", "release_year", "2002" ], [ "THE HARD WORD", "has_genre", "CRIME" ], [ "THE HARD WORD", "release_year", "2002" ], [ "THE INTERNATIONAL", "has_genre", "CRIME" ], [ "THE INTERNATIONAL", "has_tags", "R" ], [ "THE KRAYS", "has_genre", "CRIME" ], [ "THE KRAYS", "in_language", "ENGLISH" ], [ "THE LARAMIE PROJECT", "has_genre", "CRIME" ], [ "THE LARAMIE PROJECT", "release_year", "2002" ], [ "THE LOOKOUT", "has_genre", "CRIME" ], [ "THE LOOKOUT", "has_tags", "R" ], [ "THE MAN FROM LONDON", "has_genre", "CRIME" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "has_tags", "R" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "1980" ], [ "THE MIRROR CRACK'D", "has_genre", "CRIME" ], [ "THE MIRROR CRACK'D", "release_year", "1980" ], [ "THE PERFECT MURDER", "has_tags", "CRIME" ], [ "THE PERFECT MURDER", "in_language", "ENGLISH" ], [ "THE PLACE BEYOND THE PINES", "has_genre", "CRIME" ], [ "THE PLACE BEYOND THE PINES", "in_language", "ENGLISH" ], [ "THE RAID 2", "has_genre", "CRIME" ], [ "THE RAID 2", "in_language", "ENGLISH" ], [ "THE ROOKIE", "has_genre", "CRIME" ], [ "THE ROOKIE", "release_year", "2002" ], [ "THE SALTON SEA", "has_genre", "CRIME" ], [ "THE SALTON SEA", "release_year", "2002" ], [ "THE SECRET IN THEIR EYES", "has_tags", "CRIME" ], [ "THE SECRET IN THEIR EYES", "has_tags", "FOREIGN LANGUAGE" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE TOWN", "has_genre", "CRIME" ], [ "THE TOWN", "has_tags", "CRIME" ], [ "THE TOWN", "has_tags", "R" ], [ "THE UNITED STATES OF LELAND", "has_genre", "CRIME" ], [ "THE UNITED STATES OF LELAND", "has_tags", "R" ], [ "THE UNTOUCHABLES", "has_genre", "CRIME" ], [ "THE UNTOUCHABLES", "has_tags", "CRIME" ], [ "THE UNTOUCHABLES", "has_tags", "R" ], [ "THE USUAL SUSPECTS", "has_genre", "CRIME" ], [ "THE USUAL SUSPECTS", "has_tags", "CRIME" ], [ "THE USUAL SUSPECTS", "has_tags", "R" ], [ "THE VALACHI PAPERS", "has_genre", "CRIME" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "THICK AS THIEVES", "has_genre", "CRIME" ], [ "THICK AS THIEVES", "has_tags", "R" ], [ "TO DIE FOR", "has_genre", "CRIME" ], [ "TO DIE FOR", "has_tags", "R" ], [ "TRAFFIC", "has_genre", "CRIME" ], [ "TRAFFIC", "has_tags", "R" ], [ "TRAINING DAY", "has_genre", "CRIME" ], [ "TRAINING DAY", "has_tags", "R" ], [ "TRAINSPOTTING", "has_tags", "CRIME" ], [ "TRAINSPOTTING", "has_tags", "R" ], [ "TRAPPED", "has_genre", "CRIME" ], [ "TRAPPED", "release_year", "2002" ], [ "TRIGGERMEN", "has_genre", "CRIME" ], [ "TRIGGERMEN", "has_tags", "CRIME" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "UNDERWORLD", "has_genre", "CRIME" ], [ "UNDERWORLD", "in_language", "ENGLISH" ], [ "UNKNOWN", "has_genre", "CRIME" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "WANTED", "has_genre", "CRIME" ], [ "WANTED", "has_tags", "R" ], [ "WE OWN THE NIGHT", "has_genre", "CRIME" ], [ "WE OWN THE NIGHT", "has_tags", "R" ], [ "ZODIAC", "has_genre", "CRIME" ], [ "ZODIAC", "has_tags", "CRIME" ], [ "ZODIAC", "has_tags", "POLICE" ], [ "ZODIAC", "has_tags", "R" ], [ "ZULU", "has_genre", "CRIME" ], [ "ZULU", "in_language", "ENGLISH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3458, 1951 3702, 1995 38344, A STREETCAR NAMED DESIRE 38907, ABBOTT AND COSTELLO MEET THE INVISIBLE MAN 31987, ACROSS THE SEA OF TIME 4763, ADVENTURE 29638, ALICE IN WONDERLAND 17157, ARABIAN NIGHTS 18666, BALTO 38657, BEAT THE DEVIL 14207, BEYOND THE CLOUDS 1587, BUSHWHACKED 16220, CAPTAIN HORATIO HORNBLOWER R.N. 16, CONGO 10386, CRY, THE BELOVED COUNTRY 8438, CUT AND RUN 30802, CUTTHROAT ISLAND 12903, DISNEY 16200, ITALIAN 14980, JUMANJI 20149, LAST OF THE DOGMEN 4386, MIRACLE IN MILAN 39027, MORTAL KOMBAT 11078, MOUSE 12215, ROB ROY 35586, SAHARA 29427, STARCRASH 26790, SWEPT AWAY 29639, TALL TALE 38627, TEN TALL MEN 29634, THE AFRICAN QUEEN 4001, THE AMAZING PANDA ADVENTURE 30259, THE GREAT MOUSE DETECTIVE 32270, THE HORSEMAN ON THE ROOF 18787, THE INDIAN IN THE CUPBOARD 39975, THE RESCUERS 27481, THE STAR MAKER 32074, TOM AND HUCK 9450, TOY STORY 32079, ULYSSES 29631, WHITE FANG src, edge_attr, dst 38344, release_year, 3458 38344, release_year, 3702 38907, release_year, 3458 31987, has_genre, 4763 31987, release_year, 3702 29638, has_genre, 4763 29638, release_year, 3458 17157, has_genre, 4763 17157, in_language, 16200 18666, has_genre, 4763 18666, release_year, 3702 38657, has_genre, 4763 38657, in_language, 16200 14207, in_language, 16200 14207, release_year, 3702 1587, has_genre, 4763 1587, release_year, 3702 16220, has_genre, 4763 16220, release_year, 3458 16, has_genre, 4763 16, release_year, 3702 10386, release_year, 3458 10386, release_year, 3702 8438, has_genre, 4763 8438, in_language, 16200 30802, has_genre, 4763 30802, has_tags, 4763 30802, release_year, 3702 14980, has_genre, 4763 14980, has_tags, 4763 14980, release_year, 3702 20149, has_genre, 4763 20149, release_year, 3702 4386, in_language, 16200 4386, release_year, 3458 39027, has_genre, 4763 39027, release_year, 3702 12215, has_genre, 4763 12215, release_year, 3702 35586, has_genre, 4763 35586, in_language, 16200 29427, has_genre, 4763 29427, in_language, 16200 26790, has_genre, 4763 26790, in_language, 16200 29639, has_genre, 4763 29639, release_year, 3702 38627, has_genre, 4763 38627, release_year, 3458 29634, has_genre, 4763 29634, has_tags, 4763 29634, release_year, 3458 4001, has_genre, 4763 4001, release_year, 3702 30259, has_genre, 4763 30259, has_tags, 12903 30259, has_tags, 11078 32270, has_genre, 4763 32270, in_language, 16200 32270, release_year, 3702 18787, has_genre, 4763 18787, release_year, 3702 39975, has_genre, 4763 39975, has_tags, 12903 39975, has_tags, 11078 27481, in_language, 16200 27481, release_year, 3702 32074, has_genre, 4763 32074, release_year, 3702 9450, has_genre, 4763 9450, has_tags, 4763 9450, release_year, 3702 32079, has_genre, 4763 32079, in_language, 16200 29631, has_genre, 4763 29631, in_language, 16200 Question: How are ABBOTT AND COSTELLO MEET THE INVISIBLE MAN, MOUSE, and THE HORSEMAN ON THE ROOF related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ABBOTT AND COSTELLO MEET THE INVISIBLE MAN", "MOUSE", "THE HORSEMAN ON THE ROOF" ], "valid_edges": [ [ "A STREETCAR NAMED DESIRE", "release_year", "1951" ], [ "A STREETCAR NAMED DESIRE", "release_year", "1995" ], [ "ABBOTT AND COSTELLO MEET THE INVISIBLE MAN", "release_year", "1951" ], [ "ACROSS THE SEA OF TIME", "has_genre", "ADVENTURE" ], [ "ACROSS THE SEA OF TIME", "release_year", "1995" ], [ "ALICE IN WONDERLAND", "has_genre", "ADVENTURE" ], [ "ALICE IN WONDERLAND", "release_year", "1951" ], [ "ARABIAN NIGHTS", "has_genre", "ADVENTURE" ], [ "ARABIAN NIGHTS", "in_language", "ITALIAN" ], [ "BALTO", "has_genre", "ADVENTURE" ], [ "BALTO", "release_year", "1995" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "in_language", "ITALIAN" ], [ "BEYOND THE CLOUDS", "in_language", "ITALIAN" ], [ "BEYOND THE CLOUDS", "release_year", "1995" ], [ "BUSHWHACKED", "has_genre", "ADVENTURE" ], [ "BUSHWHACKED", "release_year", "1995" ], [ "CAPTAIN HORATIO HORNBLOWER R.N.", "has_genre", "ADVENTURE" ], [ "CAPTAIN HORATIO HORNBLOWER R.N.", "release_year", "1951" ], [ "CONGO", "has_genre", "ADVENTURE" ], [ "CONGO", "release_year", "1995" ], [ "CRY, THE BELOVED COUNTRY", "release_year", "1951" ], [ "CRY, THE BELOVED COUNTRY", "release_year", "1995" ], [ "CUT AND RUN", "has_genre", "ADVENTURE" ], [ "CUT AND RUN", "in_language", "ITALIAN" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "release_year", "1995" ], [ "JUMANJI", "has_genre", "ADVENTURE" ], [ "JUMANJI", "has_tags", "ADVENTURE" ], [ "JUMANJI", "release_year", "1995" ], [ "LAST OF THE DOGMEN", "has_genre", "ADVENTURE" ], [ "LAST OF THE DOGMEN", "release_year", "1995" ], [ "MIRACLE IN MILAN", "in_language", "ITALIAN" ], [ "MIRACLE IN MILAN", "release_year", "1951" ], [ "MORTAL KOMBAT", "has_genre", "ADVENTURE" ], [ "MORTAL KOMBAT", "release_year", "1995" ], [ "ROB ROY", "has_genre", "ADVENTURE" ], [ "ROB ROY", "release_year", "1995" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "in_language", "ITALIAN" ], [ "STARCRASH", "has_genre", "ADVENTURE" ], [ "STARCRASH", "in_language", "ITALIAN" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "in_language", "ITALIAN" ], [ "TALL TALE", "has_genre", "ADVENTURE" ], [ "TALL TALE", "release_year", "1995" ], [ "TEN TALL MEN", "has_genre", "ADVENTURE" ], [ "TEN TALL MEN", "release_year", "1951" ], [ "THE AFRICAN QUEEN", "has_genre", "ADVENTURE" ], [ "THE AFRICAN QUEEN", "has_tags", "ADVENTURE" ], [ "THE AFRICAN QUEEN", "release_year", "1951" ], [ "THE AMAZING PANDA ADVENTURE", "has_genre", "ADVENTURE" ], [ "THE AMAZING PANDA ADVENTURE", "release_year", "1995" ], [ "THE GREAT MOUSE DETECTIVE", "has_genre", "ADVENTURE" ], [ "THE GREAT MOUSE DETECTIVE", "has_tags", "DISNEY" ], [ "THE GREAT MOUSE DETECTIVE", "has_tags", "MOUSE" ], [ "THE HORSEMAN ON THE ROOF", "has_genre", "ADVENTURE" ], [ "THE HORSEMAN ON THE ROOF", "in_language", "ITALIAN" ], [ "THE HORSEMAN ON THE ROOF", "release_year", "1995" ], [ "THE INDIAN IN THE CUPBOARD", "has_genre", "ADVENTURE" ], [ "THE INDIAN IN THE CUPBOARD", "release_year", "1995" ], [ "THE RESCUERS", "has_genre", "ADVENTURE" ], [ "THE RESCUERS", "has_tags", "DISNEY" ], [ "THE RESCUERS", "has_tags", "MOUSE" ], [ "THE STAR MAKER", "in_language", "ITALIAN" ], [ "THE STAR MAKER", "release_year", "1995" ], [ "TOM AND HUCK", "has_genre", "ADVENTURE" ], [ "TOM AND HUCK", "release_year", "1995" ], [ "TOY STORY", "has_genre", "ADVENTURE" ], [ "TOY STORY", "has_tags", "ADVENTURE" ], [ "TOY STORY", "release_year", "1995" ], [ "ULYSSES", "has_genre", "ADVENTURE" ], [ "ULYSSES", "in_language", "ITALIAN" ], [ "WHITE FANG", "has_genre", "ADVENTURE" ], [ "WHITE FANG", "in_language", "ITALIAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7158, 1958 35935, 2002 36647, 8 WOMEN 14372, 9/11 20458, AFTER TILLER 7292, BOND GIRLS ARE FOREVER 17464, BOWLING FOR COLUMBINE 15986, BUS 174 10349, CHICAGO 20977, DAHMER 12841, DOCUMENTARY 22198, I WANT TO LIVE! 13825, INSOMNIA 3487, MINORITY REPORT 28476, MURDER 1128, NICOLAS CAGE 22991, OUT OF THE BLUE 13701, PRISONER OF PARADISE 21740, SEARCHING FOR DEBRA WINGER 7083, SONNY 8600, STANDING IN THE SHADOWS OF MOTOWN 20901, THE BACKYARD 30121, THE FROZEN GROUND 20850, THE QUIET AMERICAN 39950, THE TRIALS OF HENRY KISSINGER 25405, WINDTALKERS src, edge_attr, dst 36647, has_tags, 28476 36647, release_year, 35935 14372, has_genre, 12841 14372, release_year, 35935 20458, has_genre, 12841 7292, has_genre, 12841 7292, release_year, 35935 17464, has_genre, 12841 17464, has_tags, 12841 17464, release_year, 35935 15986, has_genre, 12841 15986, has_tags, 12841 15986, release_year, 35935 10349, has_tags, 28476 10349, release_year, 35935 20977, has_tags, 28476 20977, release_year, 35935 22198, has_tags, 28476 22198, release_year, 7158 13825, has_tags, 28476 13825, release_year, 35935 3487, has_tags, 28476 3487, release_year, 35935 22991, has_genre, 12841 22991, release_year, 35935 13701, has_genre, 12841 13701, release_year, 35935 21740, has_genre, 12841 21740, release_year, 35935 7083, directed_by, 1128 7083, has_tags, 1128 7083, release_year, 35935 8600, has_genre, 12841 8600, release_year, 35935 20901, has_genre, 12841 20901, release_year, 35935 30121, has_tags, 28476 30121, starred_actors, 1128 20850, release_year, 7158 20850, release_year, 35935 39950, has_genre, 12841 39950, has_tags, 12841 39950, release_year, 35935 25405, has_tags, 1128 25405, release_year, 35935 25405, starred_actors, 1128 Question: In what context are AFTER TILLER, I WANT TO LIVE!, and SONNY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AFTER TILLER", "I WANT TO LIVE!", "SONNY" ], "valid_edges": [ [ "8 WOMEN", "has_tags", "MURDER" ], [ "8 WOMEN", "release_year", "2002" ], [ "9/11", "has_genre", "DOCUMENTARY" ], [ "9/11", "release_year", "2002" ], [ "AFTER TILLER", "has_genre", "DOCUMENTARY" ], [ "BOND GIRLS ARE FOREVER", "has_genre", "DOCUMENTARY" ], [ "BOND GIRLS ARE FOREVER", "release_year", "2002" ], [ "BOWLING FOR COLUMBINE", "has_genre", "DOCUMENTARY" ], [ "BOWLING FOR COLUMBINE", "has_tags", "DOCUMENTARY" ], [ "BOWLING FOR COLUMBINE", "release_year", "2002" ], [ "BUS 174", "has_genre", "DOCUMENTARY" ], [ "BUS 174", "has_tags", "DOCUMENTARY" ], [ "BUS 174", "release_year", "2002" ], [ "CHICAGO", "has_tags", "MURDER" ], [ "CHICAGO", "release_year", "2002" ], [ "DAHMER", "has_tags", "MURDER" ], [ "DAHMER", "release_year", "2002" ], [ "I WANT TO LIVE!", "has_tags", "MURDER" ], [ "I WANT TO LIVE!", "release_year", "1958" ], [ "INSOMNIA", "has_tags", "MURDER" ], [ "INSOMNIA", "release_year", "2002" ], [ "MINORITY REPORT", "has_tags", "MURDER" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "OUT OF THE BLUE", "has_genre", "DOCUMENTARY" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PRISONER OF PARADISE", "has_genre", "DOCUMENTARY" ], [ "PRISONER OF PARADISE", "release_year", "2002" ], [ "SEARCHING FOR DEBRA WINGER", "has_genre", "DOCUMENTARY" ], [ "SEARCHING FOR DEBRA WINGER", "release_year", "2002" ], [ "SONNY", "directed_by", "NICOLAS CAGE" ], [ "SONNY", "has_tags", "NICOLAS CAGE" ], [ "SONNY", "release_year", "2002" ], [ "STANDING IN THE SHADOWS OF MOTOWN", "has_genre", "DOCUMENTARY" ], [ "STANDING IN THE SHADOWS OF MOTOWN", "release_year", "2002" ], [ "THE BACKYARD", "has_genre", "DOCUMENTARY" ], [ "THE BACKYARD", "release_year", "2002" ], [ "THE FROZEN GROUND", "has_tags", "MURDER" ], [ "THE FROZEN GROUND", "starred_actors", "NICOLAS CAGE" ], [ "THE QUIET AMERICAN", "release_year", "1958" ], [ "THE QUIET AMERICAN", "release_year", "2002" ], [ "THE TRIALS OF HENRY KISSINGER", "has_genre", "DOCUMENTARY" ], [ "THE TRIALS OF HENRY KISSINGER", "has_tags", "DOCUMENTARY" ], [ "THE TRIALS OF HENRY KISSINGER", "release_year", "2002" ], [ "WINDTALKERS", "has_tags", "NICOLAS CAGE" ], [ "WINDTALKERS", "release_year", "2002" ], [ "WINDTALKERS", "starred_actors", "NICOLAS CAGE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 27261, 2009 30146, A CHRISTMAS CAROL 4681, A SIMPLE WISH 25570, BEAUTY AND THE BEAST 4197, BLUEBEARD 29177, BOOTY CALL 39861, CINDERELLA 35896, CORALINE 30123, DORIAN GRAY 24303, DRAGONQUEST 36066, FANTASY 4796, HARRY POTTER AND THE HALF-BLOOD PRINCE 35174, INK 26171, KULL THE CONQUEROR 8536, MALICE IN WONDERLAND 21686, MOONLIGHT SERENADE 18584, PRINCESS MONONOKE 16482, RICKY 4314, SOLOMON KANE 13858, SOPHIE'S REVENGE 2584, THE ADVENTURES OF BARON MUNCHAUSEN 8387, THE BLACK WATERS OF ECHO'S POND 23333, THE HOLE 5081, THE IMAGINARIUM OF DOCTOR PARNASSUS 2336, THE INVENTION OF LYING 25924, THE PRINCESS AND THE FROG 11925, TWILIGHT OF THE ICE NYMPHS 4814, WARRIORS OF VIRTUE src, edge_attr, dst 30146, has_genre, 36066 30146, release_year, 14259 30146, release_year, 27261 4681, has_genre, 36066 4681, has_tags, 36066 4681, release_year, 14259 25570, has_genre, 36066 25570, has_tags, 36066 25570, release_year, 27261 4197, has_genre, 36066 4197, release_year, 27261 29177, release_year, 14259 39861, has_genre, 36066 39861, release_year, 14259 35896, has_genre, 36066 35896, has_tags, 36066 35896, release_year, 27261 30123, has_genre, 36066 30123, release_year, 27261 24303, has_genre, 36066 24303, has_tags, 36066 24303, release_year, 27261 4796, has_genre, 36066 4796, has_tags, 36066 4796, release_year, 27261 35174, has_genre, 36066 35174, release_year, 27261 26171, has_genre, 36066 26171, release_year, 14259 8536, has_genre, 36066 8536, release_year, 27261 21686, release_year, 14259 21686, release_year, 27261 18584, has_genre, 36066 18584, has_tags, 36066 18584, release_year, 14259 16482, has_genre, 36066 16482, release_year, 27261 4314, has_genre, 36066 4314, has_tags, 36066 4314, release_year, 27261 13858, release_year, 27261 2584, has_genre, 36066 2584, has_tags, 36066 8387, has_genre, 36066 8387, release_year, 27261 23333, has_genre, 36066 23333, release_year, 27261 5081, has_genre, 36066 5081, has_tags, 36066 5081, release_year, 27261 2336, has_genre, 36066 2336, release_year, 27261 25924, has_genre, 36066 25924, release_year, 27261 11925, has_genre, 36066 11925, release_year, 14259 4814, has_genre, 36066 4814, release_year, 14259 Question: For what reason are BOOTY CALL, SOPHIE'S REVENGE, and THE ADVENTURES OF BARON MUNCHAUSEN associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BOOTY CALL", "SOPHIE'S REVENGE", "THE ADVENTURES OF BARON MUNCHAUSEN" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "FANTASY" ], [ "A CHRISTMAS CAROL", "release_year", "1997" ], [ "A CHRISTMAS CAROL", "release_year", "2009" ], [ "A SIMPLE WISH", "has_genre", "FANTASY" ], [ "A SIMPLE WISH", "has_tags", "FANTASY" ], [ "A SIMPLE WISH", "release_year", "1997" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "release_year", "2009" ], [ "BLUEBEARD", "has_genre", "FANTASY" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BOOTY CALL", "release_year", "1997" ], [ "CINDERELLA", "has_genre", "FANTASY" ], [ "CINDERELLA", "release_year", "1997" ], [ "CORALINE", "has_genre", "FANTASY" ], [ "CORALINE", "has_tags", "FANTASY" ], [ "CORALINE", "release_year", "2009" ], [ "DORIAN GRAY", "has_genre", "FANTASY" ], [ "DORIAN GRAY", "release_year", "2009" ], [ "DRAGONQUEST", "has_genre", "FANTASY" ], [ "DRAGONQUEST", "has_tags", "FANTASY" ], [ "DRAGONQUEST", "release_year", "2009" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "has_genre", "FANTASY" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "has_tags", "FANTASY" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "release_year", "2009" ], [ "INK", "has_genre", "FANTASY" ], [ "INK", "release_year", "2009" ], [ "KULL THE CONQUEROR", "has_genre", "FANTASY" ], [ "KULL THE CONQUEROR", "release_year", "1997" ], [ "MALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "MALICE IN WONDERLAND", "release_year", "2009" ], [ "MOONLIGHT SERENADE", "release_year", "1997" ], [ "MOONLIGHT SERENADE", "release_year", "2009" ], [ "PRINCESS MONONOKE", "has_genre", "FANTASY" ], [ "PRINCESS MONONOKE", "has_tags", "FANTASY" ], [ "PRINCESS MONONOKE", "release_year", "1997" ], [ "RICKY", "has_genre", "FANTASY" ], [ "RICKY", "release_year", "2009" ], [ "SOLOMON KANE", "has_genre", "FANTASY" ], [ "SOLOMON KANE", "has_tags", "FANTASY" ], [ "SOLOMON KANE", "release_year", "2009" ], [ "SOPHIE'S REVENGE", "release_year", "2009" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "FANTASY" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_tags", "FANTASY" ], [ "THE BLACK WATERS OF ECHO'S POND", "has_genre", "FANTASY" ], [ "THE BLACK WATERS OF ECHO'S POND", "release_year", "2009" ], [ "THE HOLE", "has_genre", "FANTASY" ], [ "THE HOLE", "release_year", "2009" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "has_genre", "FANTASY" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "has_tags", "FANTASY" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "release_year", "2009" ], [ "THE INVENTION OF LYING", "has_genre", "FANTASY" ], [ "THE INVENTION OF LYING", "release_year", "2009" ], [ "THE PRINCESS AND THE FROG", "has_genre", "FANTASY" ], [ "THE PRINCESS AND THE FROG", "release_year", "2009" ], [ "TWILIGHT OF THE ICE NYMPHS", "has_genre", "FANTASY" ], [ "TWILIGHT OF THE ICE NYMPHS", "release_year", "1997" ], [ "WARRIORS OF VIRTUE", "has_genre", "FANTASY" ], [ "WARRIORS OF VIRTUE", "release_year", "1997" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 5423, A LATE QUARTET 32632, A ROYAL AFFAIR 20562, A THOUSAND WORDS 21800, ABOUT CHERRY 29800, ACE ATTORNEY 30332, AMOUR 36963, ANNA KARENINA 24708, ANY DAY NOW 22078, ARBITRAGE 10277, ARGO 13686, ARTHUR NEWMAN 7302, AS COOL AS I AM 9695, AT ANY PRICE 31449, BARABBAS 38263, BARBARA 23994, BARFI! 26783, BE KIND REWIND 30581, BEASTS OF THE SOUTHERN WILD 37191, BEING FLYNN 28199, BEL AMI 32770, BEST MAN DOWN 14594, BEYOND THE HILLS 890, BIG MIRACLE 36071, BLACKBIRD 39848, BLUE LIKE JAZZ 22284, BOY EATING THE BIRD'S FOOD 27030, BROKEN 33711, CAESAR MUST DIE 32831, CALL GIRL 24707, CAMILLE REWINDS 12735, CHASING MAVERICKS 32450, CHEERFUL WEATHER FOR THE WEDDING 27338, CLIP 38925, CLOUD ATLAS 21016, COMPLIANCE 24757, CONSUMING SPIRITS 37589, COSMOPOLIS 19894, CRAVE 32797, DANGEROUS LIAISONS 10643, DARLING COMPANION 31694, DEADFALL 38977, DISCONNECT 36212, DRAMA 7480, EDEN 26106, END OF WATCH 32892, ENGLISH VINGLISH 6394, EXCISION 19570, FAREWELL, MY QUEEN 39636, FILL THE VOID 5563, FLIGHT 12314, FOR ELLEN 7740, FOREIGN LETTERS 11672, FOREVER AMBER 15473, FORGETTING THE GIRL 6076, FRANCES HA 24535, GAME CHANGE 2427, GIRL IN PROGRESS 32380, GOSSIP 5647, HANNAH ARENDT 3917, HELLO HERMAN 22793, HEROINE 27350, HITCHCOCK 3030, HOLY MOTORS 35319, HOPE SPRINGS 35625, HUMAN NATURE 37844, HYDE PARK ON HUDSON 19154, I BELONG 38589, I DO 32376, IMAGINE 26911, IN THE FOG 24025, INESCAPABLE 39536, JAMES MARSDEN 6301, JAYNE MANSFIELD'S CAR 22087, JEROME CADY 5418, K-11 12835, KAUWBOY 26232, KEEP THE LIGHTS ON 3103, LAURENCE ANYWAYS 1418, LAWLESS 14601, LES MISÉRABLES 14931, LIBERAL ARTS 39727, LIFE OF PI 36020, LIKE SOMEONE IN LOVE 47, LINCOLN 17372, LOL 34517, LUV 35871, MAGIC MIKE 13801, MARFA GIRL 34611, ME AND YOU 37973, MICHEL GONDRY 31735, MIDDLE OF NOWHERE 39165, MUD 19118, MUSEUM HOURS 24915, MY WAY 26089, NAKED HARBOUR 25504, NEIGHBORING SOUNDS 8107, NO 20503, NOBODY WALKS 17532, NOT FADE AWAY 17263, NOW IS GOOD 21677, ON THE ROAD 38602, OUR CHILDREN 8523, OUT IN THE DARK 31312, PEOPLE LIKE US 15815, POST TENEBRAS LUX 11253, PROMISED LAND 11237, PURGE 25023, QUARTET 35746, REALITY 33501, RENOIR 11839, REVENGE FOR JOLLY! 12597, RUBY SPARKS 30316, RUST AND BONE 35808, SAFE 17168, SEEKING A FRIEND FOR THE END OF THE WORLD 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 28583, SHADOW DANCER 34584, SILVER LININGS PLAYBOOK 7174, SISTER 39426, SMASHED 28026, SOMEBODY UP THERE LIKES ME 33759, SOMETHING IN THE AIR 17346, SPRING BREAKERS 17608, STARLET 39286, STILL MINE 40067, STOLEN 25002, STRUCK BY LIGHTNING 3038, STUCK IN LOVE 18335, TABU 19501, THANKS FOR SHARING 3885, THE ARTIST AND THE MODEL 19623, THE BATTERY 29460, THE BEST OF ME 24441, THE BROKEN CIRCLE BREAKDOWN 38175, THE CITIZEN 6644, THE COMEDY 2399, THE DEEP 10295, THE END OF LOVE 27103, THE FITZGERALD FAMILY CHRISTMAS 14688, THE FLOATING CASTLE 35267, THE FORGER 16929, THE GIRL 15980, THE GUILT TRIP 9328, THE HUNT 38614, THE IMPOSSIBLE 22800, THE LESSER BLESSED 33948, THE LETTER 4984, THE LUCKY ONE 23191, THE MAGIC OF BELLE ISLE 24652, THE MAN WHO LAUGHS 17964, THE MASTER 15798, THE ODD LIFE OF TIMOTHY GREEN 28735, THE OTHER SON 1195, THE PATIENCE STONE 7673, THE PERKS OF BEING A WALLFLOWER 2739, THE SAPPHIRES 27064, THE SCAPEGOAT 8650, THE SESSIONS 37915, THE STORY OF LUKE 14524, THE SWEENEY 12086, THE VOW 26797, THE WALL 4614, THE WE AND THE I 3437, THE WOMAN IN BLACK 15504, THE WORDS 266, THREE WORLDS 5352, THY WOMB 9918, TO THE WONDER 17451, TROUBLE WITH THE CURVE 13359, TWO LIVES 10305, UNCONDITIONAL 30056, WAR WITCH 7030, WHAT IF... 24333, WHAT MAISIE KNEW 34118, WHAT TO EXPECT WHEN YOU'RE EXPECTING 21183, WHITE ELEPHANT 18608, WHITE FROG 36174, WINNING STREAK 26337, WON'T BACK DOWN 31040, XINGU 9052, YOSSI 16849, ZERO DARK THIRTY src, edge_attr, dst 5423, has_genre, 36212 5423, has_tags, 36212 5423, release_year, 658 32632, has_genre, 36212 32632, release_year, 658 20562, has_genre, 36212 20562, release_year, 658 21800, has_genre, 36212 21800, release_year, 658 29800, has_genre, 36212 29800, release_year, 658 30332, has_genre, 36212 30332, release_year, 658 36963, has_genre, 36212 36963, has_tags, 36212 36963, release_year, 658 24708, has_genre, 36212 24708, release_year, 658 22078, has_genre, 36212 22078, release_year, 658 10277, has_genre, 36212 10277, has_tags, 36212 10277, release_year, 658 13686, has_genre, 36212 13686, release_year, 658 7302, has_genre, 36212 7302, starred_actors, 39536 9695, has_genre, 36212 9695, release_year, 658 31449, has_genre, 36212 31449, release_year, 658 38263, has_genre, 36212 38263, release_year, 658 23994, has_genre, 36212 23994, release_year, 658 26783, directed_by, 37973 26783, has_genre, 36212 26783, has_tags, 37973 26783, written_by, 37973 30581, has_genre, 36212 30581, release_year, 658 37191, has_genre, 36212 37191, release_year, 658 28199, has_genre, 36212 28199, release_year, 658 32770, has_genre, 36212 32770, release_year, 658 14594, has_genre, 36212 14594, release_year, 658 890, has_genre, 36212 890, release_year, 658 36071, has_genre, 36212 36071, release_year, 658 39848, has_genre, 36212 39848, release_year, 658 22284, has_genre, 36212 22284, release_year, 658 27030, has_genre, 36212 27030, release_year, 658 33711, has_genre, 36212 33711, release_year, 658 32831, has_genre, 36212 32831, release_year, 658 24707, has_genre, 36212 24707, release_year, 658 12735, has_genre, 36212 12735, release_year, 658 32450, has_genre, 36212 32450, release_year, 658 27338, has_genre, 36212 27338, release_year, 658 38925, has_genre, 36212 38925, has_tags, 36212 38925, release_year, 658 21016, has_genre, 36212 21016, release_year, 658 24757, has_genre, 36212 24757, release_year, 658 37589, has_genre, 36212 37589, release_year, 658 19894, has_genre, 36212 19894, release_year, 658 32797, has_genre, 36212 32797, release_year, 658 10643, has_genre, 36212 10643, release_year, 658 31694, has_genre, 36212 31694, release_year, 658 38977, has_genre, 36212 38977, has_tags, 36212 38977, release_year, 658 7480, has_genre, 36212 7480, release_year, 658 26106, has_genre, 36212 26106, release_year, 658 32892, has_genre, 36212 32892, release_year, 658 6394, has_genre, 36212 6394, release_year, 658 19570, has_genre, 36212 19570, release_year, 658 39636, has_genre, 36212 39636, release_year, 658 5563, has_genre, 36212 5563, release_year, 658 12314, has_genre, 36212 12314, release_year, 658 7740, has_genre, 36212 7740, release_year, 658 11672, has_genre, 36212 11672, written_by, 22087 15473, has_genre, 36212 15473, release_year, 658 6076, has_genre, 36212 6076, release_year, 658 24535, has_genre, 36212 24535, release_year, 658 2427, has_genre, 36212 2427, release_year, 658 32380, has_genre, 36212 32380, has_tags, 32380 32380, starred_actors, 39536 5647, has_genre, 36212 5647, release_year, 658 3917, has_genre, 36212 3917, release_year, 658 22793, has_genre, 36212 22793, release_year, 658 27350, has_genre, 36212 27350, release_year, 658 3030, has_genre, 36212 3030, release_year, 658 35319, has_genre, 36212 35319, release_year, 658 35625, directed_by, 37973 35625, has_genre, 36212 35625, has_tags, 37973 37844, has_genre, 36212 37844, release_year, 658 19154, has_genre, 36212 19154, release_year, 658 38589, has_genre, 36212 38589, release_year, 658 32376, has_genre, 36212 32376, release_year, 658 26911, has_genre, 36212 26911, release_year, 658 24025, has_genre, 36212 24025, release_year, 658 6301, has_genre, 36212 6301, release_year, 658 5418, has_genre, 36212 5418, release_year, 658 12835, has_genre, 36212 12835, release_year, 658 26232, has_genre, 36212 26232, release_year, 658 3103, has_genre, 36212 3103, release_year, 658 1418, has_genre, 36212 1418, has_tags, 36212 1418, release_year, 658 14601, has_genre, 36212 14601, release_year, 658 14931, has_genre, 36212 14931, release_year, 658 39727, has_genre, 36212 39727, release_year, 658 36020, has_genre, 36212 36020, release_year, 658 47, has_genre, 36212 47, has_tags, 36212 47, release_year, 658 17372, has_genre, 36212 17372, release_year, 658 34517, has_genre, 36212 34517, release_year, 658 35871, has_genre, 36212 35871, release_year, 658 13801, has_genre, 36212 13801, release_year, 658 34611, has_genre, 36212 34611, release_year, 658 31735, has_genre, 36212 31735, release_year, 658 39165, has_genre, 36212 39165, release_year, 658 19118, has_genre, 36212 19118, release_year, 658 24915, has_genre, 36212 24915, release_year, 658 26089, has_genre, 36212 26089, release_year, 658 25504, has_genre, 36212 25504, release_year, 658 8107, has_genre, 36212 8107, release_year, 658 20503, has_genre, 36212 20503, release_year, 658 17532, has_genre, 36212 17532, release_year, 658 17263, has_genre, 36212 17263, release_year, 658 21677, has_genre, 36212 21677, release_year, 658 38602, has_genre, 36212 38602, release_year, 658 8523, has_genre, 36212 8523, release_year, 658 31312, has_genre, 36212 31312, has_tags, 36212 31312, release_year, 658 15815, has_genre, 36212 15815, release_year, 658 11253, has_genre, 36212 11253, release_year, 658 11237, has_genre, 36212 11237, release_year, 658 25023, has_genre, 36212 25023, release_year, 658 35746, has_genre, 36212 35746, release_year, 658 33501, has_genre, 36212 33501, release_year, 658 11839, has_genre, 36212 11839, release_year, 658 12597, has_genre, 36212 12597, release_year, 658 30316, has_genre, 36212 30316, release_year, 658 35808, has_genre, 36212 35808, release_year, 658 17168, has_genre, 36212 17168, release_year, 658 25060, has_genre, 36212 25060, release_year, 658 28583, has_genre, 36212 28583, release_year, 658 34584, has_genre, 36212 34584, has_tags, 36212 34584, release_year, 658 7174, has_genre, 36212 7174, release_year, 658 39426, has_genre, 36212 39426, release_year, 658 28026, has_genre, 36212 28026, release_year, 658 33759, has_genre, 36212 33759, release_year, 658 17346, has_genre, 36212 17346, release_year, 658 17608, has_genre, 36212 17608, release_year, 658 39286, has_genre, 36212 39286, release_year, 658 40067, has_genre, 36212 40067, release_year, 658 25002, has_genre, 36212 25002, release_year, 658 3038, has_genre, 36212 3038, release_year, 658 18335, has_genre, 36212 18335, release_year, 658 19501, has_genre, 36212 19501, release_year, 658 3885, has_genre, 36212 3885, release_year, 658 19623, has_genre, 36212 19623, release_year, 658 29460, has_genre, 36212 29460, starred_actors, 39536 24441, has_genre, 36212 24441, has_tags, 36212 24441, release_year, 658 38175, has_genre, 36212 38175, release_year, 658 6644, has_genre, 36212 6644, release_year, 658 2399, has_genre, 36212 2399, release_year, 658 10295, has_genre, 36212 10295, release_year, 658 27103, has_genre, 36212 27103, release_year, 658 14688, has_genre, 36212 14688, release_year, 658 35267, has_genre, 36212 35267, release_year, 658 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release_year, 658 12086, has_genre, 36212 12086, release_year, 658 26797, has_genre, 36212 26797, release_year, 658 4614, directed_by, 37973 4614, has_genre, 36212 4614, release_year, 658 4614, written_by, 37973 3437, has_genre, 36212 3437, release_year, 658 15504, has_genre, 36212 15504, release_year, 658 266, has_genre, 36212 266, release_year, 658 5352, has_genre, 36212 5352, release_year, 658 9918, has_genre, 36212 9918, release_year, 658 17451, has_genre, 36212 17451, release_year, 658 13359, has_genre, 36212 13359, release_year, 658 10305, has_genre, 36212 10305, release_year, 658 30056, has_genre, 36212 30056, release_year, 658 7030, has_genre, 36212 7030, release_year, 658 24333, has_genre, 36212 24333, release_year, 658 34118, has_genre, 36212 34118, release_year, 658 21183, has_genre, 36212 21183, release_year, 658 18608, has_genre, 36212 18608, release_year, 658 36174, has_genre, 36212 36174, release_year, 658 26337, has_genre, 36212 26337, release_year, 658 31040, has_genre, 36212 31040, release_year, 658 9052, has_genre, 36212 9052, release_year, 658 16849, has_genre, 36212 16849, release_year, 658 Question: In what context are JAMES MARSDEN, JEROME CADY, and THE WE AND THE I connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JAMES MARSDEN", "JEROME CADY", "THE WE AND THE I" ], "valid_edges": [ [ "A LATE QUARTET", "has_genre", "DRAMA" ], [ "A LATE QUARTET", "has_tags", "DRAMA" ], [ "A LATE QUARTET", "release_year", "2012" ], [ "A ROYAL AFFAIR", "has_genre", "DRAMA" ], [ "A ROYAL AFFAIR", "release_year", "2012" ], [ "A THOUSAND WORDS", "has_genre", "DRAMA" ], [ "A THOUSAND WORDS", "release_year", "2012" ], [ "ABOUT CHERRY", "has_genre", "DRAMA" ], [ "ABOUT CHERRY", "release_year", "2012" ], [ "ACE ATTORNEY", "has_genre", "DRAMA" ], [ "ACE ATTORNEY", "release_year", "2012" ], [ "AMOUR", "has_genre", "DRAMA" ], [ "AMOUR", "release_year", "2012" ], [ "ANNA KARENINA", "has_genre", "DRAMA" ], [ "ANNA KARENINA", "has_tags", "DRAMA" ], [ "ANNA KARENINA", "release_year", "2012" ], [ "ANY DAY NOW", "has_genre", "DRAMA" ], [ "ANY DAY NOW", "release_year", "2012" ], [ "ARBITRAGE", "has_genre", "DRAMA" ], [ "ARBITRAGE", 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"2012" ], [ "CHASING MAVERICKS", "has_genre", "DRAMA" ], [ "CHASING MAVERICKS", "release_year", "2012" ], [ "CHEERFUL WEATHER FOR THE WEDDING", "has_genre", "DRAMA" ], [ "CHEERFUL WEATHER FOR THE WEDDING", "release_year", "2012" ], [ "CLIP", "has_genre", "DRAMA" ], [ "CLIP", "release_year", "2012" ], [ "CLOUD ATLAS", "has_genre", "DRAMA" ], [ "CLOUD ATLAS", "has_tags", "DRAMA" ], [ "CLOUD ATLAS", "release_year", "2012" ], [ "COMPLIANCE", "has_genre", "DRAMA" ], [ "COMPLIANCE", "release_year", "2012" ], [ "CONSUMING SPIRITS", "has_genre", "DRAMA" ], [ "CONSUMING SPIRITS", "release_year", "2012" ], [ "COSMOPOLIS", "has_genre", "DRAMA" ], [ "COSMOPOLIS", "release_year", "2012" ], [ "CRAVE", "has_genre", "DRAMA" ], [ "CRAVE", "release_year", "2012" ], [ "DANGEROUS LIAISONS", "has_genre", "DRAMA" ], [ "DANGEROUS LIAISONS", "release_year", "2012" ], [ "DARLING COMPANION", "has_genre", "DRAMA" ], [ "DARLING COMPANION", "release_year", "2012" ], [ "DEADFALL", "has_genre", "DRAMA" ], [ 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"ME AND YOU", "release_year", "2012" ], [ "MIDDLE OF NOWHERE", "has_genre", "DRAMA" ], [ "MIDDLE OF NOWHERE", "release_year", "2012" ], [ "MUD", "has_genre", "DRAMA" ], [ "MUD", "release_year", "2012" ], [ "MUSEUM HOURS", "has_genre", "DRAMA" ], [ "MUSEUM HOURS", "release_year", "2012" ], [ "MY WAY", "has_genre", "DRAMA" ], [ "MY WAY", "release_year", "2012" ], [ "NAKED HARBOUR", "has_genre", "DRAMA" ], [ "NAKED HARBOUR", "release_year", "2012" ], [ "NEIGHBORING SOUNDS", "has_genre", "DRAMA" ], [ "NEIGHBORING SOUNDS", "release_year", "2012" ], [ "NO", "has_genre", "DRAMA" ], [ "NO", "release_year", "2012" ], [ "NOBODY WALKS", "has_genre", "DRAMA" ], [ "NOBODY WALKS", "release_year", "2012" ], [ "NOT FADE AWAY", "has_genre", "DRAMA" ], [ "NOT FADE AWAY", "release_year", "2012" ], [ "NOW IS GOOD", "has_genre", "DRAMA" ], [ "NOW IS GOOD", "release_year", "2012" ], [ "ON THE ROAD", "has_genre", "DRAMA" ], [ "ON THE ROAD", "release_year", "2012" ], [ "OUR CHILDREN", "has_genre", "DRAMA" ], [ "OUR CHILDREN", "release_year", "2012" ], [ "OUT IN THE DARK", "has_genre", "DRAMA" ], [ "OUT IN THE DARK", "release_year", "2012" ], [ "PEOPLE LIKE US", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_tags", "DRAMA" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "POST TENEBRAS LUX", "has_genre", "DRAMA" ], [ "POST TENEBRAS LUX", "release_year", "2012" ], [ "PROMISED LAND", "has_genre", "DRAMA" ], [ "PROMISED LAND", "release_year", "2012" ], [ "PURGE", "has_genre", "DRAMA" ], [ "PURGE", "release_year", "2012" ], [ "QUARTET", "has_genre", "DRAMA" ], [ "QUARTET", "release_year", "2012" ], [ "REALITY", "has_genre", "DRAMA" ], [ "REALITY", "release_year", "2012" ], [ "RENOIR", "has_genre", "DRAMA" ], [ "RENOIR", "release_year", "2012" ], [ "REVENGE FOR JOLLY!", "has_genre", "DRAMA" ], [ "REVENGE FOR JOLLY!", "release_year", "2012" ], [ "RUBY SPARKS", "has_genre", "DRAMA" ], [ "RUBY SPARKS", "release_year", "2012" ], [ "RUST AND BONE", "has_genre", "DRAMA" ], [ "RUST AND BONE", "release_year", "2012" ], [ "SAFE", "has_genre", "DRAMA" ], [ "SAFE", "release_year", "2012" ], [ "SEEKING A FRIEND FOR THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "SEEKING A FRIEND FOR THE END OF THE WORLD", "release_year", "2012" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "has_genre", "DRAMA" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "release_year", "2012" ], [ "SHADOW DANCER", "has_genre", "DRAMA" ], [ "SHADOW DANCER", "release_year", "2012" ], [ "SILVER LININGS PLAYBOOK", "has_genre", "DRAMA" ], [ "SILVER LININGS PLAYBOOK", "has_tags", "DRAMA" ], [ "SILVER LININGS PLAYBOOK", "release_year", "2012" ], [ "SISTER", "has_genre", "DRAMA" ], [ "SISTER", "release_year", "2012" ], [ "SMASHED", "has_genre", "DRAMA" ], [ "SMASHED", "release_year", "2012" ], [ "SOMEBODY UP THERE LIKES ME", "has_genre", "DRAMA" ], [ "SOMEBODY UP THERE LIKES ME", "release_year", "2012" ], [ "SOMETHING IN THE AIR", "has_genre", "DRAMA" ], [ "SOMETHING IN THE AIR", "release_year", "2012" ], [ "SPRING 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"has_genre", "DRAMA" ], [ "THE BROKEN CIRCLE BREAKDOWN", "has_tags", "DRAMA" ], [ "THE BROKEN CIRCLE BREAKDOWN", "release_year", "2012" ], [ "THE CITIZEN", "has_genre", "DRAMA" ], [ "THE CITIZEN", "release_year", "2012" ], [ "THE COMEDY", "has_genre", "DRAMA" ], [ "THE COMEDY", "release_year", "2012" ], [ "THE DEEP", "has_genre", "DRAMA" ], [ "THE DEEP", "release_year", "2012" ], [ "THE END OF LOVE", "has_genre", "DRAMA" ], [ "THE END OF LOVE", "release_year", "2012" ], [ "THE FITZGERALD FAMILY CHRISTMAS", "has_genre", "DRAMA" ], [ "THE FITZGERALD FAMILY CHRISTMAS", "release_year", "2012" ], [ "THE FLOATING CASTLE", "has_genre", "DRAMA" ], [ "THE FLOATING CASTLE", "release_year", "2012" ], [ "THE FORGER", "has_genre", "DRAMA" ], [ "THE FORGER", "release_year", "2012" ], [ "THE GIRL", "has_genre", "DRAMA" ], [ "THE GIRL", "release_year", "2012" ], [ "THE GUILT TRIP", "has_genre", "DRAMA" ], [ "THE GUILT TRIP", "release_year", "2012" ], [ "THE HUNT", "has_genre", "DRAMA" ], [ "THE HUNT", "has_tags", "DRAMA" ], [ "THE HUNT", "release_year", "2012" ], [ "THE IMPOSSIBLE", "has_genre", "DRAMA" ], [ "THE IMPOSSIBLE", "has_tags", "DRAMA" ], [ "THE IMPOSSIBLE", "release_year", "2012" ], [ "THE LESSER BLESSED", "has_genre", "DRAMA" ], [ "THE LESSER BLESSED", "release_year", "2012" ], [ "THE LETTER", "has_genre", "DRAMA" ], [ "THE LETTER", "release_year", "2012" ], [ "THE LUCKY ONE", "has_genre", "DRAMA" ], [ "THE LUCKY ONE", "release_year", "2012" ], [ "THE MAGIC OF BELLE ISLE", "has_genre", "DRAMA" ], [ "THE MAGIC OF BELLE ISLE", "release_year", "2012" ], [ "THE MAN WHO LAUGHS", "has_genre", "DRAMA" ], [ "THE MAN WHO LAUGHS", "release_year", "2012" ], [ "THE MASTER", "has_genre", "DRAMA" ], [ "THE MASTER", "release_year", "2012" ], [ "THE ODD LIFE OF TIMOTHY GREEN", "has_genre", "DRAMA" ], [ "THE ODD LIFE OF TIMOTHY GREEN", "release_year", "2012" ], [ "THE OTHER SON", "has_genre", "DRAMA" ], [ "THE OTHER SON", "release_year", "2012" ], [ "THE PATIENCE STONE", "has_genre", "DRAMA" ], [ "THE PATIENCE STONE", "release_year", "2012" ], [ "THE PERKS OF BEING A WALLFLOWER", "has_genre", "DRAMA" ], [ "THE PERKS OF BEING A WALLFLOWER", "has_tags", "DRAMA" ], [ "THE PERKS OF BEING A WALLFLOWER", "release_year", "2012" ], [ "THE SAPPHIRES", "has_genre", "DRAMA" ], [ "THE SAPPHIRES", "release_year", "2012" ], [ "THE SCAPEGOAT", "has_genre", "DRAMA" ], [ "THE SCAPEGOAT", "release_year", "2012" ], [ "THE SESSIONS", "has_genre", "DRAMA" ], [ "THE SESSIONS", "has_tags", "DRAMA" ], [ "THE SESSIONS", "release_year", "2012" ], [ "THE STORY OF LUKE", "has_genre", "DRAMA" ], [ "THE STORY OF LUKE", "release_year", "2012" ], [ "THE SWEENEY", "has_genre", "DRAMA" ], [ "THE SWEENEY", "release_year", "2012" ], [ "THE VOW", "has_genre", "DRAMA" ], [ "THE VOW", "release_year", "2012" ], [ "THE WALL", "has_genre", "DRAMA" ], [ "THE WALL", "release_year", "2012" ], [ "THE WE AND THE I", "directed_by", "MICHEL GONDRY" ], [ "THE WE AND THE I", "has_genre", "DRAMA" ], [ "THE WE AND THE I", "release_year", "2012" ], [ "THE WE AND THE I", "written_by", "MICHEL GONDRY" ], [ "THE WOMAN IN BLACK", "has_genre", "DRAMA" ], [ "THE WOMAN IN BLACK", "release_year", "2012" ], [ "THE WORDS", "has_genre", "DRAMA" ], [ "THE WORDS", "release_year", "2012" ], [ "THREE WORLDS", "has_genre", "DRAMA" ], [ "THREE WORLDS", "release_year", "2012" ], [ "THY WOMB", "has_genre", "DRAMA" ], [ "THY WOMB", "release_year", "2012" ], [ "TO THE WONDER", "has_genre", "DRAMA" ], [ "TO THE WONDER", "release_year", "2012" ], [ "TROUBLE WITH THE CURVE", "has_genre", "DRAMA" ], [ "TROUBLE WITH THE CURVE", "release_year", "2012" ], [ "TWO LIVES", "has_genre", "DRAMA" ], [ "TWO LIVES", "release_year", "2012" ], [ "UNCONDITIONAL", "has_genre", "DRAMA" ], [ "UNCONDITIONAL", "release_year", "2012" ], [ "WAR WITCH", "has_genre", "DRAMA" ], [ "WAR WITCH", "release_year", "2012" ], [ "WHAT IF...", "has_genre", "DRAMA" ], [ "WHAT IF...", "release_year", "2012" ], [ "WHAT MAISIE KNEW", "has_genre", "DRAMA" ], [ "WHAT MAISIE KNEW", "release_year", "2012" ], [ "WHAT TO EXPECT WHEN YOU'RE EXPECTING", "has_genre", "DRAMA" ], [ "WHAT TO EXPECT WHEN YOU'RE EXPECTING", "release_year", "2012" ], [ "WHITE ELEPHANT", "has_genre", "DRAMA" ], [ "WHITE ELEPHANT", "release_year", "2012" ], [ "WHITE FROG", "has_genre", "DRAMA" ], [ "WHITE FROG", "release_year", "2012" ], [ "WINNING STREAK", "has_genre", "DRAMA" ], [ "WINNING STREAK", "release_year", "2012" ], [ "WON'T BACK DOWN", "has_genre", "DRAMA" ], [ "WON'T BACK DOWN", "release_year", "2012" ], [ "XINGU", "has_genre", "DRAMA" ], [ "XINGU", "release_year", "2012" ], [ "YOSSI", "has_genre", "DRAMA" ], [ "YOSSI", "release_year", "2012" ], [ "ZERO DARK THIRTY", "has_genre", "DRAMA" ], [ "ZERO DARK THIRTY", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 28171, 1986 18899, A BUCKET OF BLOOD 39750, ALIENS 18169, APRIL FOOL'S DAY 10045, BD-R 19826, BLACK DEATH 26014, BLOOD OF THE VAMPIRE 32620, BUBBA HO-TEP 24454, CARRIE 37912, CAT PEOPLE 28328, CAT'S EYE 5741, CHILDREN OF THE CORN 36535, CHOPPING MALL 24443, CHRISTINE 14884, CLASS OF NUKE 'EM HIGH 22349, CRAWLSPACE 30260, CREEPSHOW 19984, CREEPSHOW 2 6743, CRITTERS 25956, CUJO 4381, DEAD OF NIGHT 21213, DEADLY FRIEND 27143, DEMENTIA 13 31980, DEMONS 2 8381, DETOUR 23807, DOCTOR X 3154, DONOVAN'S BRAIN 34827, DR. JEKYLL AND MR. HYDE 36920, DRACULA HAS RISEN FROM THE GRAVE 37707, DRACULA'S DAUGHTER 35978, DREAMCATCHER 29503, EYE OF THE DEVIL 24540, EYES WITHOUT A FACE 32144, FRANKENSTEIN MUST BE DESTROYED 3270, FROM BEYOND 38609, GALAXY OF TERROR 30778, GOTHIC 12378, HANDS OF THE RIPPER 39972, HOLLOW MAN 5870, HORROR 22421, HORROR EXPRESS 10147, HOUSE 10955, HOUSE OF USHER 9686, HOUSE OF WAX 13070, INVADERS FROM MARS 24952, LINK 8851, LITTLE SHOP OF HORRORS 40127, MACABRE 17728, MAD LOVE 26370, MADHOUSE 20487, MARC BRANDEL 25643, MARK OF THE VAMPIRE 3129, MAXIMUM OVERDRIVE 7625, MISERY 20500, MONSTER IN THE CLOSET 18402, MOUNTAINTOP MOTEL MASSACRE 5420, MYRNA FAHEY 16462, MYSTERY OF THE WAX MUSEUM 11181, NIGHT OF THE CREEPS 17189, NIGHT OF THE DEMONS 9330, NIGHT OF THE LEPUS 32988, NIGHT OF THE LIVING DEAD 39105, NOMADS 32891, NOSFERATU 19017, PEEPING TOM 28917, PET SEMATARY 16004, PLANET TERROR 17526, PSYCHO III 3322, QUICKSILVER HIGHWAY 31164, RAWHEAD REX 5897, REPULSION 32894, RIDING THE BULLET 30671, SILVER BULLET 16247, SLEEPWALKERS 8436, SPIRITS OF THE DEAD 32367, STAGE FRIGHT 23284, STEPHEN KING 39265, STORAGE 24 34349, SVENGALI 5932, TERRORVISION 14072, THE ABOMINABLE DR. PHIBES 12781, THE ALLIGATOR PEOPLE 13151, THE BAD SEED 17361, THE BRAIN THAT WOULDN'T DIE 25829, THE CABINET OF DR. CALIGARI 31239, THE CAT AND THE CANARY 38676, THE CREEPING FLESH 24990, THE CURSE OF FRANKENSTEIN 25979, THE DARK HALF 26351, THE DEAD ZONE 38265, THE DEVIL-DOLL 32732, THE DOCTOR AND THE DEVILS 23327, THE FEARLESS VAMPIRE KILLERS 32392, THE FLY 28048, THE GHOST BREAKERS 14113, THE GHOUL 14382, THE GORGON 5813, THE HAND 25175, THE HAUNTED PALACE 11787, THE HAUNTING 31283, THE HOUND OF THE BASKERVILLES 22212, THE HOUSE THAT DRIPPED BLOOD 32595, THE HOWLING 15198, THE HUNCHBACK OF NOTRE DAME 29358, THE HUNGER 27780, THE INNOCENTS 34005, THE INVISIBLE MAN 10379, THE LAWNMOWER MAN 8623, THE LEGEND OF HELL HOUSE 33794, THE LITTLE SHOP OF HORRORS 29109, THE LODGER 26566, THE MANGLER 11243, THE MASQUE OF THE RED DEATH 33919, THE MIST 26820, THE MUMMY 40021, THE NIGHT FLIER 8727, THE PICTURE OF DORIAN GRAY 1565, THE PLAGUE OF THE ZOMBIES 18162, THE RAVEN 10186, THE REVENGE OF FRANKENSTEIN 1143, THE SEVENTH VICTIM 19018, THE SHINING 23847, THE STEPFORD WIVES 23260, THE SWARM 33991, THE TERROR 9715, THE TEXAS CHAINSAW MASSACRE 2 19823, THE UNKNOWN 22751, THE WICKER MAN 6833, THE WITCHES 3594, THEATRE OF BLOOD 14444, THEM! 7808, THINNER 1596, TORTURE GARDEN 17409, TRICK OR TREAT 29370, TROG 31252, V/H/S 36374, VILLAGE OF THE DAMNED 28352, WHITE ZOMBIE 36013, WITCHBOARD 6037, WITCHFINDER GENERAL src, edge_attr, dst 35747, has_genre, 5870 35747, has_tags, 5870 35747, has_tags, 23284 35747, written_by, 23284 18899, has_genre, 5870 18899, has_tags, 10045 39750, has_tags, 5870 39750, release_year, 28171 18169, has_genre, 5870 18169, release_year, 28171 19826, has_genre, 5870 19826, has_tags, 10045 26014, has_genre, 5870 26014, has_tags, 10045 32620, has_tags, 10045 32620, has_tags, 5870 24454, has_genre, 5870 24454, has_tags, 5870 24454, has_tags, 23284 24454, written_by, 23284 37912, has_genre, 5870 37912, has_tags, 10045 28328, has_genre, 5870 28328, has_tags, 23284 28328, written_by, 23284 5741, has_genre, 5870 5741, has_tags, 23284 5741, written_by, 23284 36535, has_genre, 5870 36535, release_year, 28171 24443, has_genre, 5870 24443, has_tags, 23284 24443, written_by, 23284 14884, has_genre, 5870 14884, release_year, 28171 22349, has_genre, 5870 22349, release_year, 28171 30260, has_genre, 5870 30260, written_by, 23284 19984, has_genre, 5870 19984, has_tags, 23284 19984, written_by, 23284 6743, has_genre, 5870 6743, release_year, 28171 25956, has_genre, 5870 25956, has_tags, 23284 25956, written_by, 23284 4381, has_genre, 5870 4381, has_tags, 10045 21213, has_genre, 5870 21213, release_year, 28171 27143, has_genre, 5870 27143, has_tags, 10045 31980, has_genre, 5870 31980, release_year, 28171 8381, has_genre, 5870 8381, has_tags, 10045 23807, has_genre, 5870 23807, has_tags, 10045 3154, has_genre, 5870 3154, has_tags, 10045 34827, has_genre, 5870 34827, has_tags, 10045 36920, has_genre, 5870 36920, has_tags, 10045 37707, has_genre, 5870 37707, has_tags, 10045 35978, has_genre, 5870 35978, has_tags, 23284 35978, written_by, 23284 29503, has_genre, 5870 29503, has_tags, 10045 24540, has_genre, 5870 24540, has_tags, 10045 32144, has_genre, 5870 32144, has_tags, 10045 3270, has_genre, 5870 3270, release_year, 28171 38609, has_genre, 5870 38609, has_tags, 10045 30778, has_genre, 5870 30778, release_year, 28171 12378, has_genre, 5870 12378, has_tags, 10045 39972, has_tags, 10045 39972, has_tags, 5870 22421, has_genre, 5870 22421, has_tags, 10045 10147, has_genre, 5870 10147, release_year, 28171 10955, has_genre, 5870 10955, has_tags, 10045 10955, has_tags, 5870 10955, starred_actors, 5420 9686, has_genre, 5870 9686, has_tags, 10045 13070, has_genre, 5870 13070, release_year, 28171 24952, has_genre, 5870 24952, release_year, 28171 8851, has_genre, 5870 8851, release_year, 28171 40127, has_genre, 5870 40127, has_tags, 10045 17728, has_genre, 5870 17728, has_tags, 10045 26370, has_genre, 5870 26370, has_tags, 10045 25643, has_genre, 5870 25643, has_tags, 10045 3129, directed_by, 23284 3129, has_genre, 5870 3129, has_tags, 10045 3129, has_tags, 23284 3129, release_year, 28171 3129, written_by, 23284 7625, has_tags, 5870 7625, has_tags, 23284 7625, written_by, 23284 20500, has_genre, 5870 20500, release_year, 28171 18402, has_genre, 5870 18402, release_year, 28171 16462, has_genre, 5870 16462, has_tags, 10045 11181, has_genre, 5870 11181, release_year, 28171 17189, has_genre, 5870 17189, has_tags, 10045 9330, has_genre, 5870 9330, has_tags, 10045 32988, has_genre, 5870 32988, has_tags, 10045 32988, has_tags, 5870 39105, has_genre, 5870 39105, release_year, 28171 32891, has_genre, 5870 32891, has_tags, 10045 19017, has_genre, 5870 19017, has_tags, 10045 28917, has_genre, 5870 28917, has_tags, 5870 28917, has_tags, 23284 28917, written_by, 23284 16004, has_genre, 5870 16004, has_tags, 10045 16004, has_tags, 5870 17526, has_genre, 5870 17526, release_year, 28171 3322, has_genre, 5870 3322, written_by, 23284 31164, has_genre, 5870 31164, release_year, 28171 5897, has_genre, 5870 5897, has_tags, 10045 32894, has_genre, 5870 32894, has_tags, 23284 32894, written_by, 23284 30671, has_genre, 5870 30671, has_tags, 23284 30671, written_by, 23284 16247, has_genre, 5870 16247, has_tags, 5870 16247, has_tags, 23284 16247, written_by, 23284 8436, has_genre, 5870 8436, has_tags, 10045 32367, has_genre, 5870 32367, has_tags, 10045 39265, has_genre, 5870 39265, has_tags, 10045 34349, has_genre, 5870 34349, has_tags, 10045 5932, has_genre, 5870 5932, release_year, 28171 14072, has_genre, 5870 14072, has_tags, 10045 14072, has_tags, 5870 12781, has_genre, 5870 12781, has_tags, 10045 13151, has_genre, 5870 13151, has_tags, 10045 17361, has_genre, 5870 17361, has_tags, 10045 25829, has_genre, 5870 25829, has_tags, 10045 31239, has_genre, 5870 31239, has_tags, 10045 38676, has_genre, 5870 38676, has_tags, 10045 24990, has_genre, 5870 24990, has_tags, 10045 24990, has_tags, 5870 25979, has_genre, 5870 25979, has_tags, 23284 25979, written_by, 23284 26351, has_genre, 5870 26351, has_tags, 23284 26351, written_by, 23284 38265, has_genre, 5870 38265, has_tags, 10045 32732, has_genre, 5870 32732, has_tags, 10045 23327, has_genre, 5870 23327, has_tags, 10045 32392, has_genre, 5870 32392, has_tags, 5870 32392, release_year, 28171 28048, has_genre, 5870 28048, has_tags, 10045 14113, has_genre, 5870 14113, has_tags, 10045 14382, has_genre, 5870 14382, has_tags, 10045 5813, has_genre, 5870 5813, written_by, 20487 25175, has_genre, 5870 25175, has_tags, 10045 11787, has_genre, 5870 11787, has_tags, 10045 11787, has_tags, 5870 31283, has_genre, 5870 31283, has_tags, 10045 22212, has_genre, 5870 22212, has_tags, 10045 32595, has_genre, 5870 32595, has_tags, 10045 15198, has_genre, 5870 15198, has_tags, 10045 29358, has_genre, 5870 29358, has_tags, 10045 27780, has_genre, 5870 27780, has_tags, 10045 34005, has_genre, 5870 34005, has_tags, 10045 10379, has_genre, 5870 10379, written_by, 23284 8623, has_genre, 5870 8623, has_tags, 10045 33794, has_genre, 5870 33794, has_tags, 10045 29109, has_genre, 5870 29109, has_tags, 10045 26566, has_genre, 5870 26566, has_tags, 5870 26566, has_tags, 23284 26566, written_by, 23284 11243, has_genre, 5870 11243, has_tags, 10045 33919, has_genre, 5870 33919, has_tags, 23284 33919, written_by, 23284 26820, has_genre, 5870 26820, has_tags, 10045 26820, has_tags, 5870 40021, has_genre, 5870 40021, written_by, 23284 8727, has_genre, 5870 8727, has_tags, 10045 1565, has_genre, 5870 1565, has_tags, 10045 18162, has_genre, 5870 18162, has_tags, 10045 18162, has_tags, 5870 10186, has_genre, 5870 10186, has_tags, 10045 1143, has_genre, 5870 1143, has_tags, 10045 19018, has_genre, 5870 19018, has_tags, 5870 19018, has_tags, 23284 19018, written_by, 23284 23847, has_genre, 5870 23847, has_tags, 10045 23260, has_genre, 5870 23260, has_tags, 10045 33991, has_genre, 5870 33991, has_tags, 10045 9715, has_genre, 5870 9715, has_tags, 5870 9715, release_year, 28171 19823, has_genre, 5870 19823, has_tags, 10045 22751, has_genre, 5870 22751, has_tags, 10045 6833, has_genre, 5870 6833, has_tags, 10045 3594, has_genre, 5870 3594, has_tags, 10045 14444, has_genre, 5870 14444, has_tags, 10045 14444, has_tags, 5870 7808, has_genre, 5870 7808, has_tags, 23284 7808, written_by, 23284 1596, has_genre, 5870 1596, has_tags, 10045 17409, has_genre, 5870 17409, release_year, 28171 29370, has_genre, 5870 29370, has_tags, 10045 31252, has_genre, 5870 31252, has_tags, 10045 31252, has_tags, 5870 36374, has_genre, 5870 36374, has_tags, 10045 28352, has_genre, 5870 28352, has_tags, 10045 36013, has_genre, 5870 36013, release_year, 28171 6037, has_genre, 5870 6037, has_tags, 10045 Question: For what reason are MARC BRANDEL, MAXIMUM OVERDRIVE, and MYRNA FAHEY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MARC BRANDEL", "MAXIMUM OVERDRIVE", "MYRNA FAHEY" ], "valid_edges": [ [ "1408", "has_genre", "HORROR" ], [ "1408", "has_tags", "HORROR" ], [ "1408", "has_tags", "STEPHEN KING" ], [ "1408", "written_by", "STEPHEN KING" ], [ "A BUCKET OF BLOOD", "has_genre", "HORROR" ], [ "A BUCKET OF BLOOD", "has_tags", "BD-R" ], [ "ALIENS", "has_tags", "HORROR" ], [ "ALIENS", "release_year", "1986" ], [ "APRIL FOOL'S DAY", "has_genre", "HORROR" ], [ "APRIL FOOL'S DAY", "release_year", "1986" ], [ "BLACK DEATH", "has_genre", "HORROR" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLOOD OF THE VAMPIRE", "has_genre", "HORROR" ], [ "BLOOD OF THE VAMPIRE", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "HORROR" ], [ "CARRIE", "has_genre", "HORROR" ], [ "CARRIE", "has_tags", "HORROR" ], [ "CARRIE", "has_tags", "STEPHEN KING" ], [ "CARRIE", "written_by", "STEPHEN KING" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "has_tags", "BD-R" ], [ "CAT'S EYE", "has_genre", "HORROR" ], [ "CAT'S EYE", "has_tags", "STEPHEN KING" ], [ "CAT'S EYE", "written_by", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "has_genre", "HORROR" ], [ "CHILDREN OF THE CORN", "has_tags", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "written_by", "STEPHEN KING" ], [ "CHOPPING MALL", "has_genre", "HORROR" ], [ "CHOPPING MALL", "release_year", "1986" ], [ "CHRISTINE", "has_genre", "HORROR" ], [ "CHRISTINE", "has_tags", "STEPHEN KING" ], [ "CHRISTINE", "written_by", "STEPHEN KING" ], [ "CLASS OF NUKE 'EM HIGH", "has_genre", "HORROR" ], [ "CLASS OF NUKE 'EM HIGH", "release_year", "1986" ], [ "CRAWLSPACE", "has_genre", "HORROR" ], [ "CRAWLSPACE", "release_year", "1986" ], [ "CREEPSHOW", "has_genre", "HORROR" ], [ "CREEPSHOW", "written_by", "STEPHEN KING" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "has_tags", "STEPHEN KING" ], [ "CREEPSHOW 2", "written_by", "STEPHEN KING" ], [ "CRITTERS", "has_genre", "HORROR" ], [ "CRITTERS", "release_year", "1986" ], [ "CUJO", "has_genre", "HORROR" ], [ "CUJO", "has_tags", "STEPHEN KING" ], [ "CUJO", "written_by", "STEPHEN KING" ], [ "DEAD OF NIGHT", "has_genre", "HORROR" ], [ "DEAD OF NIGHT", "has_tags", "BD-R" ], [ "DEADLY FRIEND", "has_genre", "HORROR" ], [ "DEADLY FRIEND", "release_year", "1986" ], [ "DEMENTIA 13", "has_genre", "HORROR" ], [ "DEMENTIA 13", "has_tags", "BD-R" ], [ "DEMONS 2", "has_genre", "HORROR" ], [ "DEMONS 2", "release_year", "1986" ], [ "DETOUR", "has_genre", "HORROR" ], [ "DETOUR", "has_tags", "BD-R" ], [ "DOCTOR X", "has_genre", "HORROR" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DONOVAN'S BRAIN", "has_genre", "HORROR" ], [ "DONOVAN'S BRAIN", "has_tags", "BD-R" ], [ "DR. JEKYLL AND MR. HYDE", "has_genre", "HORROR" ], [ "DR. JEKYLL AND MR. HYDE", "has_tags", "BD-R" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_genre", "HORROR" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_tags", "BD-R" ], [ "DRACULA'S DAUGHTER", "has_genre", "HORROR" ], [ "DRACULA'S DAUGHTER", "has_tags", "BD-R" ], [ "DREAMCATCHER", "has_genre", "HORROR" ], [ "DREAMCATCHER", "has_tags", "STEPHEN KING" ], [ "DREAMCATCHER", "written_by", "STEPHEN KING" ], [ "EYE OF THE DEVIL", "has_genre", "HORROR" ], [ "EYE OF THE DEVIL", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_genre", "HORROR" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_genre", "HORROR" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_tags", "BD-R" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "release_year", "1986" ], [ "GALAXY OF TERROR", "has_genre", "HORROR" ], [ "GALAXY OF TERROR", "has_tags", "BD-R" ], [ "GOTHIC", "has_genre", "HORROR" ], [ "GOTHIC", "release_year", "1986" ], [ "HANDS OF THE RIPPER", "has_genre", "HORROR" ], [ "HANDS OF THE RIPPER", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "HORROR" ], [ "HORROR EXPRESS", "has_genre", "HORROR" ], [ "HORROR EXPRESS", "has_tags", "BD-R" ], [ "HOUSE", "has_genre", "HORROR" ], [ "HOUSE", "release_year", "1986" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF USHER", "starred_actors", "MYRNA FAHEY" ], [ "HOUSE OF WAX", "has_genre", "HORROR" ], [ "HOUSE OF WAX", "has_tags", "BD-R" ], [ "INVADERS FROM MARS", "has_genre", "HORROR" ], [ "INVADERS FROM MARS", "release_year", "1986" ], [ "LINK", "has_genre", "HORROR" ], [ "LINK", "release_year", "1986" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "LITTLE SHOP OF HORRORS", "release_year", "1986" ], [ "MACABRE", "has_genre", "HORROR" ], [ "MACABRE", "has_tags", "BD-R" ], [ "MAD LOVE", "has_genre", "HORROR" ], [ "MAD LOVE", "has_tags", "BD-R" ], [ "MADHOUSE", "has_genre", "HORROR" ], [ "MADHOUSE", "has_tags", "BD-R" ], [ "MARK OF THE VAMPIRE", "has_genre", "HORROR" ], [ "MARK OF THE VAMPIRE", "has_tags", "BD-R" ], [ "MAXIMUM OVERDRIVE", "directed_by", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "has_genre", "HORROR" ], [ "MAXIMUM OVERDRIVE", "has_tags", "BD-R" ], [ "MAXIMUM OVERDRIVE", "has_tags", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "release_year", "1986" ], [ "MAXIMUM OVERDRIVE", "written_by", "STEPHEN KING" ], [ "MISERY", "has_tags", "HORROR" ], [ "MISERY", "has_tags", "STEPHEN KING" ], [ "MISERY", "written_by", "STEPHEN KING" ], [ "MONSTER IN THE CLOSET", "has_genre", "HORROR" ], [ "MONSTER IN THE CLOSET", "release_year", "1986" ], [ "MOUNTAINTOP MOTEL MASSACRE", "has_genre", "HORROR" ], [ "MOUNTAINTOP MOTEL MASSACRE", "release_year", "1986" ], [ "MYSTERY OF THE WAX MUSEUM", "has_genre", "HORROR" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "BD-R" ], [ "NIGHT OF THE CREEPS", "has_genre", "HORROR" ], [ "NIGHT OF THE CREEPS", "release_year", "1986" ], [ "NIGHT OF THE DEMONS", "has_genre", "HORROR" ], [ "NIGHT OF THE DEMONS", "has_tags", "BD-R" ], [ "NIGHT OF THE LEPUS", "has_genre", "HORROR" ], [ "NIGHT OF THE LEPUS", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "NOMADS", "has_genre", "HORROR" ], [ "NOMADS", "release_year", "1986" ], [ "NOSFERATU", "has_genre", "HORROR" ], [ "NOSFERATU", "has_tags", "BD-R" ], [ "PEEPING TOM", "has_genre", "HORROR" ], [ "PEEPING TOM", "has_tags", "BD-R" ], [ "PET SEMATARY", "has_genre", "HORROR" ], [ "PET SEMATARY", "has_tags", "HORROR" ], [ "PET SEMATARY", "has_tags", "STEPHEN KING" ], [ "PET SEMATARY", "written_by", "STEPHEN KING" ], [ "PLANET TERROR", "has_genre", "HORROR" ], [ "PLANET TERROR", "has_tags", "BD-R" ], [ "PLANET TERROR", "has_tags", "HORROR" ], [ "PSYCHO III", "has_genre", "HORROR" ], [ "PSYCHO III", "release_year", "1986" ], [ "QUICKSILVER HIGHWAY", "has_genre", "HORROR" ], [ "QUICKSILVER HIGHWAY", "written_by", "STEPHEN KING" ], [ "RAWHEAD REX", "has_genre", "HORROR" ], [ "RAWHEAD REX", "release_year", "1986" ], [ "REPULSION", "has_genre", "HORROR" ], [ "REPULSION", "has_tags", "BD-R" ], [ "RIDING THE BULLET", "has_genre", "HORROR" ], [ "RIDING THE BULLET", "has_tags", "STEPHEN KING" ], [ "RIDING THE BULLET", "written_by", "STEPHEN KING" ], [ "SILVER BULLET", "has_genre", "HORROR" ], [ "SILVER BULLET", "has_tags", "STEPHEN KING" ], [ "SILVER BULLET", "written_by", "STEPHEN KING" ], [ "SLEEPWALKERS", "has_genre", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "STEPHEN KING" ], [ "SLEEPWALKERS", "written_by", "STEPHEN KING" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "STAGE FRIGHT", "has_genre", "HORROR" ], [ "STAGE FRIGHT", "has_tags", "BD-R" ], [ "STORAGE 24", "has_genre", "HORROR" ], [ "STORAGE 24", "has_tags", "BD-R" ], [ "SVENGALI", "has_genre", "HORROR" ], [ "SVENGALI", "has_tags", "BD-R" ], [ "TERRORVISION", "has_genre", "HORROR" ], [ "TERRORVISION", "release_year", "1986" ], [ "THE ABOMINABLE DR. PHIBES", "has_genre", "HORROR" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "BD-R" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_genre", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_tags", "BD-R" ], [ "THE BAD SEED", "has_genre", "HORROR" ], [ "THE BAD SEED", "has_tags", "BD-R" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_tags", "BD-R" ], [ "THE CABINET OF DR. CALIGARI", "has_genre", "HORROR" ], [ "THE CABINET OF DR. CALIGARI", "has_tags", "BD-R" ], [ "THE CAT AND THE CANARY", "has_genre", "HORROR" ], [ "THE CAT AND THE CANARY", "has_tags", "BD-R" ], [ "THE CREEPING FLESH", "has_genre", "HORROR" ], [ "THE CREEPING FLESH", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "HORROR" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "has_tags", "STEPHEN KING" ], [ "THE DARK HALF", "written_by", "STEPHEN KING" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "has_tags", "STEPHEN KING" ], [ "THE DEAD ZONE", "written_by", "STEPHEN KING" ], [ "THE DEVIL-DOLL", "has_genre", "HORROR" ], [ "THE DEVIL-DOLL", "has_tags", "BD-R" ], [ "THE DOCTOR AND THE DEVILS", "has_genre", "HORROR" ], [ "THE DOCTOR AND THE DEVILS", "has_tags", "BD-R" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_genre", "HORROR" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_tags", "BD-R" ], [ "THE FLY", "has_genre", "HORROR" ], [ "THE FLY", "has_tags", "HORROR" ], [ "THE FLY", "release_year", "1986" ], [ "THE GHOST BREAKERS", "has_genre", "HORROR" ], [ "THE GHOST BREAKERS", "has_tags", "BD-R" ], [ "THE GHOUL", "has_genre", "HORROR" ], [ "THE GHOUL", "has_tags", "BD-R" ], [ "THE GORGON", "has_genre", "HORROR" ], [ "THE GORGON", "has_tags", "BD-R" ], [ "THE HAND", "has_genre", "HORROR" ], [ "THE HAND", "written_by", "MARC BRANDEL" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_genre", "HORROR" ], [ "THE HAUNTING", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_tags", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_genre", "HORROR" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_tags", "BD-R" ], [ "THE HOWLING", "has_genre", "HORROR" ], [ "THE HOWLING", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "HORROR" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNGER", "has_genre", "HORROR" ], [ "THE HUNGER", "has_tags", "BD-R" ], [ "THE INNOCENTS", "has_genre", "HORROR" ], [ "THE INNOCENTS", "has_tags", "BD-R" ], [ "THE INVISIBLE MAN", "has_genre", "HORROR" ], [ "THE INVISIBLE MAN", "has_tags", "BD-R" ], [ "THE LAWNMOWER MAN", "has_genre", "HORROR" ], [ "THE LAWNMOWER MAN", "written_by", "STEPHEN KING" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "BD-R" ], [ "THE LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "THE LITTLE SHOP OF HORRORS", "has_tags", "BD-R" ], [ "THE LODGER", "has_genre", "HORROR" ], [ "THE LODGER", "has_tags", "BD-R" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "has_tags", "STEPHEN KING" ], [ "THE MANGLER", "written_by", "STEPHEN KING" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "BD-R" ], [ "THE MIST", "has_genre", "HORROR" ], [ "THE MIST", "has_tags", "STEPHEN KING" ], [ "THE MIST", "written_by", "STEPHEN KING" ], [ "THE MUMMY", "has_genre", "HORROR" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE MUMMY", "has_tags", "HORROR" ], [ "THE NIGHT FLIER", "has_genre", "HORROR" ], [ "THE NIGHT FLIER", "written_by", "STEPHEN KING" ], [ "THE PICTURE OF DORIAN GRAY", "has_genre", "HORROR" ], [ "THE PICTURE OF DORIAN GRAY", "has_tags", "BD-R" ], [ "THE PLAGUE OF THE ZOMBIES", "has_genre", "HORROR" ], [ "THE PLAGUE OF THE ZOMBIES", "has_tags", "BD-R" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "BD-R" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE SEVENTH VICTIM", "has_genre", "HORROR" ], [ "THE SEVENTH VICTIM", "has_tags", "BD-R" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "STEPHEN KING" ], [ "THE SHINING", "written_by", "STEPHEN KING" ], [ "THE STEPFORD WIVES", "has_genre", "HORROR" ], [ "THE STEPFORD WIVES", "has_tags", "BD-R" ], [ "THE SWARM", "has_genre", "HORROR" ], [ "THE SWARM", "has_tags", "BD-R" ], [ "THE TERROR", "has_genre", "HORROR" ], [ "THE TERROR", "has_tags", "BD-R" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_genre", "HORROR" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_tags", "HORROR" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "release_year", "1986" ], [ "THE UNKNOWN", "has_genre", "HORROR" ], [ "THE UNKNOWN", "has_tags", "BD-R" ], [ "THE WICKER MAN", "has_genre", "HORROR" ], [ "THE WICKER MAN", "has_tags", "BD-R" ], [ "THE WITCHES", "has_genre", "HORROR" ], [ "THE WITCHES", "has_tags", "BD-R" ], [ "THEATRE OF BLOOD", "has_genre", "HORROR" ], [ "THEATRE OF BLOOD", "has_tags", "BD-R" ], [ "THEM!", "has_genre", "HORROR" ], [ "THEM!", "has_tags", "BD-R" ], [ "THEM!", "has_tags", "HORROR" ], [ "THINNER", "has_genre", "HORROR" ], [ "THINNER", "has_tags", "STEPHEN KING" ], [ "THINNER", "written_by", "STEPHEN KING" ], [ "TORTURE GARDEN", "has_genre", "HORROR" ], [ "TORTURE GARDEN", "has_tags", "BD-R" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "release_year", "1986" ], [ "TROG", "has_genre", "HORROR" ], [ "TROG", "has_tags", "BD-R" ], [ "V/H/S", "has_genre", "HORROR" ], [ "V/H/S", "has_tags", "BD-R" ], [ "V/H/S", "has_tags", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_genre", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_tags", "BD-R" ], [ "WHITE ZOMBIE", "has_genre", "HORROR" ], [ "WHITE ZOMBIE", "has_tags", "BD-R" ], [ "WITCHBOARD", "has_genre", "HORROR" ], [ "WITCHBOARD", "release_year", "1986" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29157, BOCA 14724, CRIME 15631, EDWARD G. ROBINSON 32536, FLAVIO FREDERICO 19711, FRANK MCHUGH 2554, JOHN FARROW 25821, NIGHT HAS A THOUSAND EYES 20292, THE WIDOW FROM CHICAGO src, edge_attr, dst 29157, directed_by, 32536 29157, has_genre, 14724 29157, written_by, 32536 25821, directed_by, 2554 25821, has_tags, 2554 25821, starred_actors, 15631 20292, has_genre, 14724 20292, starred_actors, 15631 20292, starred_actors, 19711 Question: For what reason are FLAVIO FREDERICO, FRANK MCHUGH, and JOHN FARROW associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FLAVIO FREDERICO", "FRANK MCHUGH", "JOHN FARROW" ], "valid_edges": [ [ "BOCA", "directed_by", "FLAVIO FREDERICO" ], [ "BOCA", "has_genre", "CRIME" ], [ "BOCA", "written_by", "FLAVIO FREDERICO" ], [ "NIGHT HAS A THOUSAND EYES", "directed_by", "JOHN FARROW" ], [ "NIGHT HAS A THOUSAND EYES", "has_tags", "JOHN FARROW" ], [ "NIGHT HAS A THOUSAND EYES", "starred_actors", "EDWARD G. ROBINSON" ], [ "THE WIDOW FROM CHICAGO", "has_genre", "CRIME" ], [ "THE WIDOW FROM CHICAGO", "starred_actors", "EDWARD G. ROBINSON" ], [ "THE WIDOW FROM CHICAGO", "starred_actors", "FRANK MCHUGH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 10110, A TIME FOR KILLING 7687, ADVANCE TO THE REAR 23328, APPALOOSA 26781, CIMARRON 34347, COUNT THREE AND PRAY 18170, COWBOY 25442, GLENN FORD 8819, JUBAL 6417, LUST FOR GOLD 15037, OTIS 12214, PRAIRIE FEVER 7585, TEXAS 37288, THE COURTSHIP OF EDDIE'S FATHER 18466, THE DESPERADOES 10084, THE FASTEST GUN ALIVE 35340, THE MAN FROM THE ALAMO 28829, THE SECRET OF CONVICT LAKE 5394, THE SHEEPMAN 30942, THE VIOLENT MEN 36026, WESTERN src, edge_attr, dst 10110, has_genre, 36026 10110, starred_actors, 25442 7687, has_genre, 36026 7687, starred_actors, 25442 23328, has_genre, 36026 23328, has_tags, 36026 23328, release_year, 26762 26781, has_genre, 36026 26781, starred_actors, 25442 34347, has_genre, 36026 18170, has_genre, 36026 18170, starred_actors, 25442 8819, has_genre, 36026 8819, starred_actors, 25442 6417, has_genre, 36026 6417, starred_actors, 25442 15037, release_year, 26762 12214, has_genre, 36026 12214, release_year, 26762 7585, has_genre, 36026 7585, starred_actors, 25442 37288, starred_actors, 25442 18466, has_genre, 36026 18466, starred_actors, 25442 10084, has_genre, 36026 10084, starred_actors, 25442 35340, has_genre, 36026 35340, starred_actors, 25442 28829, has_genre, 36026 28829, starred_actors, 25442 5394, has_genre, 36026 5394, starred_actors, 25442 30942, has_genre, 36026 30942, starred_actors, 25442 Question: In what context are COUNT THREE AND PRAY, OTIS, and THE COURTSHIP OF EDDIE'S FATHER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "COUNT THREE AND PRAY", "OTIS", "THE COURTSHIP OF EDDIE'S FATHER" ], "valid_edges": [ [ "A TIME FOR KILLING", "has_genre", "WESTERN" ], [ "A TIME FOR KILLING", "starred_actors", "GLENN FORD" ], [ "ADVANCE TO THE REAR", "has_genre", "WESTERN" ], [ "ADVANCE TO THE REAR", "starred_actors", "GLENN FORD" ], [ "APPALOOSA", "has_genre", "WESTERN" ], [ "APPALOOSA", "has_tags", "WESTERN" ], [ "APPALOOSA", "release_year", "2008" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "starred_actors", "GLENN FORD" ], [ "COUNT THREE AND PRAY", "has_genre", "WESTERN" ], [ "COWBOY", "has_genre", "WESTERN" ], [ "COWBOY", "starred_actors", "GLENN FORD" ], [ "JUBAL", "has_genre", "WESTERN" ], [ "JUBAL", "starred_actors", "GLENN FORD" ], [ "LUST FOR GOLD", "has_genre", "WESTERN" ], [ "LUST FOR GOLD", "starred_actors", "GLENN FORD" ], [ "OTIS", "release_year", "2008" ], [ "PRAIRIE FEVER", "has_genre", "WESTERN" ], [ "PRAIRIE FEVER", "release_year", "2008" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "TEXAS", "starred_actors", "GLENN FORD" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "starred_actors", "GLENN FORD" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "GLENN FORD" ], [ "THE FASTEST GUN ALIVE", "has_genre", "WESTERN" ], [ "THE FASTEST GUN ALIVE", "starred_actors", "GLENN FORD" ], [ "THE MAN FROM THE ALAMO", "has_genre", "WESTERN" ], [ "THE MAN FROM THE ALAMO", "starred_actors", "GLENN FORD" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "starred_actors", "GLENN FORD" ], [ "THE SHEEPMAN", "has_genre", "WESTERN" ], [ "THE SHEEPMAN", "starred_actors", "GLENN FORD" ], [ "THE VIOLENT MEN", "has_genre", "WESTERN" ], [ "THE VIOLENT MEN", "starred_actors", "GLENN FORD" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36173, 1946 24818, 1992 30553, 7TH CAVALRY 12094, A LAWLESS STREET 12549, ALBUQUERQUE 27991, BADMAN'S TERRITORY 29926, BUCHANAN RIDES ALONE 34547, CANYON PASSAGE 8622, CAROLE EASTMAN 27943, CARSON CITY 18014, COMANCHE STATION 13930, DECISION AT SUNDOWN 22900, DUEL IN THE SUN 26417, FIVE EASY PIECES 17966, HANGMAN'S KNOT 25413, HELDORADO 32025, HIGH, WIDE, AND HANDSOME 21488, JACK NICHOLSON 13787, MAN IN THE SADDLE 24068, MAN TROUBLE 15797, MY DARLING CLEMENTINE 10835, RAGE AT DAWN 22364, RANDOLPH SCOTT 2314, RIDE LONESOME 4848, RIDE THE HIGH COUNTRY 30533, SANTA FE 21240, SEVEN MEN FROM NOW 15270, SHOOT-OUT AT MEDICINE BEND 36482, STUART SAMUELS 18466, THE DESPERADOES 25351, THE MAN BEHIND THE GUN 18556, THE SHOOTING 33389, THE SPOILERS 1144, THE TALL T 28632, THE VIRGINIAN 30844, VISIONS OF LIGHT 36026, WESTERN 5882, WESTERN UNION src, edge_attr, dst 30553, has_genre, 36026 30553, starred_actors, 22364 12094, has_genre, 36026 12094, starred_actors, 22364 12549, has_genre, 36026 12549, starred_actors, 22364 27991, has_genre, 36026 27991, release_year, 36173 27991, starred_actors, 22364 29926, has_genre, 36026 29926, starred_actors, 22364 34547, has_genre, 36026 34547, release_year, 36173 27943, has_genre, 36026 27943, starred_actors, 22364 18014, has_genre, 36026 18014, starred_actors, 22364 13930, has_genre, 36026 13930, starred_actors, 22364 22900, has_genre, 36026 22900, release_year, 36173 26417, has_tags, 21488 26417, starred_actors, 21488 26417, written_by, 8622 17966, has_genre, 36026 17966, starred_actors, 22364 25413, has_genre, 36026 25413, release_year, 36173 32025, has_genre, 36026 32025, starred_actors, 22364 13787, has_genre, 36026 13787, starred_actors, 22364 24068, has_tags, 21488 24068, release_year, 24818 24068, starred_actors, 21488 24068, written_by, 8622 15797, has_genre, 36026 15797, release_year, 36173 10835, has_genre, 36026 10835, starred_actors, 22364 2314, has_genre, 36026 2314, starred_actors, 22364 4848, has_genre, 36026 4848, has_tags, 22364 4848, starred_actors, 22364 30533, has_genre, 36026 30533, starred_actors, 22364 21240, has_genre, 36026 21240, starred_actors, 22364 15270, has_genre, 36026 15270, starred_actors, 22364 18466, has_genre, 36026 18466, starred_actors, 22364 25351, has_genre, 36026 25351, starred_actors, 22364 18556, has_genre, 36026 18556, has_tags, 21488 18556, starred_actors, 21488 18556, written_by, 8622 33389, has_genre, 36026 33389, starred_actors, 22364 1144, has_genre, 36026 1144, has_tags, 36026 1144, starred_actors, 22364 28632, has_genre, 36026 28632, release_year, 36173 30844, directed_by, 36482 30844, release_year, 24818 5882, has_genre, 36026 5882, starred_actors, 22364 Question: In what context are BADMAN'S TERRITORY, CAROLE EASTMAN, and STUART SAMUELS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BADMAN'S TERRITORY", "CAROLE EASTMAN", "STUART SAMUELS" ], "valid_edges": [ [ "7TH CAVALRY", "has_genre", "WESTERN" ], [ "7TH CAVALRY", "starred_actors", "RANDOLPH SCOTT" ], [ "A LAWLESS STREET", "has_genre", "WESTERN" ], [ "A LAWLESS STREET", "starred_actors", "RANDOLPH SCOTT" ], [ "ALBUQUERQUE", "has_genre", "WESTERN" ], [ "ALBUQUERQUE", "starred_actors", "RANDOLPH SCOTT" ], [ "BADMAN'S TERRITORY", "has_genre", "WESTERN" ], [ "BADMAN'S TERRITORY", "release_year", "1946" ], [ "BADMAN'S TERRITORY", "starred_actors", "RANDOLPH SCOTT" ], [ "BUCHANAN RIDES ALONE", "has_genre", "WESTERN" ], [ "BUCHANAN RIDES ALONE", "starred_actors", "RANDOLPH SCOTT" ], [ "CANYON PASSAGE", "has_genre", "WESTERN" ], [ "CANYON PASSAGE", "release_year", "1946" ], [ "CARSON CITY", "has_genre", "WESTERN" ], [ "CARSON CITY", "starred_actors", "RANDOLPH SCOTT" ], [ "COMANCHE STATION", "has_genre", "WESTERN" ], [ "COMANCHE STATION", "starred_actors", "RANDOLPH SCOTT" ], [ "DECISION AT SUNDOWN", "has_genre", "WESTERN" ], [ "DECISION AT SUNDOWN", "starred_actors", "RANDOLPH SCOTT" ], [ "DUEL IN THE SUN", "has_genre", "WESTERN" ], [ "DUEL IN THE SUN", "release_year", "1946" ], [ "FIVE EASY PIECES", "has_tags", "JACK NICHOLSON" ], [ "FIVE EASY PIECES", "starred_actors", "JACK NICHOLSON" ], [ "FIVE EASY PIECES", "written_by", "CAROLE EASTMAN" ], [ "HANGMAN'S KNOT", "has_genre", "WESTERN" ], [ "HANGMAN'S KNOT", "starred_actors", "RANDOLPH SCOTT" ], [ "HELDORADO", "has_genre", "WESTERN" ], [ "HELDORADO", "release_year", "1946" ], [ "HIGH, WIDE, AND HANDSOME", "has_genre", "WESTERN" ], [ "HIGH, WIDE, AND HANDSOME", "starred_actors", "RANDOLPH SCOTT" ], [ "MAN IN THE SADDLE", "has_genre", "WESTERN" ], [ "MAN IN THE SADDLE", "starred_actors", "RANDOLPH SCOTT" ], [ "MAN TROUBLE", "has_tags", "JACK NICHOLSON" ], [ "MAN TROUBLE", "release_year", "1992" ], [ "MAN TROUBLE", "starred_actors", "JACK NICHOLSON" ], [ "MAN TROUBLE", "written_by", "CAROLE EASTMAN" ], [ "MY DARLING CLEMENTINE", "has_genre", "WESTERN" ], [ "MY DARLING CLEMENTINE", "release_year", "1946" ], [ "RAGE AT DAWN", "has_genre", "WESTERN" ], [ "RAGE AT DAWN", "starred_actors", "RANDOLPH SCOTT" ], [ "RIDE LONESOME", "has_genre", "WESTERN" ], [ "RIDE LONESOME", "starred_actors", "RANDOLPH SCOTT" ], [ "RIDE THE HIGH COUNTRY", "has_genre", "WESTERN" ], [ "RIDE THE HIGH COUNTRY", "has_tags", "RANDOLPH SCOTT" ], [ "RIDE THE HIGH COUNTRY", "starred_actors", "RANDOLPH SCOTT" ], [ "SANTA FE", "has_genre", "WESTERN" ], [ "SANTA FE", "starred_actors", "RANDOLPH SCOTT" ], [ "SEVEN MEN FROM NOW", "has_genre", "WESTERN" ], [ "SEVEN MEN FROM NOW", "starred_actors", "RANDOLPH SCOTT" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_genre", "WESTERN" ], [ "SHOOT-OUT AT MEDICINE BEND", "starred_actors", "RANDOLPH SCOTT" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "RANDOLPH SCOTT" ], [ "THE MAN BEHIND THE GUN", "has_genre", "WESTERN" ], [ "THE MAN BEHIND THE GUN", "starred_actors", "RANDOLPH SCOTT" ], [ "THE SHOOTING", "has_genre", "WESTERN" ], [ "THE SHOOTING", "has_tags", "JACK NICHOLSON" ], [ "THE SHOOTING", "starred_actors", "JACK NICHOLSON" ], [ "THE SHOOTING", "written_by", "CAROLE EASTMAN" ], [ "THE SPOILERS", "has_genre", "WESTERN" ], [ "THE SPOILERS", "starred_actors", "RANDOLPH SCOTT" ], [ "THE TALL T", "has_genre", "WESTERN" ], [ "THE TALL T", "has_tags", "WESTERN" ], [ "THE TALL T", "starred_actors", "RANDOLPH SCOTT" ], [ "THE VIRGINIAN", "has_genre", "WESTERN" ], [ "THE VIRGINIAN", "release_year", "1946" ], [ "VISIONS OF LIGHT", "directed_by", "STUART SAMUELS" ], [ "VISIONS OF LIGHT", "release_year", "1992" ], [ "WESTERN UNION", "has_genre", "WESTERN" ], [ "WESTERN UNION", "starred_actors", "RANDOLPH SCOTT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 26277, A FEW GOOD MEN 31344, A LEAGUE OF THEIR OWN 9317, A RIVER RUNS THROUGH IT 35276, A TALE OF WINTER 36782, AFTERBURN 39584, AMERICAN ME 34836, ARTICLE 99 5247, BAD LIEUTENANT 5618, BREAKING THE RULES 25358, CAMERA 11673, CITY OF JOY 22229, CLAIRE OF THE MOON 2408, CRISSCROSS 7946, CROSSING THE BRIDGE 656, CRUSH 28562, DAENS 30624, DANCES WITH WOLVES 2890, DESERT HEARTS 33069, DOING TIME ON MAPLE DRIVE 36212, DRAMA 38483, EVERLASTING MOMENTS 18031, FAR AND AWAY 17947, FINAL ANALYSIS 8089, FOREVER YOUNG 35150, FRIED GREEN TOMATOES 9778, GLADIATOR 16491, GLENGARRY GLEN ROSS 35421, GO FISH 35838, GUNCRAZY 19463, HEDD WYN 3829, HERO 9849, HOUSE OF ANGELS 25277, HUSBANDS AND WIVES 19642, JUICE 34688, LAWS OF GRAVITY 191, LEAVING NORMAL 8635, LESBIAN 16441, LIGHT SLEEPER 2682, LORENZO'S OIL 14167, LOVE FIELD 7221, LOVE SICK 19549, MALCOLM X 29234, MICHAEL BLAKE 34536, MISTRESS 23375, NEWSIES 8720, OLIVIER, OLIVIER 8280, PARIAH 25678, PETER'S FRIENDS 27925, POISON IVY 38711, PURE COUNTRY 37297, RADIO FLYER 1844, ROMPER STOMPER 13542, SAVAGE NIGHTS 40001, SCENT OF A WOMAN 28758, SCHOOL TIES 30817, SHINING THROUGH 36604, SOUTH CENTRAL 24853, SPIDER LILIES 1432, STRICTLY BALLROOM 23746, THE BEST INTENTIONS 37993, THE BOYS OF ST. VINCENT 165, THE CRYING GAME 14308, THE LOVER 22217, THE MAMBO KINGS 25792, THE OAK 214, THE POWER OF ONE 11845, THE TURNING 22264, THE WATERDANCE 20210, THE WOMEN 36340, TRACES OF RED 22214, WAR 8611, ZEBRAHEAD src, edge_attr, dst 26277, has_genre, 36212 26277, has_tags, 36212 26277, release_year, 24818 31344, has_genre, 36212 31344, has_tags, 36212 31344, release_year, 24818 9317, has_genre, 36212 9317, release_year, 24818 35276, has_genre, 36212 35276, release_year, 24818 36782, has_genre, 36212 36782, release_year, 24818 39584, has_genre, 36212 39584, release_year, 24818 34836, has_genre, 36212 34836, release_year, 24818 5247, has_genre, 36212 5247, release_year, 24818 5618, has_genre, 36212 5618, release_year, 24818 11673, has_genre, 36212 11673, release_year, 24818 22229, has_genre, 36212 22229, has_tags, 8635 22229, release_year, 24818 2408, has_genre, 36212 2408, release_year, 24818 7946, has_genre, 36212 7946, release_year, 24818 656, has_genre, 36212 656, release_year, 24818 28562, has_genre, 36212 28562, release_year, 24818 30624, has_genre, 36212 30624, has_tags, 36212 30624, has_tags, 22214 30624, written_by, 29234 2890, has_genre, 36212 2890, has_tags, 8635 33069, has_genre, 36212 33069, release_year, 24818 38483, has_genre, 36212 38483, has_tags, 25358 38483, has_tags, 22214 18031, has_genre, 36212 18031, release_year, 24818 17947, has_genre, 36212 17947, release_year, 24818 8089, has_genre, 36212 8089, release_year, 24818 35150, has_genre, 36212 35150, has_tags, 36212 35150, has_tags, 8635 9778, has_genre, 36212 9778, has_tags, 36212 9778, release_year, 24818 16491, has_genre, 36212 16491, release_year, 24818 35421, has_genre, 36212 35421, has_tags, 8635 35838, has_genre, 36212 35838, release_year, 24818 19463, has_genre, 36212 19463, release_year, 24818 3829, has_genre, 36212 3829, release_year, 24818 9849, has_genre, 36212 9849, release_year, 24818 25277, has_genre, 36212 25277, release_year, 24818 19642, has_genre, 36212 19642, release_year, 24818 34688, has_genre, 36212 34688, release_year, 24818 191, has_genre, 36212 191, release_year, 24818 16441, has_genre, 36212 16441, release_year, 24818 2682, has_genre, 36212 2682, release_year, 24818 14167, has_genre, 36212 14167, release_year, 24818 7221, has_genre, 36212 7221, has_tags, 8635 19549, has_genre, 36212 19549, release_year, 24818 34536, has_genre, 36212 34536, release_year, 24818 23375, has_genre, 36212 23375, release_year, 24818 8720, has_genre, 36212 8720, release_year, 24818 8280, has_genre, 36212 8280, has_tags, 8635 25678, has_genre, 36212 25678, release_year, 24818 27925, has_genre, 36212 27925, release_year, 24818 38711, has_genre, 36212 38711, release_year, 24818 37297, has_genre, 36212 37297, release_year, 24818 1844, has_genre, 36212 1844, release_year, 24818 13542, has_genre, 36212 13542, release_year, 24818 40001, has_genre, 36212 40001, has_tags, 36212 40001, release_year, 24818 28758, has_genre, 36212 28758, release_year, 24818 30817, has_genre, 36212 30817, release_year, 24818 36604, has_genre, 36212 36604, release_year, 24818 24853, has_genre, 36212 24853, has_tags, 36212 24853, has_tags, 8635 1432, has_genre, 36212 1432, release_year, 24818 23746, has_genre, 36212 23746, release_year, 24818 37993, has_genre, 36212 37993, release_year, 24818 165, has_genre, 36212 165, release_year, 24818 14308, has_genre, 36212 14308, release_year, 24818 22217, has_genre, 36212 22217, release_year, 24818 25792, has_genre, 36212 25792, release_year, 24818 214, has_genre, 36212 214, release_year, 24818 11845, has_genre, 36212 11845, release_year, 24818 22264, has_genre, 36212 22264, release_year, 24818 20210, has_genre, 36212 20210, has_tags, 8635 36340, has_genre, 36212 36340, release_year, 24818 8611, has_genre, 36212 8611, release_year, 24818 Question: How are CAMERA, CLAIRE OF THE MOON, and MICHAEL BLAKE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CAMERA", "CLAIRE OF THE MOON", "MICHAEL BLAKE" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "release_year", "1992" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "DRAMA" ], [ "A LEAGUE OF THEIR OWN", "has_tags", "DRAMA" ], [ "A LEAGUE OF THEIR OWN", "release_year", "1992" ], [ "A RIVER RUNS THROUGH IT", "has_genre", "DRAMA" ], [ "A RIVER RUNS THROUGH IT", "release_year", "1992" ], [ "A TALE OF WINTER", "has_genre", "DRAMA" ], [ "A TALE OF WINTER", "release_year", "1992" ], [ "AFTERBURN", "has_genre", "DRAMA" ], [ "AFTERBURN", "release_year", "1992" ], [ "AMERICAN ME", "has_genre", "DRAMA" ], [ "AMERICAN ME", "release_year", "1992" ], [ "ARTICLE 99", "has_genre", "DRAMA" ], [ "ARTICLE 99", "release_year", "1992" ], [ "BAD LIEUTENANT", "has_genre", "DRAMA" ], [ "BAD LIEUTENANT", "release_year", "1992" ], [ "BREAKING THE RULES", "has_genre", "DRAMA" ], [ "BREAKING THE RULES", "release_year", "1992" ], [ "CITY OF JOY", "has_genre", "DRAMA" ], [ "CITY OF JOY", "release_year", "1992" ], [ "CLAIRE OF THE MOON", "has_genre", "DRAMA" ], [ "CLAIRE OF THE MOON", "has_tags", "LESBIAN" ], [ "CLAIRE OF THE MOON", "release_year", "1992" ], [ "CRISSCROSS", "has_genre", "DRAMA" ], [ "CRISSCROSS", "release_year", "1992" ], [ "CROSSING THE BRIDGE", "has_genre", "DRAMA" ], [ "CROSSING THE BRIDGE", "release_year", "1992" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "1992" ], [ "DAENS", "has_genre", "DRAMA" ], [ "DAENS", "release_year", "1992" ], [ "DANCES WITH WOLVES", "has_genre", "DRAMA" ], [ "DANCES WITH WOLVES", "has_tags", "DRAMA" ], [ "DANCES WITH WOLVES", "has_tags", "WAR" ], [ "DANCES WITH WOLVES", "written_by", "MICHAEL BLAKE" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "has_tags", "LESBIAN" ], [ "DOING TIME ON MAPLE DRIVE", "has_genre", "DRAMA" ], [ "DOING TIME ON MAPLE DRIVE", "release_year", "1992" ], [ "EVERLASTING MOMENTS", "has_genre", "DRAMA" ], [ "EVERLASTING MOMENTS", "has_tags", "CAMERA" ], [ "EVERLASTING MOMENTS", "has_tags", "WAR" ], [ "FAR AND AWAY", "has_genre", "DRAMA" ], [ "FAR AND AWAY", "release_year", "1992" ], [ "FINAL ANALYSIS", "has_genre", "DRAMA" ], [ "FINAL ANALYSIS", "release_year", "1992" ], [ "FOREVER YOUNG", "has_genre", "DRAMA" ], [ "FOREVER YOUNG", "release_year", "1992" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "LESBIAN" ], [ "GLADIATOR", "has_genre", "DRAMA" ], [ "GLADIATOR", "has_tags", "DRAMA" ], [ "GLADIATOR", "release_year", "1992" ], [ "GLENGARRY GLEN ROSS", "has_genre", "DRAMA" ], [ "GLENGARRY GLEN ROSS", "release_year", "1992" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "LESBIAN" ], [ "GUNCRAZY", "has_genre", "DRAMA" ], [ "GUNCRAZY", "release_year", "1992" ], [ "HEDD WYN", "has_genre", "DRAMA" ], [ "HEDD WYN", "release_year", "1992" ], [ "HERO", "has_genre", "DRAMA" ], [ "HERO", "release_year", "1992" ], [ "HOUSE OF ANGELS", "has_genre", "DRAMA" ], [ "HOUSE OF ANGELS", "release_year", "1992" ], [ "HUSBANDS AND WIVES", "has_genre", "DRAMA" ], [ "HUSBANDS AND WIVES", "release_year", "1992" ], [ "JUICE", "has_genre", "DRAMA" ], [ "JUICE", "release_year", "1992" ], [ "LAWS OF GRAVITY", "has_genre", "DRAMA" ], [ "LAWS OF GRAVITY", "release_year", "1992" ], [ "LEAVING NORMAL", "has_genre", "DRAMA" ], [ "LEAVING NORMAL", "release_year", "1992" ], [ "LIGHT SLEEPER", "has_genre", "DRAMA" ], [ "LIGHT SLEEPER", "release_year", "1992" ], [ "LORENZO'S OIL", "has_genre", "DRAMA" ], [ "LORENZO'S OIL", "release_year", "1992" ], [ "LOVE FIELD", "has_genre", "DRAMA" ], [ "LOVE FIELD", "release_year", "1992" ], [ "LOVE SICK", "has_genre", "DRAMA" ], [ "LOVE SICK", "has_tags", "LESBIAN" ], [ "MALCOLM X", "has_genre", "DRAMA" ], [ "MALCOLM X", "release_year", "1992" ], [ "MISTRESS", "has_genre", "DRAMA" ], [ "MISTRESS", "release_year", "1992" ], [ "NEWSIES", "has_genre", "DRAMA" ], [ "NEWSIES", "release_year", "1992" ], [ "OLIVIER, OLIVIER", "has_genre", "DRAMA" ], [ "OLIVIER, OLIVIER", "release_year", "1992" ], [ "PARIAH", "has_genre", "DRAMA" ], [ "PARIAH", "has_tags", "LESBIAN" ], [ "PETER'S FRIENDS", "has_genre", "DRAMA" ], [ "PETER'S FRIENDS", "release_year", "1992" ], [ "POISON IVY", "has_genre", "DRAMA" ], [ "POISON IVY", "release_year", "1992" ], [ "PURE COUNTRY", "has_genre", "DRAMA" ], [ "PURE COUNTRY", "release_year", "1992" ], [ "RADIO FLYER", "has_genre", "DRAMA" ], [ "RADIO FLYER", "release_year", "1992" ], [ "ROMPER STOMPER", "has_genre", "DRAMA" ], [ "ROMPER STOMPER", "release_year", "1992" ], [ "SAVAGE NIGHTS", "has_genre", "DRAMA" ], [ "SAVAGE NIGHTS", "release_year", "1992" ], [ "SCENT OF A WOMAN", "has_genre", "DRAMA" ], [ "SCENT OF A WOMAN", "has_tags", "DRAMA" ], [ "SCENT OF A WOMAN", "release_year", "1992" ], [ "SCHOOL TIES", "has_genre", "DRAMA" ], [ "SCHOOL TIES", "release_year", "1992" ], [ "SHINING THROUGH", "has_genre", "DRAMA" ], [ "SHINING THROUGH", "release_year", "1992" ], [ "SOUTH CENTRAL", "has_genre", "DRAMA" ], [ "SOUTH CENTRAL", "release_year", "1992" ], [ "SPIDER LILIES", "has_genre", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "LESBIAN" ], [ "STRICTLY BALLROOM", "has_genre", "DRAMA" ], [ "STRICTLY BALLROOM", "release_year", "1992" ], [ "THE BEST INTENTIONS", "has_genre", "DRAMA" ], [ "THE BEST INTENTIONS", "release_year", "1992" ], [ "THE BOYS OF ST. VINCENT", "has_genre", "DRAMA" ], [ "THE BOYS OF ST. VINCENT", "release_year", "1992" ], [ "THE CRYING GAME", "has_genre", "DRAMA" ], [ "THE CRYING GAME", "release_year", "1992" ], [ "THE LOVER", "has_genre", "DRAMA" ], [ "THE LOVER", "release_year", "1992" ], [ "THE MAMBO KINGS", "has_genre", "DRAMA" ], [ "THE MAMBO KINGS", "release_year", "1992" ], [ "THE OAK", "has_genre", "DRAMA" ], [ "THE OAK", "release_year", "1992" ], [ "THE POWER OF ONE", "has_genre", "DRAMA" ], [ "THE POWER OF ONE", "release_year", "1992" ], [ "THE TURNING", "has_genre", "DRAMA" ], [ "THE TURNING", "release_year", "1992" ], [ "THE WATERDANCE", "has_genre", "DRAMA" ], [ "THE WATERDANCE", "release_year", "1992" ], [ "THE WOMEN", "has_genre", "DRAMA" ], [ "THE WOMEN", "has_tags", "LESBIAN" ], [ "TRACES OF RED", "has_genre", "DRAMA" ], [ "TRACES OF RED", "release_year", "1992" ], [ "ZEBRAHEAD", "has_genre", "DRAMA" ], [ "ZEBRAHEAD", "release_year", "1992" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 10702, 1991 1421, 2013 9377, 2014 15407, 29TH STREET 13170, A BRIGHTER SUMMER DAY 30736, A KISS BEFORE DYING 39705, A LITTLE STIFF 39289, ACTION 23683, ALL I WANT FOR CHRISTMAS 24177, ANIMATION 22321, ANNABELLA SCIORRA 4329, ANNETTE BENING 30578, ANOTHER YOU 11870, ANYTHING GOES 8688, AT PLAY IN THE FIELDS OF THE LORD 37608, AUSTRALIA 10045, BD-R 25570, BEAUTY AND THE BEAST 9414, BINGO 23922, BOB DENVER 1637, BOYZ N THE HOOD 21748, BRUCE WILLIS 13639, BUGSY 28295, CAREER OPPORTUNITIES 3343, CARNE 24274, CITY OF HOPE 15585, CITY SLICKERS 8484, CLASS ACTION 30463, COMEDY 29148, CRAZY SAFARI 14724, CRIME 8100, CURLY SUE 24841, DANNY AIELLO 31214, DEFENDING YOUR LIFE 29485, DELIRIOUS 37395, DEN OFRIVILLIGE GOLFAREN 14733, DIARY OF A HITMAN 31163, DIRECTORIAL DEBUT 12903, DISNEY 3160, DOC HOLLYWOOD 16978, DON'T TELL MOM THE BABYSITTER'S DEAD 36212, DRAMA 20846, DROP DEAD FRED 31008, DUTCH 31783, ENGLISH 36202, ERNEST SCARED STUPID 27930, EYES OF AN ANGEL 9791, FAIRY TALE 36066, FANTASY 38250, FATHER OF THE BRIDE 21606, FLIRTING 15589, FRANKIE AND JOHNNY 6012, FRENCH 35150, FRIED GREEN TOMATOES 34231, GENE HACKMAN 6480, GERMAN 11565, GOOD 36229, GRAND CANYON 18119, HE SAID, SHE SAID 34320, HEAR MY SONG 30939, HIGH HEELS 25610, HIGH STRUNG 22676, HOLLY HUNTER 8579, HOMICIDE 6546, HOT SHOTS! 39726, HUDSON HAWK 3909, IF LOOKS COULD KILL 32542, INTO THE WOODS 12389, JOBETH WILLIAMS 1841, JOE MANTEGNA 21996, JOHN CANDY 29019, JOHN HUGHES 528, JOHNNY STECCHINO 18391, JUNGLE FEVER 29911, KEVIN BACON 30015, KING RALPH 7439, L.A. STORY 29323, LIFE STINKS 26893, LITTLE MAN TATE 4139, MERYL STREEP 5678, MICHAEL J. FOX 14165, MISSISSIPPI MASALA 31100, MOBSTERS 24593, MUSICAL 33507, MY GIRL 34472, MY OWN PRIVATE IDAHO 32627, MYSTERY DATE 27118, NAKED LUNCH 5337, NATHAN LANE 37497, NATIONAL FILM REGISTRY 25620, NECESSARY ROUGHNESS 30144, NEW JACK CITY 40059, ONCE AROUND 32528, ONE GOOD COP 23735, ONLY THE LONELY 34288, ONLY YESTERDAY 30662, OSCAR 17667, OTHER PEOPLE'S MONEY 25715, P.G. WODEHOUSE 25824, PARADISE 21683, PARIS TROUT 32423, PERFECTLY NORMAL 36610, PHOEBE CATES 284, POISON 23297, PROBLEM CHILD 2 4584, PROOF 39, PURE LUCK 25772, PYRATES 29601, QUEENS LOGIC 33257, RAMBLING ROSE 15283, REGARDING HENRY 2373, RICHARD DREYFUSS 8379, ROMANCE 31600, RUBIN AND ED 11468, RUSH 18913, SALMONBERRIES 33291, SCORCHERS 33607, SEX AND ZEN 8932, SLACKER 38469, SLEEPING WITH THE ENEMY 11883, SOAPDISH 38762, SPEAKING OF THE DEVIL 24849, STEVE MARTIN 16219, STORY 29906, SUBURBAN COMMANDO 35064, SWITCH 33479, THANK YOU, JEEVES! 10559, THE ADJUSTER 8210, THE BUTCHER'S WIFE 4345, THE COMMITMENTS 252, THE DARK BACKWARD 16528, THE DOCTOR 20229, THE FISHER KING 21817, THE FIVE HEARTBEATS 32102, THE HARD WAY 34438, THE INDIAN RUNNER 37849, THE INNER CIRCLE 37565, THE LAST BOY SCOUT 35557, THE MAN IN THE MOON 12947, THE MARRYING MAN 15388, THE PRINCE OF TIDES 4037, THE RAPTURE 1545, THE SUPER 18296, THE SWEET RIDE 24811, THRILLER 13776, TOY SOLDIERS 30063, TRUE COLORS 26494, UNDER SUSPICION 33802, UNTIL THE END OF THE WORLD 24117, VOYAGER 24634, WESLEY SNIPES 7593, WHAT ABOUT BOB? 6397, WHERE ANGELS FEAR TO TREAD 1178, WHORE src, edge_attr, dst 15407, has_genre, 30463 15407, has_genre, 36212 15407, release_year, 10702 13170, has_genre, 36212 13170, release_year, 10702 30736, release_year, 9177 30736, release_year, 10702 39705, has_genre, 30463 39705, release_year, 10702 23683, has_genre, 30463 23683, release_year, 10702 30578, has_genre, 30463 30578, release_year, 10702 11870, has_genre, 24593 11870, in_language, 31783 11870, release_year, 9177 11870, written_by, 25715 8688, has_genre, 36212 8688, release_year, 10702 25570, has_genre, 24177 25570, has_genre, 36066 25570, has_tags, 24177 25570, has_tags, 12903 25570, has_tags, 9791 25570, has_tags, 36066 25570, has_tags, 24593 25570, has_tags, 37497 25570, has_tags, 16219 25570, in_language, 6012 25570, release_year, 10702 25570, release_year, 9377 9414, has_genre, 30463 9414, release_year, 10702 1637, has_genre, 36212 1637, has_imdb_rating, 11565 1637, has_tags, 31163 1637, has_tags, 36212 1637, has_tags, 37497 1637, release_year, 10702 13639, has_genre, 14724 13639, has_genre, 36212 13639, release_year, 10702 13639, starred_actors, 4329 28295, has_genre, 30463 28295, release_year, 10702 28295, written_by, 29019 3343, has_genre, 36212 3343, has_tags, 6012 3343, in_language, 6012 3343, release_year, 10702 24274, has_genre, 36212 24274, release_year, 10702 15585, has_genre, 30463 15585, release_year, 10702 8484, has_genre, 36212 8484, has_genre, 24811 8484, has_tags, 34231 8484, release_year, 10702 8484, starred_actors, 34231 29148, has_genre, 30463 29148, release_year, 10702 8100, directed_by, 29019 8100, has_genre, 30463 8100, has_genre, 36212 8100, has_tags, 29019 8100, release_year, 10702 8100, written_by, 29019 31214, has_genre, 30463 31214, has_genre, 36212 31214, has_genre, 36066 31214, has_tags, 4139 31214, release_year, 10702 29485, has_genre, 30463 29485, release_year, 10702 29485, starred_actors, 21996 37395, has_genre, 30463 37395, in_language, 31783 37395, release_year, 10702 14733, has_genre, 36212 14733, release_year, 10702 3160, has_genre, 30463 3160, has_tags, 30463 3160, has_tags, 5678 3160, release_year, 10702 3160, starred_actors, 5678 16978, has_genre, 30463 16978, release_year, 10702 20846, has_genre, 30463 20846, has_genre, 36066 20846, release_year, 10702 20846, starred_actors, 36610 31008, has_genre, 30463 31008, has_genre, 36212 31008, has_tags, 29019 31008, release_year, 10702 31008, starred_actors, 12389 31008, written_by, 29019 36202, has_genre, 30463 36202, release_year, 10702 27930, has_genre, 36212 27930, release_year, 10702 38250, has_genre, 30463 38250, has_imdb_rating, 11565 38250, has_tags, 10045 38250, has_tags, 30463 38250, has_tags, 24849 38250, release_year, 10702 38250, starred_actors, 24849 21606, has_genre, 36212 21606, has_genre, 8379 21606, has_tags, 37608 21606, release_year, 10702 15589, has_genre, 36212 15589, has_genre, 24593 15589, has_genre, 8379 15589, release_year, 10702 15589, starred_actors, 5337 35150, has_genre, 30463 35150, has_genre, 36212 35150, has_tags, 36212 35150, release_year, 10702 36229, has_genre, 36212 36229, release_year, 10702 18119, has_genre, 30463 18119, release_year, 10702 18119, starred_actors, 29911 18119, starred_actors, 5337 34320, has_genre, 30463 34320, release_year, 10702 30939, has_genre, 36212 30939, release_year, 10702 25610, has_genre, 30463 25610, release_year, 10702 8579, has_genre, 14724 8579, has_genre, 36212 8579, has_tags, 1841 8579, release_year, 10702 8579, starred_actors, 1841 6546, has_genre, 30463 6546, has_tags, 30463 6546, release_year, 10702 39726, has_genre, 39289 39726, has_genre, 30463 39726, has_tags, 21748 39726, has_tags, 30463 39726, release_year, 10702 39726, starred_actors, 21748 39726, starred_actors, 24841 39726, written_by, 21748 3909, has_genre, 39289 3909, has_genre, 30463 3909, release_year, 10702 32542, has_genre, 36066 32542, has_genre, 24593 32542, has_tags, 12903 32542, has_tags, 9791 32542, has_tags, 36066 32542, has_tags, 4139 32542, has_tags, 24593 32542, release_year, 10702 32542, release_year, 9377 528, has_genre, 30463 528, release_year, 10702 18391, has_genre, 36212 18391, has_genre, 8379 18391, release_year, 10702 18391, starred_actors, 22321 18391, starred_actors, 24634 30015, has_genre, 30463 30015, has_tags, 30463 30015, release_year, 10702 7439, has_genre, 30463 7439, has_genre, 36066 7439, has_tags, 24849 7439, has_tags, 16219 7439, release_year, 10702 7439, starred_actors, 24849 7439, written_by, 24849 29323, has_genre, 30463 29323, release_year, 10702 26893, has_genre, 36212 26893, has_tags, 31163 26893, release_year, 10702 14165, has_genre, 36212 14165, has_genre, 8379 14165, release_year, 10702 31100, has_genre, 14724 31100, has_genre, 36212 31100, release_year, 10702 33507, has_genre, 36212 33507, has_tags, 36212 33507, release_year, 10702 34472, has_genre, 36212 34472, release_year, 10702 32627, has_genre, 30463 32627, release_year, 10702 27118, has_genre, 36212 27118, in_language, 31783 27118, release_year, 10702 25620, has_genre, 30463 25620, release_year, 10702 30144, has_genre, 14724 30144, has_genre, 36212 30144, has_tags, 24634 30144, release_year, 10702 30144, starred_actors, 24634 40059, has_genre, 30463 40059, has_genre, 36212 40059, has_tags, 36212 40059, release_year, 10702 40059, starred_actors, 24841 40059, starred_actors, 22676 40059, starred_actors, 2373 32528, has_genre, 14724 32528, has_genre, 36212 32528, release_year, 10702 23735, has_genre, 30463 23735, release_year, 10702 23735, starred_actors, 21996 34288, has_genre, 24177 34288, has_genre, 36212 34288, release_year, 10702 30662, has_genre, 30463 30662, in_language, 31783 30662, release_year, 10702 17667, has_genre, 30463 17667, has_genre, 36212 17667, release_year, 10702 25824, has_genre, 30463 25824, has_genre, 36212 25824, has_genre, 8379 25824, in_language, 31783 25824, release_year, 10702 25824, release_year, 1421 25824, starred_actors, 22676 25824, starred_actors, 36610 21683, has_genre, 36212 21683, release_year, 10702 32423, has_genre, 30463 32423, release_year, 10702 284, has_genre, 36212 284, release_year, 10702 23297, has_genre, 30463 23297, release_year, 10702 4584, has_genre, 36212 4584, has_tags, 37608 4584, release_year, 10702 39, has_genre, 30463 39, release_year, 10702 25772, has_genre, 30463 25772, release_year, 10702 25772, starred_actors, 29911 29601, has_genre, 30463 29601, release_year, 10702 29601, starred_actors, 1841 29601, starred_actors, 29911 33257, has_genre, 36212 33257, release_year, 10702 15283, has_genre, 36212 15283, has_tags, 4329 15283, release_year, 10702 15283, starred_actors, 4329 31600, has_genre, 30463 31600, release_year, 10702 11468, has_genre, 14724 11468, has_genre, 36212 11468, release_year, 10702 11468, release_year, 1421 18913, has_genre, 36212 18913, in_language, 31783 18913, release_year, 10702 33291, has_genre, 36212 33291, release_year, 10702 33607, has_genre, 30463 33607, release_year, 10702 8932, has_genre, 30463 8932, has_genre, 36212 8932, release_year, 10702 38469, has_genre, 36212 38469, has_genre, 24811 38469, release_year, 10702 11883, has_genre, 30463 11883, has_tags, 30463 11883, release_year, 10702 38762, has_genre, 30463 38762, release_year, 10702 29906, has_genre, 39289 29906, has_genre, 30463 29906, release_year, 10702 35064, has_genre, 30463 35064, release_year, 10702 35064, starred_actors, 12389 33479, has_genre, 30463 33479, written_by, 25715 10559, has_genre, 36212 10559, release_year, 10702 8210, has_genre, 30463 8210, release_year, 10702 4345, has_genre, 30463 4345, has_genre, 36212 4345, release_year, 10702 252, has_genre, 30463 252, release_year, 10702 16528, has_genre, 36212 16528, release_year, 10702 20229, has_genre, 30463 20229, has_genre, 36212 20229, release_year, 10702 21817, has_genre, 36212 21817, release_year, 10702 32102, has_genre, 39289 32102, has_genre, 30463 32102, has_genre, 36212 32102, has_genre, 24593 32102, has_tags, 5678 32102, release_year, 10702 32102, starred_actors, 22321 32102, starred_actors, 5678 34438, has_genre, 36212 34438, release_year, 10702 37849, has_genre, 36212 37849, in_language, 31783 37849, release_year, 10702 37565, has_genre, 39289 37565, has_genre, 30463 37565, has_tags, 21748 37565, release_year, 10702 37565, starred_actors, 21748 35557, has_genre, 36212 35557, release_year, 10702 12947, has_genre, 30463 12947, release_year, 10702 15388, has_genre, 36212 15388, has_tags, 10045 15388, release_year, 10702 4037, has_genre, 36212 4037, release_year, 10702 1545, has_genre, 30463 1545, release_year, 10702 18296, has_genre, 36212 18296, starred_actors, 23922 13776, has_genre, 39289 13776, has_genre, 36212 13776, has_imdb_rating, 11565 13776, release_year, 10702 30063, has_genre, 36212 30063, release_year, 10702 26494, has_genre, 36212 26494, has_tags, 34231 26494, release_year, 10702 26494, starred_actors, 34231 33802, has_genre, 36212 33802, has_tags, 6480 33802, in_language, 6480 33802, release_year, 10702 24117, has_genre, 36212 24117, in_language, 31783 24117, in_language, 6480 24117, release_year, 10702 7593, has_genre, 30463 7593, has_tags, 2373 7593, release_year, 10702 7593, starred_actors, 2373 6397, has_genre, 36212 6397, release_year, 10702 1178, has_genre, 36212 1178, release_year, 10702 Question: How are 1991, BOB DENVER, and P.G. WODEHOUSE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1991", "BOB DENVER", "P.G. WODEHOUSE" ], "valid_edges": [ [ "29TH STREET", "has_genre", "COMEDY" ], [ "29TH STREET", "has_genre", "DRAMA" ], [ "29TH STREET", "release_year", "1991" ], [ "A BRIGHTER SUMMER DAY", "has_genre", "DRAMA" ], [ "A BRIGHTER SUMMER DAY", "release_year", "1991" ], [ "A KISS BEFORE DYING", "release_year", "1956" ], [ "A KISS BEFORE DYING", "release_year", "1991" ], [ "A LITTLE STIFF", "has_genre", "COMEDY" ], [ "A LITTLE STIFF", "release_year", "1991" ], [ "ALL I WANT FOR CHRISTMAS", "has_genre", "COMEDY" ], [ "ALL I WANT FOR CHRISTMAS", "release_year", "1991" ], [ "ANOTHER YOU", "has_genre", "COMEDY" ], [ "ANOTHER YOU", "release_year", "1991" ], [ "ANYTHING GOES", "has_genre", "MUSICAL" ], [ "ANYTHING GOES", "in_language", "ENGLISH" ], [ "ANYTHING GOES", "release_year", "1956" ], [ "ANYTHING GOES", "written_by", "P.G. WODEHOUSE" ], [ "AT PLAY IN THE FIELDS OF THE LORD", "has_genre", "DRAMA" ], [ "AT PLAY IN THE FIELDS OF THE LORD", "release_year", "1991" ], [ "BEAUTY AND THE BEAST", "has_genre", "ANIMATION" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "ANIMATION" ], [ "BEAUTY AND THE BEAST", "has_tags", "DISNEY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FAIRY TALE" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "MUSICAL" ], [ "BEAUTY AND THE BEAST", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BEAUTY AND THE BEAST", "has_tags", "STORY" ], [ "BEAUTY AND THE BEAST", "in_language", "FRENCH" ], [ "BEAUTY AND THE BEAST", "release_year", "1991" ], [ "BEAUTY AND THE BEAST", "release_year", "2014" ], [ "BINGO", "has_genre", "COMEDY" ], [ "BINGO", "release_year", "1991" ], [ "BOYZ N THE HOOD", "has_genre", "DRAMA" ], [ "BOYZ N THE HOOD", "has_imdb_rating", "GOOD" ], [ "BOYZ N THE HOOD", "has_tags", "DIRECTORIAL DEBUT" ], [ "BOYZ N THE HOOD", "has_tags", "DRAMA" ], [ "BOYZ N THE HOOD", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BOYZ N THE HOOD", "release_year", "1991" ], [ "BUGSY", "has_genre", "CRIME" ], [ "BUGSY", "has_genre", "DRAMA" ], [ "BUGSY", "release_year", "1991" ], [ "BUGSY", "starred_actors", "ANNETTE BENING" ], [ "CAREER OPPORTUNITIES", "has_genre", "COMEDY" ], [ "CAREER OPPORTUNITIES", "release_year", "1991" ], [ "CAREER OPPORTUNITIES", "written_by", "JOHN HUGHES" ], [ "CARNE", "has_genre", "DRAMA" ], [ "CARNE", "has_tags", "FRENCH" ], [ "CARNE", "in_language", "FRENCH" ], [ "CARNE", "release_year", "1991" ], [ "CITY OF HOPE", "has_genre", "DRAMA" ], [ "CITY OF HOPE", "release_year", "1991" ], [ "CITY SLICKERS", "has_genre", "COMEDY" ], [ "CITY SLICKERS", "release_year", "1991" ], [ "CLASS ACTION", "has_genre", "DRAMA" ], [ "CLASS ACTION", "has_genre", "THRILLER" ], [ "CLASS ACTION", "has_tags", "GENE HACKMAN" ], [ "CLASS ACTION", "release_year", "1991" ], [ "CLASS ACTION", "starred_actors", "GENE HACKMAN" ], [ "CRAZY SAFARI", "has_genre", "COMEDY" ], [ "CRAZY SAFARI", "release_year", "1991" ], [ "CURLY SUE", "directed_by", "JOHN HUGHES" ], [ "CURLY SUE", "has_genre", "COMEDY" ], [ "CURLY SUE", "has_genre", "DRAMA" ], [ "CURLY SUE", "has_tags", "JOHN HUGHES" ], [ "CURLY SUE", "release_year", "1991" ], [ "CURLY SUE", "written_by", "JOHN HUGHES" ], [ "DEFENDING YOUR LIFE", "has_genre", "COMEDY" ], [ "DEFENDING YOUR LIFE", "has_genre", "DRAMA" ], [ "DEFENDING YOUR LIFE", "has_genre", "FANTASY" ], [ "DEFENDING YOUR LIFE", "has_tags", "MERYL STREEP" ], [ "DEFENDING YOUR LIFE", "release_year", "1991" ], [ "DELIRIOUS", "has_genre", "COMEDY" ], [ "DELIRIOUS", "release_year", "1991" ], [ "DELIRIOUS", "starred_actors", "JOHN CANDY" ], [ "DEN OFRIVILLIGE GOLFAREN", "has_genre", "COMEDY" ], [ "DEN OFRIVILLIGE GOLFAREN", "in_language", "ENGLISH" ], [ "DEN OFRIVILLIGE GOLFAREN", "release_year", "1991" ], [ "DIARY OF A HITMAN", "has_genre", "DRAMA" ], [ "DIARY OF A HITMAN", "release_year", "1991" ], [ "DOC HOLLYWOOD", "has_genre", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "release_year", "1991" ], [ "DOC HOLLYWOOD", "starred_actors", "MICHAEL J. FOX" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "has_genre", "COMEDY" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "release_year", "1991" ], [ "DROP DEAD FRED", "has_genre", "COMEDY" ], [ "DROP DEAD FRED", "has_genre", "FANTASY" ], [ "DROP DEAD FRED", "release_year", "1991" ], [ "DROP DEAD FRED", "starred_actors", "PHOEBE CATES" ], [ "DUTCH", "has_genre", "COMEDY" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "DUTCH", "has_tags", "JOHN HUGHES" ], [ "DUTCH", "release_year", "1991" ], [ "DUTCH", "starred_actors", "JOBETH WILLIAMS" ], [ "DUTCH", "written_by", "JOHN HUGHES" ], [ "ERNEST SCARED STUPID", "has_genre", "COMEDY" ], [ "ERNEST SCARED STUPID", "release_year", "1991" ], [ "EYES OF AN ANGEL", "has_genre", "DRAMA" ], [ "EYES OF AN ANGEL", "release_year", "1991" ], [ "FATHER OF THE BRIDE", "has_genre", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_tags", "BD-R" ], [ "FATHER OF THE BRIDE", "has_tags", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_tags", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "release_year", "1991" ], [ "FATHER OF THE BRIDE", "starred_actors", "STEVE MARTIN" ], [ "FLIRTING", "has_genre", "DRAMA" ], [ "FLIRTING", "has_genre", "ROMANCE" ], [ "FLIRTING", "has_tags", "AUSTRALIA" ], [ "FLIRTING", "release_year", "1991" ], [ "FRANKIE AND JOHNNY", "has_genre", "DRAMA" ], [ "FRANKIE AND JOHNNY", "has_genre", "MUSICAL" ], [ "FRANKIE AND JOHNNY", "has_genre", "ROMANCE" ], [ "FRANKIE AND JOHNNY", "release_year", "1991" ], [ "FRANKIE AND JOHNNY", "starred_actors", "NATHAN LANE" ], [ "FRIED GREEN TOMATOES", "has_genre", "COMEDY" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "release_year", "1991" ], [ "GRAND CANYON", "has_genre", "DRAMA" ], [ "GRAND CANYON", "release_year", "1991" ], [ "HE SAID, SHE SAID", "has_genre", "COMEDY" ], [ "HE SAID, SHE SAID", "release_year", "1991" ], [ "HE SAID, SHE SAID", "starred_actors", "KEVIN BACON" ], [ "HE SAID, SHE SAID", "starred_actors", "NATHAN LANE" ], [ "HEAR MY SONG", "has_genre", "COMEDY" ], [ "HEAR MY SONG", "release_year", "1991" ], [ "HIGH HEELS", "has_genre", "DRAMA" ], [ "HIGH HEELS", "release_year", "1991" ], [ "HIGH STRUNG", "has_genre", "COMEDY" ], [ "HIGH STRUNG", "release_year", "1991" ], [ "HOMICIDE", "has_genre", "CRIME" ], [ "HOMICIDE", "has_genre", "DRAMA" ], [ "HOMICIDE", "has_tags", "JOE MANTEGNA" ], [ "HOMICIDE", "release_year", "1991" ], [ "HOMICIDE", "starred_actors", "JOE MANTEGNA" ], [ "HOT SHOTS!", "has_genre", "COMEDY" ], [ "HOT SHOTS!", "has_tags", "COMEDY" ], [ "HOT SHOTS!", "release_year", "1991" ], [ "HUDSON HAWK", "has_genre", "ACTION" ], [ "HUDSON HAWK", "has_genre", "COMEDY" ], [ "HUDSON HAWK", "has_tags", "BRUCE WILLIS" ], [ "HUDSON HAWK", "has_tags", "COMEDY" ], [ "HUDSON HAWK", "release_year", "1991" ], [ "HUDSON HAWK", "starred_actors", "BRUCE WILLIS" ], [ "HUDSON HAWK", "starred_actors", "DANNY AIELLO" ], [ "HUDSON HAWK", "written_by", "BRUCE WILLIS" ], [ "IF LOOKS COULD KILL", "has_genre", "ACTION" ], [ "IF LOOKS COULD KILL", "has_genre", "COMEDY" ], [ "IF LOOKS COULD KILL", "release_year", "1991" ], [ "INTO THE WOODS", "has_genre", "FANTASY" ], [ "INTO THE WOODS", "has_genre", "MUSICAL" ], [ "INTO THE WOODS", "has_tags", "DISNEY" ], [ "INTO THE WOODS", "has_tags", "FAIRY TALE" ], [ "INTO THE WOODS", "has_tags", "FANTASY" ], [ "INTO THE WOODS", "has_tags", "MERYL STREEP" ], [ "INTO THE WOODS", "has_tags", "MUSICAL" ], [ "INTO THE WOODS", "release_year", "1991" ], [ "INTO THE WOODS", "release_year", "2014" ], [ "JOHNNY STECCHINO", "has_genre", "COMEDY" ], [ "JOHNNY STECCHINO", "release_year", "1991" ], [ "JUNGLE FEVER", "has_genre", "DRAMA" ], [ "JUNGLE FEVER", "has_genre", "ROMANCE" ], [ "JUNGLE FEVER", "release_year", "1991" ], [ "JUNGLE FEVER", "starred_actors", "ANNABELLA SCIORRA" ], [ "JUNGLE FEVER", "starred_actors", "WESLEY SNIPES" ], [ "KING RALPH", "has_genre", "COMEDY" ], [ "KING RALPH", "has_tags", "COMEDY" ], [ "KING RALPH", "release_year", "1991" ], [ "L.A. STORY", "has_genre", "COMEDY" ], [ "L.A. STORY", "has_genre", "FANTASY" ], [ "L.A. STORY", "has_tags", "STEVE MARTIN" ], [ "L.A. STORY", "has_tags", "STORY" ], [ "L.A. STORY", "release_year", "1991" ], [ "L.A. STORY", "starred_actors", "STEVE MARTIN" ], [ "L.A. STORY", "written_by", "STEVE MARTIN" ], [ "LIFE STINKS", "has_genre", "COMEDY" ], [ "LIFE STINKS", "release_year", "1991" ], [ "LITTLE MAN TATE", "has_genre", "DRAMA" ], [ "LITTLE MAN TATE", "has_tags", "DIRECTORIAL DEBUT" ], [ "LITTLE MAN TATE", "release_year", "1991" ], [ "MISSISSIPPI MASALA", "has_genre", "DRAMA" ], [ "MISSISSIPPI MASALA", "has_genre", "ROMANCE" ], [ "MISSISSIPPI MASALA", "release_year", "1991" ], [ "MOBSTERS", "has_genre", "CRIME" ], [ "MOBSTERS", "has_genre", "DRAMA" ], [ "MOBSTERS", "release_year", "1991" ], [ "MY GIRL", "has_genre", "DRAMA" ], [ "MY GIRL", "has_tags", "DRAMA" ], [ "MY GIRL", "release_year", "1991" ], [ "MY OWN PRIVATE IDAHO", "has_genre", "DRAMA" ], [ "MY OWN PRIVATE IDAHO", "release_year", "1991" ], [ "MYSTERY DATE", "has_genre", "COMEDY" ], [ "MYSTERY DATE", "release_year", "1991" ], [ "NAKED LUNCH", "has_genre", "DRAMA" ], [ "NAKED LUNCH", "in_language", "ENGLISH" ], [ "NAKED LUNCH", "release_year", "1991" ], [ "NECESSARY ROUGHNESS", "has_genre", "COMEDY" ], [ "NECESSARY ROUGHNESS", "release_year", "1991" ], [ "NEW JACK CITY", "has_genre", "CRIME" ], [ "NEW JACK CITY", "has_genre", "DRAMA" ], [ "NEW JACK CITY", "has_tags", "WESLEY SNIPES" ], [ "NEW JACK CITY", "release_year", "1991" ], [ "NEW JACK CITY", "starred_actors", "WESLEY SNIPES" ], [ "ONCE AROUND", "has_genre", "COMEDY" ], [ "ONCE AROUND", "has_genre", "DRAMA" ], [ "ONCE AROUND", "has_tags", "DRAMA" ], [ "ONCE AROUND", "release_year", "1991" ], [ "ONCE AROUND", "starred_actors", "DANNY AIELLO" ], [ "ONCE AROUND", "starred_actors", "HOLLY HUNTER" ], [ "ONCE AROUND", "starred_actors", "RICHARD DREYFUSS" ], [ "ONE GOOD COP", "has_genre", "CRIME" ], [ "ONE GOOD COP", "has_genre", "DRAMA" ], [ "ONE GOOD COP", "release_year", "1991" ], [ "ONLY THE LONELY", "has_genre", "COMEDY" ], [ "ONLY THE LONELY", "release_year", "1991" ], [ "ONLY THE LONELY", "starred_actors", "JOHN CANDY" ], [ "ONLY YESTERDAY", "has_genre", "ANIMATION" ], [ "ONLY YESTERDAY", "has_genre", "DRAMA" ], [ "ONLY YESTERDAY", "release_year", "1991" ], [ "OSCAR", "has_genre", "COMEDY" ], [ "OSCAR", "in_language", "ENGLISH" ], [ "OSCAR", "release_year", "1991" ], [ "OTHER PEOPLE'S MONEY", "has_genre", "COMEDY" ], [ "OTHER PEOPLE'S MONEY", "has_genre", "DRAMA" ], [ "OTHER PEOPLE'S MONEY", "release_year", "1991" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "ROMANCE" ], [ "PARADISE", "in_language", "ENGLISH" ], [ "PARADISE", "release_year", "1991" ], [ "PARADISE", "release_year", "2013" ], [ "PARADISE", "starred_actors", "HOLLY HUNTER" ], [ "PARADISE", "starred_actors", "PHOEBE CATES" ], [ "PARIS TROUT", "has_genre", "DRAMA" ], [ "PARIS TROUT", "release_year", "1991" ], [ "PERFECTLY NORMAL", "has_genre", "COMEDY" ], [ "PERFECTLY NORMAL", "release_year", "1991" ], [ "POISON", "has_genre", "DRAMA" ], [ "POISON", "release_year", "1991" ], [ "PROBLEM CHILD 2", "has_genre", "COMEDY" ], [ "PROBLEM CHILD 2", "release_year", "1991" ], [ "PROOF", "has_genre", "DRAMA" ], [ "PROOF", "has_tags", "AUSTRALIA" ], [ "PROOF", "release_year", "1991" ], [ "PURE LUCK", "has_genre", "COMEDY" ], [ "PURE LUCK", "release_year", "1991" ], [ "PYRATES", "has_genre", "COMEDY" ], [ "PYRATES", "release_year", "1991" ], [ "PYRATES", "starred_actors", "KEVIN BACON" ], [ "QUEENS LOGIC", "has_genre", "COMEDY" ], [ "QUEENS LOGIC", "release_year", "1991" ], [ "QUEENS LOGIC", "starred_actors", "JOE MANTEGNA" ], [ "QUEENS LOGIC", "starred_actors", "KEVIN BACON" ], [ "RAMBLING ROSE", "has_genre", "DRAMA" ], [ "RAMBLING ROSE", "release_year", "1991" ], [ "REGARDING HENRY", "has_genre", "DRAMA" ], [ "REGARDING HENRY", "has_tags", "ANNETTE BENING" ], [ "REGARDING HENRY", "release_year", "1991" ], [ "REGARDING HENRY", "starred_actors", "ANNETTE BENING" ], [ "RUBIN AND ED", "has_genre", "COMEDY" ], [ "RUBIN AND ED", "release_year", "1991" ], [ "RUSH", "has_genre", "CRIME" ], [ "RUSH", "has_genre", "DRAMA" ], [ "RUSH", "release_year", "1991" ], [ "RUSH", "release_year", "2013" ], [ "SALMONBERRIES", "has_genre", "DRAMA" ], [ "SALMONBERRIES", "in_language", "ENGLISH" ], [ "SALMONBERRIES", "release_year", "1991" ], [ "SCORCHERS", "has_genre", "DRAMA" ], [ "SCORCHERS", "release_year", "1991" ], [ "SEX AND ZEN", "has_genre", "COMEDY" ], [ "SEX AND ZEN", "release_year", "1991" ], [ "SLACKER", "has_genre", "COMEDY" ], [ "SLACKER", "has_genre", "DRAMA" ], [ "SLACKER", "release_year", "1991" ], [ "SLEEPING WITH THE ENEMY", "has_genre", "DRAMA" ], [ "SLEEPING WITH THE ENEMY", "has_genre", "THRILLER" ], [ "SLEEPING WITH THE ENEMY", "release_year", "1991" ], [ "SOAPDISH", "has_genre", "COMEDY" ], [ "SOAPDISH", "has_tags", "COMEDY" ], [ "SOAPDISH", "release_year", "1991" ], [ "SPEAKING OF THE DEVIL", "has_genre", "COMEDY" ], [ "SPEAKING OF THE DEVIL", "release_year", "1991" ], [ "SUBURBAN COMMANDO", "has_genre", "ACTION" ], [ "SUBURBAN COMMANDO", "has_genre", "COMEDY" ], [ "SUBURBAN COMMANDO", "release_year", "1991" ], [ "SWITCH", "has_genre", "COMEDY" ], [ "SWITCH", "release_year", "1991" ], [ "SWITCH", "starred_actors", "JOBETH WILLIAMS" ], [ "THANK YOU, JEEVES!", "has_genre", "COMEDY" ], [ "THANK YOU, JEEVES!", "written_by", "P.G. WODEHOUSE" ], [ "THE ADJUSTER", "has_genre", "DRAMA" ], [ "THE ADJUSTER", "release_year", "1991" ], [ "THE BUTCHER'S WIFE", "has_genre", "COMEDY" ], [ "THE BUTCHER'S WIFE", "release_year", "1991" ], [ "THE COMMITMENTS", "has_genre", "COMEDY" ], [ "THE COMMITMENTS", "has_genre", "DRAMA" ], [ "THE COMMITMENTS", "release_year", "1991" ], [ "THE DARK BACKWARD", "has_genre", "COMEDY" ], [ "THE DARK BACKWARD", "release_year", "1991" ], [ "THE DOCTOR", "has_genre", "DRAMA" ], [ "THE DOCTOR", "release_year", "1991" ], [ "THE FISHER KING", "has_genre", "COMEDY" ], [ "THE FISHER KING", "has_genre", "DRAMA" ], [ "THE FISHER KING", "release_year", "1991" ], [ "THE FIVE HEARTBEATS", "has_genre", "DRAMA" ], [ "THE FIVE HEARTBEATS", "release_year", "1991" ], [ "THE HARD WAY", "has_genre", "ACTION" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_genre", "MUSICAL" ], [ "THE HARD WAY", "has_tags", "MICHAEL J. FOX" ], [ "THE HARD WAY", "release_year", "1991" ], [ "THE HARD WAY", "starred_actors", "ANNABELLA SCIORRA" ], [ "THE HARD WAY", "starred_actors", "MICHAEL J. FOX" ], [ "THE INDIAN RUNNER", "has_genre", "DRAMA" ], [ "THE INDIAN RUNNER", "release_year", "1991" ], [ "THE INNER CIRCLE", "has_genre", "DRAMA" ], [ "THE INNER CIRCLE", "in_language", "ENGLISH" ], [ "THE INNER CIRCLE", "release_year", "1991" ], [ "THE LAST BOY SCOUT", "has_genre", "ACTION" ], [ "THE LAST BOY SCOUT", "has_genre", "COMEDY" ], [ "THE LAST BOY SCOUT", "has_tags", "BRUCE WILLIS" ], [ "THE LAST BOY SCOUT", "release_year", "1991" ], [ "THE LAST BOY SCOUT", "starred_actors", "BRUCE WILLIS" ], [ "THE MAN IN THE MOON", "has_genre", "DRAMA" ], [ "THE MAN IN THE MOON", "release_year", "1991" ], [ "THE MARRYING MAN", "has_genre", "COMEDY" ], [ "THE MARRYING MAN", "release_year", "1991" ], [ "THE PRINCE OF TIDES", "has_genre", "DRAMA" ], [ "THE PRINCE OF TIDES", "has_tags", "BD-R" ], [ "THE PRINCE OF TIDES", "release_year", "1991" ], [ "THE RAPTURE", "has_genre", "DRAMA" ], [ "THE RAPTURE", "release_year", "1991" ], [ "THE SUPER", "has_genre", "COMEDY" ], [ "THE SUPER", "release_year", "1991" ], [ "THE SWEET RIDE", "has_genre", "DRAMA" ], [ "THE SWEET RIDE", "starred_actors", "BOB DENVER" ], [ "TOY SOLDIERS", "has_genre", "ACTION" ], [ "TOY SOLDIERS", "has_genre", "DRAMA" ], [ "TOY SOLDIERS", "has_imdb_rating", "GOOD" ], [ "TOY SOLDIERS", "release_year", "1991" ], [ "TRUE COLORS", "has_genre", "DRAMA" ], [ "TRUE COLORS", "release_year", "1991" ], [ "UNDER SUSPICION", "has_genre", "DRAMA" ], [ "UNDER SUSPICION", "has_tags", "GENE HACKMAN" ], [ "UNDER SUSPICION", "release_year", "1991" ], [ "UNDER SUSPICION", "starred_actors", "GENE HACKMAN" ], [ "UNTIL THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "UNTIL THE END OF THE WORLD", "has_tags", "GERMAN" ], [ "UNTIL THE END OF THE WORLD", "in_language", "GERMAN" ], [ "UNTIL THE END OF THE WORLD", "release_year", "1991" ], [ "VOYAGER", "has_genre", "DRAMA" ], [ "VOYAGER", "in_language", "ENGLISH" ], [ "VOYAGER", "in_language", "GERMAN" ], [ "VOYAGER", "release_year", "1991" ], [ "WHAT ABOUT BOB?", "has_genre", "COMEDY" ], [ "WHAT ABOUT BOB?", "has_tags", "RICHARD DREYFUSS" ], [ "WHAT ABOUT BOB?", "release_year", "1991" ], [ "WHAT ABOUT BOB?", "starred_actors", "RICHARD DREYFUSS" ], [ "WHERE ANGELS FEAR TO TREAD", "has_genre", "DRAMA" ], [ "WHERE ANGELS FEAR TO TREAD", "release_year", "1991" ], [ "WHORE", "has_genre", "DRAMA" ], [ "WHORE", "release_year", "1991" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27410, ANGELS IN THE OUTFIELD 10072, CHRISTINE JEFFS 30463, COMEDY 36212, DRAMA 19463, HEDD WYN 6064, PAUL TURNER 8367, RAIN 29231, SUNSHINE CLEANING 16954, SYLVIA src, edge_attr, dst 27410, has_genre, 30463 19463, directed_by, 6064 19463, has_genre, 36212 8367, directed_by, 10072 8367, has_genre, 36212 8367, written_by, 10072 29231, directed_by, 10072 29231, has_genre, 30463 29231, has_genre, 36212 29231, has_tags, 10072 16954, directed_by, 10072 16954, has_genre, 36212 16954, has_tags, 10072 Question: How are ANGELS IN THE OUTFIELD, CHRISTINE JEFFS, and PAUL TURNER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANGELS IN THE OUTFIELD", "CHRISTINE JEFFS", "PAUL TURNER" ], "valid_edges": [ [ "ANGELS IN THE OUTFIELD", "has_genre", "COMEDY" ], [ "HEDD WYN", "directed_by", "PAUL TURNER" ], [ "HEDD WYN", "has_genre", "DRAMA" ], [ "RAIN", "directed_by", "CHRISTINE JEFFS" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "written_by", "CHRISTINE JEFFS" ], [ "SUNSHINE CLEANING", "directed_by", "CHRISTINE JEFFS" ], [ "SUNSHINE CLEANING", "has_genre", "COMEDY" ], [ "SUNSHINE CLEANING", "has_genre", "DRAMA" ], [ "SUNSHINE CLEANING", "has_tags", "CHRISTINE JEFFS" ], [ "SYLVIA", "directed_by", "CHRISTINE JEFFS" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "has_tags", "CHRISTINE JEFFS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39289, ACTION 8233, AJANTRIK 20356, APARAJITO 14600, APU TRILOGY 16154, ATTACK FORCE 9669, AUDREY WELLS 32624, BENGALI 18764, CHARULATA 35040, DAVID KENNEDY 36212, DRAMA 19204, GUINEVERE 37384, GUNDAY 25862, INDIA 11222, PATHER PANCHALI 28200, SATYAJIT RAY 15523, SOUMITRA CHATTERJEE 32531, THE WORLD OF APU 1491, TRILOGY 11544, UNDER THE TUSCAN SUN src, edge_attr, dst 8233, has_genre, 36212 8233, in_language, 32624 20356, directed_by, 28200 20356, has_genre, 36212 20356, has_tags, 14600 20356, has_tags, 25862 20356, has_tags, 28200 20356, has_tags, 1491 20356, in_language, 32624 20356, written_by, 28200 16154, has_genre, 39289 16154, starred_actors, 35040 18764, directed_by, 28200 18764, has_genre, 36212 18764, has_tags, 28200 18764, in_language, 32624 18764, starred_actors, 15523 18764, written_by, 28200 19204, directed_by, 9669 19204, has_genre, 36212 19204, written_by, 9669 37384, has_genre, 39289 37384, in_language, 32624 11222, directed_by, 28200 11222, has_genre, 36212 11222, has_tags, 14600 11222, has_tags, 25862 11222, has_tags, 28200 11222, has_tags, 1491 11222, in_language, 32624 11222, written_by, 28200 32531, directed_by, 28200 32531, has_genre, 36212 32531, has_tags, 14600 32531, has_tags, 25862 32531, has_tags, 28200 32531, in_language, 32624 32531, starred_actors, 15523 32531, written_by, 28200 11544, directed_by, 9669 11544, has_genre, 36212 11544, written_by, 9669 Question: For what reason are AUDREY WELLS, BENGALI, and DAVID KENNEDY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AUDREY WELLS", "BENGALI", "DAVID KENNEDY" ], "valid_edges": [ [ "AJANTRIK", "has_genre", "DRAMA" ], [ "AJANTRIK", "in_language", "BENGALI" ], [ "APARAJITO", "directed_by", "SATYAJIT RAY" ], [ "APARAJITO", "has_genre", "DRAMA" ], [ "APARAJITO", "has_tags", "APU TRILOGY" ], [ "APARAJITO", "has_tags", "INDIA" ], [ "APARAJITO", "has_tags", "SATYAJIT RAY" ], [ "APARAJITO", "has_tags", "TRILOGY" ], [ "APARAJITO", "in_language", "BENGALI" ], [ "APARAJITO", "written_by", "SATYAJIT RAY" ], [ "ATTACK FORCE", "has_genre", "ACTION" ], [ "ATTACK FORCE", "starred_actors", "DAVID KENNEDY" ], [ "CHARULATA", "directed_by", "SATYAJIT RAY" ], [ "CHARULATA", "has_genre", "DRAMA" ], [ "CHARULATA", "has_tags", "SATYAJIT RAY" ], [ "CHARULATA", "in_language", "BENGALI" ], [ "CHARULATA", "starred_actors", "SOUMITRA CHATTERJEE" ], [ "CHARULATA", "written_by", "SATYAJIT RAY" ], [ "GUINEVERE", "directed_by", "AUDREY WELLS" ], [ "GUINEVERE", "has_genre", "DRAMA" ], [ "GUINEVERE", "written_by", "AUDREY WELLS" ], [ "GUNDAY", "has_genre", "ACTION" ], [ "GUNDAY", "in_language", "BENGALI" ], [ "PATHER PANCHALI", "directed_by", "SATYAJIT RAY" ], [ "PATHER PANCHALI", "has_genre", "DRAMA" ], [ "PATHER PANCHALI", "has_tags", "APU TRILOGY" ], [ "PATHER PANCHALI", "has_tags", "INDIA" ], [ "PATHER PANCHALI", "has_tags", "SATYAJIT RAY" ], [ "PATHER PANCHALI", "has_tags", "TRILOGY" ], [ "PATHER PANCHALI", "in_language", "BENGALI" ], [ "PATHER PANCHALI", "written_by", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "directed_by", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "has_genre", "DRAMA" ], [ "THE WORLD OF APU", "has_tags", "APU TRILOGY" ], [ "THE WORLD OF APU", "has_tags", "INDIA" ], [ "THE WORLD OF APU", "has_tags", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "in_language", "BENGALI" ], [ "THE WORLD OF APU", "starred_actors", "SOUMITRA CHATTERJEE" ], [ "THE WORLD OF APU", "written_by", "SATYAJIT RAY" ], [ "UNDER THE TUSCAN SUN", "directed_by", "AUDREY WELLS" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "written_by", "AUDREY WELLS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21931, 1941 24438, 1993 1006, 1996 33657, A NIGHT AT THE ROXBURY 26763, ACCIÓN MUTANTE 1274, ADDAMS FAMILY VALUES 19308, AIRBORNE 14296, ANOTHER STAKEOUT 35941, ANTZ 5658, BAD BOY BUBBY 3256, BHAJI ON THE BEACH 16023, BLUES BROTHERS 2000 37616, BORN YESTERDAY 10201, BRIAN YUZNA 36392, CANNIBAL! THE MUSICAL 37126, CASTLE FREAK 29831, CB4 11620, CELTIC PRIDE 16386, CITY HUNTER 30463, COMEDY 24459, CONEHEADS 4824, DAGON 6519, DAN AYKROYD 32420, DAVE 36009, DAZED AND CONFUSED 12688, DENNIS PAOLI 36492, DIAMONDS 21558, DOCTOR DETROIT 23612, DOLLS 30803, DOPPELGANGER 31407, DRAGNET 7815, DRÖMKÅKEN 29122, ED AND HIS DEAD MOTHER 254, EDMOND 28612, ELECTRIC DREAMS 20426, ERNEST RIDES AGAIN 10648, EVEN COWGIRLS GET THE BLUES 20441, EXIT TO EDEN 11065, FATAL INSTINCT 4297, FATHER HOOD 26053, FOR LOVE OR MONEY 278, FORTRESS 845, FREAKED 3270, FROM BEYOND 39198, GETTING AWAY WITH MURDER 29393, GHOSTBUSTERS 30959, GROSSE POINTE BLANK 4680, GROUNDHOG DAY 10918, GRUMPY OLD MEN 19871, GYPSY 25648, HEART AND SOULS 36376, HEXED 17578, HOCUS POCUS 5870, HORROR 5068, HOT SHOTS! PART DEUX 18026, INDIAN SUMMER 34092, IT CAME FROM HOLLYWOOD 37202, IT'S PAT 28152, JEFFREY COMBS 1841, JOE MANTEGNA 7228, JOSH AND S.A.M. 8587, KEN FOREE 27812, LA ESTRATEGIA DEL CARACOL 39841, LAST ACTION HERO 32278, LEPRECHAUN 12766, LIFE WITH MIKEY 9946, LOADED WEAPON 1 35654, LOOSE CANNONS 14647, LOVE BITES 16700, LOVECRAFT 17855, MACGRUBER 14587, MAD DOG AND GLORY 17663, MADE IN AMERICA 39670, MAN'S BEST FRIEND 28789, MANHATTAN MURDER MYSTERY 39913, MATINEE 19791, MEAN GIRLS 15787, MONEY FOR NOTHING 5930, MR. WONDERFUL 862, MRS. DOUBTFIRE 31377, MUCH ADO ABOUT NOTHING 8519, MY BOYFRIEND'S BACK 37465, MY FELLOW AMERICANS 28963, MY GIRL 2 25950, MY STEPMOTHER IS AN ALIEN 11905, NAKED IN NEW YORK 30766, NEIGHBORS 27284, PARIS, FRANCE 11005, PAUL KOSLO 35198, RAT 39358, RE-ANIMATOR 33471, ROBOT JOX 4602, ROOKIE OF THE YEAR 18201, SATURDAY NIGHT LIVE 12936, SGT. BILKO 26699, SHORT CUTS 31824, SIX DEGREES OF SEPARATION 36264, SLEEPLESS IN SEATTLE 30664, SMOKING/NO SMOKING 10666, SO I MARRIED AN AXE MURDERER 29811, SON IN LAW 19541, SPACE TRUCKERS 18657, SPIES LIKE US 11421, STEFANO QUANTESTORIE 29425, STEVE BARRON 18809, STUART GORDON 22718, STUART SAVES HIS FAMILY 40061, STUCK 25480, SUPER MARIO BROS. 27511, SUPERSTAR 39976, TEENAGE MUTANT NINJA TURTLES 27760, THE BEVERLY HILLBILLIES 26008, THE BLUES BROTHERS 12710, THE COUCH TRIP 23699, THE DENTIST 7087, THE GREAT OUTDOORS 39842, THE LADIES MAN 1648, THE METEOR MAN 37211, THE PIT AND THE PENDULUM 15471, THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM 7816, THE THREE MUSKETEERS 9725, THE WONDERFUL ICE CREAM SUIT 27619, THE WRONG TROUSERS 24929, THREE OF HEARTS 24811, THRILLER 18863, TRADING PLACES 31130, UNDERCOVER BLUES 25299, UNTAMED HEART 38839, WAYNE'S WORLD 5306, WAYNE'S WORLD 2 4857, WEEKEND AT BERNIE'S II 18181, WHO'S THE MAN? 1287, WILDER NAPALM 22756, WINDOW TO PARIS 30255, YOGI BEAR src, edge_attr, dst 21931, has_genre, 30463 21931, starred_actors, 6519 33657, has_genre, 30463 33657, has_tags, 18201 26763, has_genre, 30463 26763, release_year, 24438 1274, has_genre, 30463 1274, release_year, 24438 19308, has_genre, 30463 19308, has_tags, 30463 19308, release_year, 24438 14296, has_genre, 30463 14296, release_year, 24438 35941, has_genre, 30463 35941, starred_actors, 6519 5658, has_genre, 30463 5658, release_year, 24438 3256, has_genre, 30463 3256, release_year, 24438 16023, has_genre, 30463 16023, has_tags, 6519 16023, starred_actors, 6519 16023, written_by, 6519 37616, has_genre, 30463 37616, release_year, 24438 36392, has_genre, 30463 36392, has_tags, 30463 36392, release_year, 24438 37126, directed_by, 18809 37126, has_genre, 5870 37126, written_by, 18809 29831, has_genre, 30463 29831, release_year, 24438 11620, has_genre, 30463 11620, has_tags, 6519 11620, starred_actors, 6519 16386, has_genre, 30463 16386, release_year, 24438 24459, directed_by, 29425 24459, has_genre, 30463 24459, has_tags, 6519 24459, has_tags, 18201 24459, has_tags, 29425 24459, release_year, 24438 24459, starred_actors, 6519 24459, written_by, 6519 4824, directed_by, 18809 4824, has_genre, 5870 4824, written_by, 12688 32420, has_genre, 30463 32420, release_year, 24438 36009, has_genre, 30463 36009, release_year, 24438 36492, has_genre, 30463 36492, starred_actors, 6519 21558, has_genre, 30463 21558, starred_actors, 6519 23612, directed_by, 18809 23612, has_genre, 5870 23612, has_tags, 23612 30803, has_genre, 30463 30803, release_year, 24438 31407, has_genre, 30463 31407, starred_actors, 6519 31407, written_by, 6519 7815, has_genre, 30463 7815, release_year, 24438 29122, has_genre, 30463 29122, release_year, 24438 254, directed_by, 18809 254, has_genre, 24811 254, starred_actors, 1841 28612, directed_by, 29425 28612, has_genre, 30463 20426, has_genre, 30463 20426, release_year, 24438 10648, has_genre, 30463 10648, release_year, 24438 20441, has_genre, 30463 20441, starred_actors, 6519 11065, has_genre, 30463 11065, release_year, 24438 4297, has_genre, 30463 4297, release_year, 24438 26053, has_genre, 30463 26053, release_year, 24438 278, directed_by, 18809 278, has_genre, 24811 845, has_genre, 30463 845, release_year, 24438 3270, directed_by, 18809 3270, has_genre, 5870 3270, has_tags, 16700 3270, starred_actors, 28152 3270, starred_actors, 8587 3270, written_by, 10201 3270, written_by, 12688 3270, written_by, 18809 39198, has_genre, 30463 39198, starred_actors, 6519 29393, has_genre, 30463 29393, has_tags, 30463 29393, has_tags, 6519 29393, has_tags, 18201 29393, starred_actors, 6519 29393, written_by, 6519 30959, has_genre, 30463 30959, has_tags, 6519 30959, starred_actors, 6519 4680, has_genre, 30463 4680, has_tags, 30463 4680, release_year, 24438 10918, has_genre, 30463 10918, has_tags, 30463 10918, release_year, 24438 19871, has_genre, 30463 19871, release_year, 24438 25648, has_genre, 30463 25648, release_year, 24438 36376, has_genre, 30463 36376, release_year, 24438 17578, has_genre, 30463 17578, release_year, 24438 5068, has_genre, 30463 5068, has_tags, 30463 5068, release_year, 24438 18026, has_genre, 30463 18026, release_year, 24438 34092, has_genre, 30463 34092, starred_actors, 6519 37202, has_genre, 30463 37202, has_tags, 18201 7228, has_genre, 30463 7228, release_year, 24438 27812, has_genre, 30463 27812, release_year, 24438 39841, has_genre, 30463 39841, has_tags, 30463 39841, release_year, 24438 32278, has_genre, 30463 32278, release_year, 24438 12766, has_genre, 30463 12766, release_year, 24438 9946, has_genre, 30463 9946, release_year, 24438 35654, has_genre, 30463 35654, starred_actors, 6519 14647, has_genre, 30463 14647, release_year, 24438 17855, has_genre, 30463 17855, has_tags, 30463 17855, has_tags, 18201 14587, has_genre, 30463 14587, release_year, 24438 17663, has_genre, 30463 17663, release_year, 24438 39670, has_genre, 30463 39670, release_year, 24438 28789, has_genre, 30463 28789, release_year, 24438 39913, has_genre, 30463 39913, release_year, 24438 19791, has_genre, 30463 19791, has_tags, 30463 19791, has_tags, 18201 15787, has_genre, 30463 15787, release_year, 24438 5930, has_genre, 30463 5930, release_year, 24438 862, has_genre, 30463 862, has_tags, 30463 862, release_year, 24438 31377, has_genre, 30463 31377, has_tags, 30463 31377, release_year, 24438 8519, has_genre, 30463 8519, release_year, 24438 37465, has_genre, 30463 37465, has_tags, 6519 37465, starred_actors, 6519 28963, has_genre, 30463 28963, has_tags, 6519 28963, starred_actors, 6519 25950, has_genre, 30463 25950, starred_actors, 6519 11905, has_genre, 30463 11905, release_year, 24438 30766, has_genre, 30463 30766, starred_actors, 6519 27284, has_genre, 30463 27284, release_year, 24438 35198, directed_by, 29425 35198, has_genre, 30463 39358, directed_by, 18809 39358, has_genre, 30463 39358, has_genre, 5870 39358, has_tags, 5870 39358, has_tags, 16700 39358, starred_actors, 28152 39358, written_by, 18809 33471, directed_by, 18809 33471, starred_actors, 11005 33471, written_by, 18809 4602, has_genre, 30463 4602, release_year, 24438 12936, has_genre, 30463 12936, starred_actors, 6519 26699, has_genre, 30463 26699, release_year, 24438 31824, has_genre, 30463 31824, release_year, 24438 36264, has_genre, 30463 36264, has_tags, 30463 36264, release_year, 24438 30664, has_genre, 30463 30664, release_year, 24438 10666, has_genre, 30463 10666, has_tags, 30463 10666, release_year, 24438 29811, has_genre, 30463 29811, release_year, 24438 19541, directed_by, 18809 19541, has_genre, 30463 19541, release_year, 1006 19541, written_by, 18809 18657, has_genre, 30463 18657, starred_actors, 6519 18657, written_by, 6519 11421, has_genre, 30463 11421, release_year, 24438 22718, has_genre, 30463 22718, has_tags, 18201 40061, directed_by, 18809 40061, has_genre, 24811 40061, written_by, 18809 25480, has_genre, 30463 25480, has_tags, 30463 25480, release_year, 24438 27511, has_genre, 30463 27511, has_tags, 18201 39976, directed_by, 29425 39976, has_genre, 30463 39976, has_tags, 29425 27760, has_genre, 30463 27760, release_year, 24438 26008, has_genre, 30463 26008, has_tags, 30463 26008, has_tags, 6519 26008, has_tags, 18201 26008, starred_actors, 6519 26008, written_by, 6519 12710, has_genre, 30463 12710, starred_actors, 6519 23699, directed_by, 10201 23699, has_genre, 5870 23699, release_year, 1006 23699, starred_actors, 8587 23699, written_by, 12688 23699, written_by, 18809 7087, has_genre, 30463 7087, starred_actors, 6519 39842, has_genre, 30463 39842, has_tags, 18201 1648, has_genre, 30463 1648, release_year, 24438 37211, directed_by, 18809 37211, has_genre, 5870 15471, has_genre, 30463 15471, release_year, 24438 7816, has_genre, 30463 7816, release_year, 24438 9725, directed_by, 18809 9725, starred_actors, 1841 27619, has_genre, 30463 27619, has_tags, 30463 27619, release_year, 24438 24929, has_genre, 30463 24929, release_year, 24438 18863, has_genre, 30463 18863, has_tags, 30463 18863, has_tags, 6519 18863, starred_actors, 6519 31130, has_genre, 30463 31130, release_year, 24438 25299, has_genre, 30463 25299, release_year, 24438 38839, has_genre, 30463 38839, has_tags, 30463 38839, has_tags, 18201 5306, has_genre, 30463 5306, has_tags, 18201 5306, release_year, 24438 4857, has_genre, 30463 4857, release_year, 24438 18181, has_genre, 30463 18181, release_year, 24438 1287, has_genre, 30463 1287, release_year, 24438 22756, has_genre, 30463 22756, release_year, 24438 30255, has_genre, 30463 30255, starred_actors, 6519 Question: How are CONEHEADS, PAUL KOSLO, and STUART GORDON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CONEHEADS", "PAUL KOSLO", "STUART GORDON" ], "valid_edges": [ [ "1941", "has_genre", "COMEDY" ], [ "1941", "starred_actors", "DAN AYKROYD" ], [ "A NIGHT AT THE ROXBURY", "has_genre", "COMEDY" ], [ "A NIGHT AT THE ROXBURY", "has_tags", "SATURDAY NIGHT LIVE" ], [ "ACCIÓN MUTANTE", "has_genre", "COMEDY" ], [ "ACCIÓN MUTANTE", "release_year", "1993" ], [ "ADDAMS FAMILY VALUES", "has_genre", "COMEDY" ], [ "ADDAMS FAMILY VALUES", "release_year", "1993" ], [ "AIRBORNE", "has_genre", "COMEDY" ], [ "AIRBORNE", "has_tags", "COMEDY" ], [ "AIRBORNE", "release_year", "1993" ], [ "ANOTHER STAKEOUT", "has_genre", "COMEDY" ], [ "ANOTHER STAKEOUT", "release_year", "1993" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "starred_actors", "DAN AYKROYD" ], [ "BAD BOY BUBBY", "has_genre", "COMEDY" ], [ "BAD BOY BUBBY", "release_year", "1993" ], [ "BHAJI ON THE BEACH", "has_genre", "COMEDY" ], [ "BHAJI ON THE BEACH", "release_year", "1993" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "has_tags", "DAN AYKROYD" ], [ "BLUES BROTHERS 2000", "starred_actors", "DAN AYKROYD" ], [ "BLUES BROTHERS 2000", "written_by", "DAN AYKROYD" ], [ "BORN YESTERDAY", "has_genre", "COMEDY" ], [ "BORN YESTERDAY", "release_year", "1993" ], [ "CANNIBAL! THE MUSICAL", "has_genre", "COMEDY" ], [ "CANNIBAL! THE MUSICAL", "has_tags", "COMEDY" ], [ "CANNIBAL! THE MUSICAL", "release_year", "1993" ], [ "CASTLE FREAK", "directed_by", "STUART GORDON" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "written_by", "STUART GORDON" ], [ "CB4", "has_genre", "COMEDY" ], [ "CB4", "release_year", "1993" ], [ "CELTIC PRIDE", "has_genre", "COMEDY" ], [ "CELTIC PRIDE", "has_tags", "DAN AYKROYD" ], [ "CELTIC PRIDE", "starred_actors", "DAN AYKROYD" ], [ "CITY HUNTER", "has_genre", "COMEDY" ], [ "CITY HUNTER", "release_year", "1993" ], [ "CONEHEADS", "directed_by", "STEVE BARRON" ], [ "CONEHEADS", "has_genre", "COMEDY" ], [ "CONEHEADS", "has_tags", "DAN AYKROYD" ], [ "CONEHEADS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "CONEHEADS", "has_tags", "STEVE BARRON" ], [ "CONEHEADS", "release_year", "1993" ], [ "CONEHEADS", "starred_actors", "DAN AYKROYD" ], [ "CONEHEADS", "written_by", "DAN AYKROYD" ], [ "DAGON", "directed_by", "STUART GORDON" ], [ "DAGON", "has_genre", "HORROR" ], [ "DAGON", "written_by", "DENNIS PAOLI" ], [ "DAVE", "has_genre", "COMEDY" ], [ "DAVE", "release_year", "1993" ], [ "DAZED AND CONFUSED", "has_genre", "COMEDY" ], [ "DAZED AND CONFUSED", "release_year", "1993" ], [ "DIAMONDS", "has_genre", "COMEDY" ], [ "DIAMONDS", "starred_actors", "DAN AYKROYD" ], [ "DOCTOR DETROIT", "has_genre", "COMEDY" ], [ "DOCTOR DETROIT", "starred_actors", "DAN AYKROYD" ], [ "DOLLS", "directed_by", "STUART GORDON" ], [ "DOLLS", "has_genre", "HORROR" ], [ "DOLLS", "has_tags", "DOLLS" ], [ "DOPPELGANGER", "has_genre", "COMEDY" ], [ "DOPPELGANGER", "release_year", "1993" ], [ "DRAGNET", "has_genre", "COMEDY" ], [ "DRAGNET", "starred_actors", "DAN AYKROYD" ], [ "DRAGNET", "written_by", "DAN AYKROYD" ], [ "DRÖMKÅKEN", "has_genre", "COMEDY" ], [ "DRÖMKÅKEN", "release_year", "1993" ], [ "ED AND HIS DEAD MOTHER", "has_genre", "COMEDY" ], [ "ED AND HIS DEAD MOTHER", "release_year", "1993" ], [ "EDMOND", "directed_by", "STUART GORDON" ], [ "EDMOND", "has_genre", "THRILLER" ], [ "EDMOND", "starred_actors", "JOE MANTEGNA" ], [ "ELECTRIC DREAMS", "directed_by", "STEVE BARRON" ], [ "ELECTRIC DREAMS", "has_genre", "COMEDY" ], [ "ERNEST RIDES AGAIN", "has_genre", "COMEDY" ], [ "ERNEST RIDES AGAIN", "release_year", "1993" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "COMEDY" ], [ "EVEN COWGIRLS GET THE BLUES", "release_year", "1993" ], [ "EXIT TO EDEN", "has_genre", "COMEDY" ], [ "EXIT TO EDEN", "starred_actors", "DAN AYKROYD" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "release_year", "1993" ], [ "FATHER HOOD", "has_genre", "COMEDY" ], [ "FATHER HOOD", "release_year", "1993" ], [ "FOR LOVE OR MONEY", "has_genre", "COMEDY" ], [ "FOR LOVE OR MONEY", "release_year", "1993" ], [ "FORTRESS", "directed_by", "STUART GORDON" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FREAKED", "has_genre", "COMEDY" ], [ "FREAKED", "release_year", "1993" ], [ "FROM BEYOND", "directed_by", "STUART GORDON" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "has_tags", "LOVECRAFT" ], [ "FROM BEYOND", "starred_actors", "JEFFREY COMBS" ], [ "FROM BEYOND", "starred_actors", "KEN FOREE" ], [ "FROM BEYOND", "written_by", "BRIAN YUZNA" ], [ "FROM BEYOND", "written_by", "DENNIS PAOLI" ], [ "FROM BEYOND", "written_by", "STUART GORDON" ], [ "GETTING AWAY WITH MURDER", "has_genre", "COMEDY" ], [ "GETTING AWAY WITH MURDER", "starred_actors", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "has_genre", "COMEDY" ], [ "GHOSTBUSTERS", "has_tags", "COMEDY" ], [ "GHOSTBUSTERS", "has_tags", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "GHOSTBUSTERS", "starred_actors", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "written_by", "DAN AYKROYD" ], [ "GROSSE POINTE BLANK", "has_genre", "COMEDY" ], [ "GROSSE POINTE BLANK", "has_tags", "DAN AYKROYD" ], [ "GROSSE POINTE BLANK", "starred_actors", "DAN AYKROYD" ], [ "GROUNDHOG DAY", "has_genre", "COMEDY" ], [ "GROUNDHOG DAY", "has_tags", "COMEDY" ], [ "GROUNDHOG DAY", "release_year", "1993" ], [ "GRUMPY OLD MEN", "has_genre", "COMEDY" ], [ "GRUMPY OLD MEN", "has_tags", "COMEDY" ], [ "GRUMPY OLD MEN", "release_year", "1993" ], [ "GYPSY", "has_genre", "COMEDY" ], [ "GYPSY", "release_year", "1993" ], [ "HEART AND SOULS", "has_genre", "COMEDY" ], [ "HEART AND SOULS", "release_year", "1993" ], [ "HEXED", "has_genre", "COMEDY" ], [ "HEXED", "release_year", "1993" ], [ "HOCUS POCUS", "has_genre", "COMEDY" ], [ "HOCUS POCUS", "release_year", "1993" ], [ "HOT SHOTS! PART DEUX", "has_genre", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "has_tags", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "release_year", "1993" ], [ "INDIAN SUMMER", "has_genre", "COMEDY" ], [ "INDIAN SUMMER", "release_year", "1993" ], [ "IT CAME FROM HOLLYWOOD", "has_genre", "COMEDY" ], [ "IT CAME FROM HOLLYWOOD", "starred_actors", "DAN AYKROYD" ], [ "IT'S PAT", "has_genre", "COMEDY" ], [ "IT'S PAT", "has_tags", "SATURDAY NIGHT LIVE" ], [ "JOSH AND S.A.M.", "has_genre", "COMEDY" ], [ "JOSH AND S.A.M.", "release_year", "1993" ], [ "LA ESTRATEGIA DEL CARACOL", "has_genre", "COMEDY" ], [ "LA ESTRATEGIA DEL CARACOL", "release_year", "1993" ], [ "LAST ACTION HERO", "has_genre", "COMEDY" ], [ "LAST ACTION HERO", "has_tags", "COMEDY" ], [ "LAST ACTION HERO", "release_year", "1993" ], [ "LEPRECHAUN", "has_genre", "COMEDY" ], [ "LEPRECHAUN", "release_year", "1993" ], [ "LIFE WITH MIKEY", "has_genre", "COMEDY" ], [ "LIFE WITH MIKEY", "release_year", "1993" ], [ "LOADED WEAPON 1", "has_genre", "COMEDY" ], [ "LOADED WEAPON 1", "release_year", "1993" ], [ "LOOSE CANNONS", "has_genre", "COMEDY" ], [ "LOOSE CANNONS", "starred_actors", "DAN AYKROYD" ], [ "LOVE BITES", "has_genre", "COMEDY" ], [ "LOVE BITES", "release_year", "1993" ], [ "MACGRUBER", "has_genre", "COMEDY" ], [ "MACGRUBER", "has_tags", "COMEDY" ], [ "MACGRUBER", "has_tags", "SATURDAY NIGHT LIVE" ], [ "MAD DOG AND GLORY", "has_genre", "COMEDY" ], [ "MAD DOG AND GLORY", "release_year", "1993" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "release_year", "1993" ], [ "MAN'S BEST FRIEND", "has_genre", "COMEDY" ], [ "MAN'S BEST FRIEND", "release_year", "1993" ], [ "MANHATTAN MURDER MYSTERY", "has_genre", "COMEDY" ], [ "MANHATTAN MURDER MYSTERY", "release_year", "1993" ], [ "MATINEE", "has_genre", "COMEDY" ], [ "MATINEE", "release_year", "1993" ], [ "MEAN GIRLS", "has_genre", "COMEDY" ], [ "MEAN GIRLS", "has_tags", "COMEDY" ], [ "MEAN GIRLS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "MONEY FOR NOTHING", "has_genre", "COMEDY" ], [ "MONEY FOR NOTHING", "release_year", "1993" ], [ "MR. WONDERFUL", "has_genre", "COMEDY" ], [ "MR. WONDERFUL", "release_year", "1993" ], [ "MRS. DOUBTFIRE", "has_genre", "COMEDY" ], [ "MRS. DOUBTFIRE", "has_tags", "COMEDY" ], [ "MRS. DOUBTFIRE", "release_year", "1993" ], [ "MUCH ADO ABOUT NOTHING", "has_genre", "COMEDY" ], [ "MUCH ADO ABOUT NOTHING", "has_tags", "COMEDY" ], [ "MUCH ADO ABOUT NOTHING", "release_year", "1993" ], [ "MY BOYFRIEND'S BACK", "has_genre", "COMEDY" ], [ "MY BOYFRIEND'S BACK", "release_year", "1993" ], [ "MY FELLOW AMERICANS", "has_genre", "COMEDY" ], [ "MY FELLOW AMERICANS", "has_tags", "DAN AYKROYD" ], [ "MY FELLOW AMERICANS", "starred_actors", "DAN AYKROYD" ], [ "MY GIRL 2", "has_genre", "COMEDY" ], [ "MY GIRL 2", "has_tags", "DAN AYKROYD" ], [ "MY GIRL 2", "starred_actors", "DAN AYKROYD" ], [ "MY STEPMOTHER IS AN ALIEN", "has_genre", "COMEDY" ], [ "MY STEPMOTHER IS AN ALIEN", "starred_actors", "DAN AYKROYD" ], [ "NAKED IN NEW YORK", "has_genre", "COMEDY" ], [ "NAKED IN NEW YORK", "release_year", "1993" ], [ "NEIGHBORS", "has_genre", "COMEDY" ], [ "NEIGHBORS", "starred_actors", "DAN AYKROYD" ], [ "PARIS, FRANCE", "has_genre", "COMEDY" ], [ "PARIS, FRANCE", "release_year", "1993" ], [ "RAT", "directed_by", "STEVE BARRON" ], [ "RAT", "has_genre", "COMEDY" ], [ "RE-ANIMATOR", "directed_by", "STUART GORDON" ], [ "RE-ANIMATOR", "has_genre", "COMEDY" ], [ "RE-ANIMATOR", "has_genre", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "LOVECRAFT" ], [ "RE-ANIMATOR", "starred_actors", "JEFFREY COMBS" ], [ "RE-ANIMATOR", "written_by", "STUART GORDON" ], [ "ROBOT JOX", "directed_by", "STUART GORDON" ], [ "ROBOT JOX", "starred_actors", "PAUL KOSLO" ], [ "ROBOT JOX", "written_by", "STUART GORDON" ], [ "ROOKIE OF THE YEAR", "has_genre", "COMEDY" ], [ "ROOKIE OF THE YEAR", "release_year", "1993" ], [ "SGT. BILKO", "has_genre", "COMEDY" ], [ "SGT. BILKO", "starred_actors", "DAN AYKROYD" ], [ "SHORT CUTS", "has_genre", "COMEDY" ], [ "SHORT CUTS", "release_year", "1993" ], [ "SIX DEGREES OF SEPARATION", "has_genre", "COMEDY" ], [ "SIX DEGREES OF SEPARATION", "release_year", "1993" ], [ "SLEEPLESS IN SEATTLE", "has_genre", "COMEDY" ], [ "SLEEPLESS IN SEATTLE", "has_tags", "COMEDY" ], [ "SLEEPLESS IN SEATTLE", "release_year", "1993" ], [ "SMOKING/NO SMOKING", "has_genre", "COMEDY" ], [ "SMOKING/NO SMOKING", "release_year", "1993" ], [ "SO I MARRIED AN AXE MURDERER", "has_genre", "COMEDY" ], [ "SO I MARRIED AN AXE MURDERER", "has_tags", "COMEDY" ], [ "SO I MARRIED AN AXE MURDERER", "release_year", "1993" ], [ "SON IN LAW", "has_genre", "COMEDY" ], [ "SON IN LAW", "release_year", "1993" ], [ "SPACE TRUCKERS", "directed_by", "STUART GORDON" ], [ "SPACE TRUCKERS", "has_genre", "COMEDY" ], [ "SPACE TRUCKERS", "release_year", "1996" ], [ "SPACE TRUCKERS", "written_by", "STUART GORDON" ], [ "SPIES LIKE US", "has_genre", "COMEDY" ], [ "SPIES LIKE US", "starred_actors", "DAN AYKROYD" ], [ "SPIES LIKE US", "written_by", "DAN AYKROYD" ], [ "STEFANO QUANTESTORIE", "has_genre", "COMEDY" ], [ "STEFANO QUANTESTORIE", "release_year", "1993" ], [ "STUART SAVES HIS FAMILY", "has_genre", "COMEDY" ], [ "STUART SAVES HIS FAMILY", "has_tags", "SATURDAY NIGHT LIVE" ], [ "STUCK", "directed_by", "STUART GORDON" ], [ "STUCK", "has_genre", "THRILLER" ], [ "STUCK", "written_by", "STUART GORDON" ], [ "SUPER MARIO BROS.", "has_genre", "COMEDY" ], [ "SUPER MARIO BROS.", "has_tags", "COMEDY" ], [ "SUPER MARIO BROS.", "release_year", "1993" ], [ "SUPERSTAR", "has_genre", "COMEDY" ], [ "SUPERSTAR", "has_tags", "SATURDAY NIGHT LIVE" ], [ "TEENAGE MUTANT NINJA TURTLES", "directed_by", "STEVE BARRON" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "COMEDY" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_tags", "STEVE BARRON" ], [ "THE BEVERLY HILLBILLIES", "has_genre", "COMEDY" ], [ "THE BEVERLY HILLBILLIES", "release_year", "1993" ], [ "THE BLUES BROTHERS", "has_genre", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "DAN AYKROYD" ], [ "THE BLUES BROTHERS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "THE BLUES BROTHERS", "starred_actors", "DAN AYKROYD" ], [ "THE BLUES BROTHERS", "written_by", "DAN AYKROYD" ], [ "THE COUCH TRIP", "has_genre", "COMEDY" ], [ "THE COUCH TRIP", "starred_actors", "DAN AYKROYD" ], [ "THE DENTIST", "directed_by", "BRIAN YUZNA" ], [ "THE DENTIST", "has_genre", "HORROR" ], [ "THE DENTIST", "release_year", "1996" ], [ "THE DENTIST", "starred_actors", "KEN FOREE" ], [ "THE DENTIST", "written_by", "DENNIS PAOLI" ], [ "THE DENTIST", "written_by", "STUART GORDON" ], [ "THE GREAT OUTDOORS", "has_genre", "COMEDY" ], [ "THE GREAT OUTDOORS", "starred_actors", "DAN AYKROYD" ], [ "THE LADIES MAN", "has_genre", "COMEDY" ], [ "THE LADIES MAN", "has_tags", "SATURDAY NIGHT LIVE" ], [ "THE METEOR MAN", "has_genre", "COMEDY" ], [ "THE METEOR MAN", "release_year", "1993" ], [ "THE PIT AND THE PENDULUM", "directed_by", "STUART GORDON" ], [ "THE PIT AND THE PENDULUM", "has_genre", "HORROR" ], [ "THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM", "has_genre", "COMEDY" ], [ "THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM", "release_year", "1993" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "release_year", "1993" ], [ "THE WONDERFUL ICE CREAM SUIT", "directed_by", "STUART GORDON" ], [ "THE WONDERFUL ICE CREAM SUIT", "starred_actors", "JOE MANTEGNA" ], [ "THE WRONG TROUSERS", "has_genre", "COMEDY" ], [ "THE WRONG TROUSERS", "has_tags", "COMEDY" ], [ "THE WRONG TROUSERS", "release_year", "1993" ], [ "THREE OF HEARTS", "has_genre", "COMEDY" ], [ "THREE OF HEARTS", "release_year", "1993" ], [ "TRADING PLACES", "has_genre", "COMEDY" ], [ "TRADING PLACES", "has_tags", "COMEDY" ], [ "TRADING PLACES", "has_tags", "DAN AYKROYD" ], [ "TRADING PLACES", "starred_actors", "DAN AYKROYD" ], [ "UNDERCOVER BLUES", "has_genre", "COMEDY" ], [ "UNDERCOVER BLUES", "release_year", "1993" ], [ "UNTAMED HEART", "has_genre", "COMEDY" ], [ "UNTAMED HEART", "release_year", "1993" ], [ "WAYNE'S WORLD", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "SATURDAY NIGHT LIVE" ], [ "WAYNE'S WORLD 2", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD 2", "has_tags", "SATURDAY NIGHT LIVE" ], [ "WAYNE'S WORLD 2", "release_year", "1993" ], [ "WEEKEND AT BERNIE'S II", "has_genre", "COMEDY" ], [ "WEEKEND AT BERNIE'S II", "release_year", "1993" ], [ "WHO'S THE MAN?", "has_genre", "COMEDY" ], [ "WHO'S THE MAN?", "release_year", "1993" ], [ "WILDER NAPALM", "has_genre", "COMEDY" ], [ "WILDER NAPALM", "release_year", "1993" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "release_year", "1993" ], [ "YOGI BEAR", "has_genre", "COMEDY" ], [ "YOGI BEAR", "starred_actors", "DAN AYKROYD" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 2043, 9 SONGS 5321, A GOOD WOMAN 38203, A HOLE IN MY HEART 20026, A HOME AT THE END OF THE WORLD 5441, A LOVE SONG FOR BOBBY LONG 11398, A MOMENT TO REMEMBER 20576, A WORLD WITHOUT THIEVES 30109, A.C.O.D. 27020, AGAINST THE ROPES 1698, ALFIE 34789, BAD EDUCATION 18380, BEFORE SUNSET 1815, BEFORE THE FALL 2137, BEING JULIA 20294, BIRTH 2856, BROTHERS 20489, CHANGING TIMES 30885, CLOSER 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 32049, CRASH 34180, CRUEL INTENTIONS 3 15696, DAY AND NIGHT 27982, DEAR FRANKIE 16961, DIRTY FILTHY LOVE 2283, DIVORCE 15779, DORIAN BLUES 1441, DOWN TO THE BONE 36212, DRAMA 1329, ENVY 5924, EROS 15635, ETHAN MAO 5501, EVERYDAY PEOPLE 36165, FALLING DOWN 32706, FIRST LOVE 15080, FLIGHT OF THE PHOENIX 13263, FREEZE FRAME 3175, FRIDAY NIGHT LIGHTS 21640, GARDEN STATE 16914, GILLES' WIFE 17567, HARRY + MAX 9621, HAWAII, OSLO 23477, HAWKING 4840, HEAD IN THE CLOUDS 1044, HOTEL RWANDA 20303, HOUSE OF D 6753, IMAGINARY HEROES 38426, IRON JAWED ANGELS 21861, JERSEY GIRL 8849, KEANE 34731, KINSEY 926, LADDER 49 30600, LADIES IN LAVENDER 37237, LAND OF PLENTY 5251, LIGHTNING BUG 11689, LOOK AT ME 12292, MARIE AND BRUCE 20283, MEAN CREEK 831, MELINDA AND MELINDA 33998, MICKEY 28532, MILLION DOLLAR BABY 13143, MILLIONS 4168, MIRACLE 34674, MY SUMMER OF LOVE 26817, MYSTERIOUS SKIN 20433, NEW POLICE STORY 25709, NOBODY KNOWS 37353, NOEL 4132, OMAGH 11031, OUT OF REACH 13268, OYSTER FARMER 29275, P.S. 28047, PALINDROMES 12683, PRIMER 35167, PRIVATE 28125, RAINCOAT 5693, RAISING HELEN 33617, RED DUST 31114, SAINT RALPH 11313, SAVED! 2135, SAVING FACE 12902, SHE HATE ME 36797, SIDEWAYS 12464, SILVER CITY 32387, SIMON 7717, SPANGLISH 10978, STAGE BEAUTY 8374, STRIP SEARCH 4845, STU ZICHERMAN 24987, SUMMER STORM 6439, THE AVIATOR 16499, THE BEAUTIFUL COUNTRY 5686, THE BRIDGE OF SAN LUIS REY 33022, THE CHORUS 18130, THE CLEARING 21465, THE DOOR IN THE FLOOR 19685, THE FINAL CUT 15429, THE FORGOTTEN 14807, THE GOODBYE GIRL 38765, THE HOLY GIRL 8435, THE KEYS TO THE HOUSE 11711, THE LIBERTINE 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 36024, THE LIZARD 38433, THE MERCHANT OF VENICE 11555, THE NOTEBOOK 34751, THE PASSION OF THE CHRIST 7537, THE RETURNED 15768, THE TERMINAL 25426, THE WOODSMAN 16413, TROPICAL MALADY 29947, TURTLES CAN FLY 32733, VANITY FAIR 7577, VEER-ZAARA 22949, VERA DRAKE 37859, WE DON'T LIVE HERE ANYMORE 21897, WHEN WILL I BE LOVED 7055, WICKER PARK 18720, WILBY WONDERFUL 32096, WILD SIDE 7208, WINTER SOLSTICE 9901, YOU GOT SERVED src, edge_attr, dst 2043, has_genre, 36212 2043, release_year, 37484 5321, has_genre, 36212 5321, release_year, 37484 38203, has_genre, 36212 38203, release_year, 37484 20026, has_genre, 36212 20026, release_year, 37484 5441, has_genre, 36212 5441, release_year, 37484 11398, has_genre, 36212 11398, release_year, 37484 20576, has_genre, 36212 20576, release_year, 37484 30109, directed_by, 4845 30109, has_tags, 2283 30109, written_by, 4845 27020, has_genre, 36212 27020, release_year, 37484 1698, has_genre, 36212 1698, release_year, 37484 34789, has_genre, 36212 34789, has_tags, 36212 34789, release_year, 37484 18380, has_genre, 36212 18380, release_year, 37484 1815, has_genre, 36212 1815, release_year, 37484 2137, has_genre, 36212 2137, release_year, 37484 20294, has_genre, 36212 20294, release_year, 37484 2856, has_genre, 36212 2856, release_year, 37484 20489, has_genre, 36212 20489, release_year, 37484 30885, has_genre, 36212 30885, has_tags, 36212 30885, release_year, 37484 10272, has_tags, 36212 10272, release_year, 37484 32049, has_genre, 36212 32049, release_year, 37484 34180, has_genre, 36212 34180, release_year, 37484 15696, has_genre, 36212 15696, has_tags, 36212 15696, release_year, 37484 27982, has_genre, 36212 27982, release_year, 37484 16961, has_genre, 36212 16961, release_year, 37484 2283, has_genre, 36212 15779, has_genre, 36212 15779, release_year, 37484 1441, has_genre, 36212 1441, release_year, 37484 1329, has_genre, 36212 1329, release_year, 37484 5924, has_genre, 36212 5924, release_year, 37484 15635, has_genre, 36212 15635, release_year, 37484 5501, has_genre, 36212 5501, release_year, 37484 36165, has_genre, 36212 32706, has_genre, 36212 32706, release_year, 37484 15080, has_genre, 36212 15080, release_year, 37484 13263, has_genre, 36212 13263, release_year, 37484 3175, has_genre, 36212 3175, has_tags, 36212 3175, release_year, 37484 21640, has_genre, 36212 21640, release_year, 37484 16914, has_genre, 36212 16914, release_year, 37484 17567, has_genre, 36212 17567, release_year, 37484 9621, has_genre, 36212 9621, release_year, 37484 23477, has_genre, 36212 23477, release_year, 37484 4840, has_genre, 36212 4840, release_year, 37484 1044, has_genre, 36212 1044, has_tags, 36212 1044, release_year, 37484 20303, has_genre, 36212 20303, release_year, 37484 6753, has_genre, 36212 6753, release_year, 37484 38426, has_genre, 36212 38426, release_year, 37484 21861, has_genre, 36212 21861, has_tags, 36212 21861, release_year, 37484 8849, has_genre, 36212 8849, release_year, 37484 34731, has_genre, 36212 34731, release_year, 37484 926, has_genre, 36212 926, release_year, 37484 30600, has_genre, 36212 30600, release_year, 37484 37237, has_genre, 36212 37237, release_year, 37484 5251, has_genre, 36212 5251, release_year, 37484 11689, has_genre, 36212 11689, release_year, 37484 12292, has_genre, 36212 12292, release_year, 37484 20283, has_genre, 36212 20283, has_tags, 36212 20283, release_year, 37484 831, has_genre, 36212 831, release_year, 37484 33998, has_genre, 36212 33998, release_year, 37484 28532, has_genre, 36212 28532, has_tags, 36212 28532, release_year, 37484 13143, has_genre, 36212 13143, release_year, 37484 4168, has_genre, 36212 4168, release_year, 37484 34674, has_genre, 36212 34674, has_tags, 36212 34674, release_year, 37484 26817, has_genre, 36212 26817, release_year, 37484 20433, has_genre, 36212 20433, release_year, 37484 25709, has_genre, 36212 25709, release_year, 37484 37353, has_genre, 36212 37353, has_tags, 36212 37353, release_year, 37484 4132, has_genre, 36212 4132, release_year, 37484 11031, has_genre, 36212 11031, release_year, 37484 13268, has_genre, 36212 13268, release_year, 37484 29275, has_genre, 36212 29275, release_year, 37484 28047, has_genre, 36212 28047, release_year, 37484 12683, has_genre, 36212 12683, release_year, 37484 35167, has_genre, 36212 35167, release_year, 37484 28125, has_genre, 36212 28125, release_year, 37484 5693, has_genre, 36212 5693, release_year, 37484 33617, has_genre, 36212 33617, release_year, 37484 31114, has_genre, 36212 31114, release_year, 37484 11313, has_genre, 36212 11313, release_year, 37484 2135, has_genre, 36212 2135, release_year, 37484 12902, has_genre, 36212 12902, release_year, 37484 36797, has_genre, 36212 36797, release_year, 37484 12464, has_genre, 36212 12464, release_year, 37484 32387, has_genre, 36212 32387, release_year, 37484 7717, has_genre, 36212 7717, release_year, 37484 10978, has_genre, 36212 10978, release_year, 37484 8374, has_genre, 36212 8374, release_year, 37484 24987, has_genre, 36212 24987, release_year, 37484 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 37484 16499, has_genre, 36212 16499, has_tags, 36212 16499, release_year, 37484 5686, has_genre, 36212 5686, release_year, 37484 33022, has_genre, 36212 33022, has_tags, 36212 33022, release_year, 37484 18130, has_genre, 36212 18130, release_year, 37484 21465, has_genre, 36212 21465, has_tags, 36212 21465, release_year, 37484 19685, has_genre, 36212 19685, release_year, 37484 15429, has_genre, 36212 15429, release_year, 37484 14807, has_genre, 36212 14807, release_year, 37484 38765, has_genre, 36212 38765, release_year, 37484 8435, has_genre, 36212 8435, release_year, 37484 11711, has_genre, 36212 11711, release_year, 37484 28217, has_genre, 36212 28217, release_year, 37484 36024, has_genre, 36212 36024, release_year, 37484 38433, has_genre, 36212 38433, release_year, 37484 11555, has_genre, 36212 11555, release_year, 37484 34751, has_genre, 36212 34751, release_year, 37484 7537, has_genre, 36212 7537, release_year, 37484 15768, has_genre, 36212 15768, has_tags, 36212 15768, release_year, 37484 25426, has_genre, 36212 25426, has_tags, 36212 25426, release_year, 37484 16413, has_genre, 36212 16413, release_year, 37484 29947, has_genre, 36212 29947, release_year, 37484 32733, has_genre, 36212 32733, release_year, 37484 7577, has_genre, 36212 7577, release_year, 37484 22949, has_genre, 36212 22949, release_year, 37484 37859, has_genre, 36212 37859, release_year, 37484 21897, has_genre, 36212 21897, release_year, 37484 7055, has_genre, 36212 7055, release_year, 37484 18720, has_genre, 36212 18720, release_year, 37484 32096, has_genre, 36212 32096, release_year, 37484 7208, has_genre, 36212 7208, release_year, 37484 9901, release_year, 37484 Question: For what reason are FALLING DOWN, STU ZICHERMAN, and YOU GOT SERVED associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FALLING DOWN", "STU ZICHERMAN", "YOU GOT SERVED" ], "valid_edges": [ [ "9 SONGS", "has_genre", "DRAMA" ], [ "9 SONGS", "release_year", "2004" ], [ "A GOOD WOMAN", "has_genre", "DRAMA" ], [ "A GOOD WOMAN", "release_year", "2004" ], [ "A HOLE IN MY HEART", "has_genre", "DRAMA" ], [ "A HOLE IN MY HEART", "release_year", "2004" ], [ "A HOME AT THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "A HOME AT THE END OF THE WORLD", "release_year", "2004" ], [ "A LOVE SONG FOR BOBBY LONG", "has_genre", "DRAMA" ], [ "A LOVE SONG FOR BOBBY LONG", "release_year", "2004" ], [ "A MOMENT TO REMEMBER", "has_genre", "DRAMA" ], [ "A MOMENT TO REMEMBER", "release_year", "2004" ], [ "A WORLD WITHOUT THIEVES", "has_genre", "DRAMA" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "A.C.O.D.", "directed_by", "STU ZICHERMAN" ], [ "A.C.O.D.", "has_tags", "DIVORCE" ], [ "A.C.O.D.", "written_by", "STU ZICHERMAN" ], [ "AGAINST THE ROPES", "has_genre", "DRAMA" ], [ "AGAINST THE ROPES", "release_year", "2004" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "release_year", "2004" ], [ "BAD EDUCATION", "has_genre", "DRAMA" ], [ "BAD EDUCATION", "has_tags", "DRAMA" ], [ "BAD EDUCATION", "release_year", "2004" ], [ "BEFORE SUNSET", "has_genre", "DRAMA" ], [ "BEFORE SUNSET", "release_year", "2004" ], [ "BEFORE THE FALL", "has_genre", "DRAMA" ], [ "BEFORE THE FALL", "release_year", "2004" ], [ "BEING JULIA", "has_genre", "DRAMA" ], [ "BEING JULIA", "release_year", "2004" ], [ "BIRTH", "has_genre", "DRAMA" ], [ "BIRTH", "release_year", "2004" ], [ "BROTHERS", "has_genre", "DRAMA" ], [ "BROTHERS", "release_year", "2004" ], [ "CHANGING TIMES", "has_genre", "DRAMA" ], [ "CHANGING TIMES", "release_year", "2004" ], [ "CLOSER", "has_genre", "DRAMA" ], [ "CLOSER", "has_tags", "DRAMA" ], [ "CLOSER", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CRASH", "has_genre", "DRAMA" ], [ "CRASH", "release_year", "2004" ], [ "CRUEL INTENTIONS 3", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 3", "release_year", "2004" ], [ "DAY AND NIGHT", "has_genre", "DRAMA" ], [ "DAY AND NIGHT", "has_tags", "DRAMA" ], [ "DAY AND NIGHT", "release_year", "2004" ], [ "DEAR FRANKIE", "has_genre", "DRAMA" ], [ "DEAR FRANKIE", "release_year", "2004" ], [ "DIRTY FILTHY LOVE", "has_genre", "DRAMA" ], [ "DIRTY FILTHY LOVE", "release_year", "2004" ], [ "DIVORCE", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "release_year", "2004" ], [ "DOWN TO THE BONE", "has_genre", "DRAMA" ], [ "DOWN TO THE BONE", "release_year", "2004" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ENVY", "release_year", "2004" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "release_year", "2004" ], [ "ETHAN MAO", "has_genre", "DRAMA" ], [ "ETHAN MAO", "release_year", "2004" ], [ "EVERYDAY PEOPLE", "has_genre", "DRAMA" ], [ "EVERYDAY PEOPLE", "release_year", "2004" ], [ "FALLING DOWN", "has_genre", "DRAMA" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "release_year", "2004" ], [ "FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "FLIGHT OF THE PHOENIX", "release_year", "2004" ], [ "FREEZE FRAME", "has_genre", "DRAMA" ], [ "FREEZE FRAME", "release_year", "2004" ], [ "FRIDAY NIGHT LIGHTS", "has_genre", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "has_tags", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "release_year", "2004" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "release_year", "2004" ], [ "GILLES' WIFE", "has_genre", "DRAMA" ], [ "GILLES' WIFE", "release_year", "2004" ], [ "HARRY + MAX", "has_genre", "DRAMA" ], [ "HARRY + MAX", "release_year", "2004" ], [ "HAWAII, OSLO", "has_genre", "DRAMA" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWKING", "has_genre", "DRAMA" ], [ "HAWKING", "release_year", "2004" ], [ "HEAD IN THE CLOUDS", "has_genre", "DRAMA" ], [ "HEAD IN THE CLOUDS", "release_year", "2004" ], [ "HOTEL RWANDA", "has_genre", "DRAMA" ], [ "HOTEL RWANDA", "has_tags", "DRAMA" ], [ "HOTEL RWANDA", "release_year", "2004" ], [ "HOUSE OF D", "has_genre", "DRAMA" ], [ "HOUSE OF D", "release_year", "2004" ], [ "IMAGINARY HEROES", "has_genre", "DRAMA" ], [ "IMAGINARY HEROES", "release_year", "2004" ], [ "IRON JAWED ANGELS", "has_genre", "DRAMA" ], [ "IRON JAWED ANGELS", "release_year", "2004" ], [ "JERSEY GIRL", "has_genre", "DRAMA" ], [ "JERSEY GIRL", "has_tags", "DRAMA" ], [ "JERSEY GIRL", "release_year", "2004" ], [ "KEANE", "has_genre", "DRAMA" ], [ "KEANE", "release_year", "2004" ], [ "KINSEY", "has_genre", "DRAMA" ], [ "KINSEY", "release_year", "2004" ], [ "LADDER 49", "has_genre", "DRAMA" ], [ "LADDER 49", "release_year", "2004" ], [ "LADIES IN LAVENDER", "has_genre", "DRAMA" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "LAND OF PLENTY", "has_genre", "DRAMA" ], [ "LAND OF PLENTY", "release_year", "2004" ], [ "LIGHTNING BUG", "has_genre", "DRAMA" ], [ "LIGHTNING BUG", "release_year", "2004" ], [ "LOOK AT ME", "has_genre", "DRAMA" ], [ "LOOK AT ME", "release_year", "2004" ], [ "MARIE AND BRUCE", "has_genre", "DRAMA" ], [ "MARIE AND BRUCE", "release_year", "2004" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEAN CREEK", "release_year", "2004" ], [ "MELINDA AND MELINDA", "has_genre", "DRAMA" ], [ "MELINDA AND MELINDA", "release_year", "2004" ], [ "MICKEY", "has_genre", "DRAMA" ], [ "MICKEY", "release_year", "2004" ], [ "MILLION DOLLAR BABY", "has_genre", "DRAMA" ], [ "MILLION DOLLAR BABY", "has_tags", "DRAMA" ], [ "MILLION DOLLAR BABY", "release_year", "2004" ], [ "MILLIONS", "has_genre", "DRAMA" ], [ "MILLIONS", "release_year", "2004" ], [ "MIRACLE", "has_genre", "DRAMA" ], [ "MIRACLE", "release_year", "2004" ], [ "MY SUMMER OF LOVE", "has_genre", "DRAMA" ], [ "MY SUMMER OF LOVE", "has_tags", "DRAMA" ], [ "MY SUMMER OF LOVE", "release_year", "2004" ], [ "MYSTERIOUS SKIN", "has_genre", "DRAMA" ], [ "MYSTERIOUS SKIN", "release_year", "2004" ], [ "NEW POLICE STORY", "has_genre", "DRAMA" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NOBODY KNOWS", "has_genre", "DRAMA" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "release_year", "2004" ], [ "OMAGH", "has_genre", "DRAMA" ], [ "OMAGH", "release_year", "2004" ], [ "OUT OF REACH", "has_genre", "DRAMA" ], [ "OUT OF REACH", "release_year", "2004" ], [ "OYSTER FARMER", "has_genre", "DRAMA" ], [ "OYSTER FARMER", "release_year", "2004" ], [ "P.S.", "has_genre", "DRAMA" ], [ "P.S.", "release_year", "2004" ], [ "PALINDROMES", "has_genre", "DRAMA" ], [ "PALINDROMES", "release_year", "2004" ], [ "PRIMER", "has_genre", "DRAMA" ], [ "PRIMER", "release_year", "2004" ], [ "PRIVATE", "has_genre", "DRAMA" ], [ "PRIVATE", "release_year", "2004" ], [ "RAINCOAT", "has_genre", "DRAMA" ], [ "RAINCOAT", "release_year", "2004" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "RAISING HELEN", "release_year", "2004" ], [ "RED DUST", "has_genre", "DRAMA" ], [ "RED DUST", "release_year", "2004" ], [ "SAINT RALPH", "has_genre", "DRAMA" ], [ "SAINT RALPH", "release_year", "2004" ], [ "SAVED!", "has_genre", "DRAMA" ], [ "SAVED!", "release_year", "2004" ], [ "SAVING FACE", "has_genre", "DRAMA" ], [ "SAVING FACE", "release_year", "2004" ], [ "SHE HATE ME", "has_genre", "DRAMA" ], [ "SHE HATE ME", "release_year", "2004" ], [ "SIDEWAYS", "has_genre", "DRAMA" ], [ "SIDEWAYS", "release_year", "2004" ], [ "SILVER CITY", "has_genre", "DRAMA" ], [ "SILVER CITY", "release_year", "2004" ], [ "SIMON", "has_genre", "DRAMA" ], [ "SIMON", "release_year", "2004" ], [ "SPANGLISH", "has_genre", "DRAMA" ], [ "SPANGLISH", "release_year", "2004" ], [ "STAGE BEAUTY", "has_genre", "DRAMA" ], [ "STAGE BEAUTY", "release_year", "2004" ], [ "STRIP SEARCH", "has_genre", "DRAMA" ], [ "STRIP SEARCH", "release_year", "2004" ], [ "SUMMER STORM", "has_genre", "DRAMA" ], [ "SUMMER STORM", "release_year", "2004" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "2004" ], [ "THE BEAUTIFUL COUNTRY", "has_genre", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "has_tags", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "release_year", "2004" ], [ "THE BRIDGE OF SAN LUIS REY", "has_genre", "DRAMA" ], [ "THE BRIDGE OF SAN LUIS REY", "release_year", "2004" ], [ "THE CHORUS", "has_genre", "DRAMA" ], [ "THE CHORUS", "has_tags", "DRAMA" ], [ "THE CHORUS", "release_year", "2004" ], [ "THE CLEARING", "has_genre", "DRAMA" ], [ "THE CLEARING", "release_year", "2004" ], [ "THE DOOR IN THE FLOOR", "has_genre", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "has_tags", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "release_year", "2004" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE FORGOTTEN", "has_genre", "DRAMA" ], [ "THE FORGOTTEN", "release_year", "2004" ], [ "THE GOODBYE GIRL", "has_genre", "DRAMA" ], [ "THE GOODBYE GIRL", "release_year", "2004" ], [ "THE HOLY GIRL", "has_genre", "DRAMA" ], [ "THE HOLY GIRL", "release_year", "2004" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "release_year", "2004" ], [ "THE LIBERTINE", "has_genre", "DRAMA" ], [ "THE LIBERTINE", "release_year", "2004" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "release_year", "2004" ], [ "THE LIZARD", "has_genre", "DRAMA" ], [ "THE LIZARD", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE NOTEBOOK", "has_genre", "DRAMA" ], [ "THE NOTEBOOK", "release_year", "2004" ], [ "THE PASSION OF THE CHRIST", "has_genre", "DRAMA" ], [ "THE PASSION OF THE CHRIST", "release_year", "2004" ], [ "THE RETURNED", "has_genre", "DRAMA" ], [ "THE RETURNED", "release_year", "2004" ], [ "THE TERMINAL", "has_genre", "DRAMA" ], [ "THE TERMINAL", "has_tags", "DRAMA" ], [ "THE TERMINAL", "release_year", "2004" ], [ "THE WOODSMAN", "has_genre", "DRAMA" ], [ "THE WOODSMAN", "has_tags", "DRAMA" ], [ "THE WOODSMAN", "release_year", "2004" ], [ "TROPICAL MALADY", "has_genre", "DRAMA" ], [ "TROPICAL MALADY", "release_year", "2004" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "release_year", "2004" ], [ "VANITY FAIR", "has_genre", "DRAMA" ], [ "VANITY FAIR", "release_year", "2004" ], [ "VEER-ZAARA", "has_genre", "DRAMA" ], [ "VEER-ZAARA", "release_year", "2004" ], [ "VERA DRAKE", "has_genre", "DRAMA" ], [ "VERA DRAKE", "release_year", "2004" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHEN WILL I BE LOVED", "has_genre", "DRAMA" ], [ "WHEN WILL I BE LOVED", "release_year", "2004" ], [ "WICKER PARK", "has_genre", "DRAMA" ], [ "WICKER PARK", "release_year", "2004" ], [ "WILBY WONDERFUL", "has_genre", "DRAMA" ], [ "WILBY WONDERFUL", "release_year", "2004" ], [ "WILD SIDE", "has_genre", "DRAMA" ], [ "WILD SIDE", "release_year", "2004" ], [ "WINTER SOLSTICE", "has_genre", "DRAMA" ], [ "WINTER SOLSTICE", "release_year", "2004" ], [ "YOU GOT SERVED", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 24818, 1992 29424, 2011 17280, CHRISTMAS 26766, CHRISTOPHER CAIN 6029, EMILIO ESTEVEZ 32518, FREEJACK 31648, FRIGHT NIGHT 1153, MICHAEL CAINE 10743, ONE MAGIC CHRISTMAS 38711, PURE COUNTRY 19260, ST. ELMO'S FIRE 15048, THAT WAS THEN... THIS IS NOW 17931, THE BREAKFAST CLUB 29997, THE HOLCROFT COVENANT 24724, THE MIGHTY DUCKS 26128, THE MUPPET CHRISTMAS CAROL 22911, TO GRANDMOTHER'S HOUSE WE GO 5030, YOUNG GUNS 17195, ZOOKEEPER src, edge_attr, dst 32518, release_year, 24818 32518, starred_actors, 6029 31648, release_year, 38097 31648, release_year, 29424 10743, has_tags, 17280 10743, release_year, 38097 38711, directed_by, 26766 38711, release_year, 24818 19260, has_tags, 6029 19260, release_year, 38097 19260, starred_actors, 6029 15048, directed_by, 26766 15048, release_year, 38097 15048, starred_actors, 6029 15048, written_by, 6029 17931, has_tags, 6029 17931, release_year, 38097 17931, starred_actors, 6029 29997, release_year, 38097 29997, starred_actors, 1153 24724, has_tags, 6029 24724, release_year, 24818 24724, starred_actors, 6029 26128, has_tags, 17280 26128, has_tags, 1153 26128, release_year, 24818 26128, starred_actors, 1153 22911, has_tags, 17280 22911, release_year, 24818 5030, directed_by, 26766 5030, has_tags, 26766 5030, has_tags, 6029 5030, starred_actors, 6029 17195, release_year, 29424 Question: How are THAT WAS THEN... THIS IS NOW, THE MUPPET CHRISTMAS CAROL, and ZOOKEEPER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "THAT WAS THEN... THIS IS NOW", "THE MUPPET CHRISTMAS CAROL", "ZOOKEEPER" ], "valid_edges": [ [ "FREEJACK", "release_year", "1992" ], [ "FREEJACK", "starred_actors", "EMILIO ESTEVEZ" ], [ "FRIGHT NIGHT", "release_year", "1985" ], [ "FRIGHT NIGHT", "release_year", "2011" ], [ "ONE MAGIC CHRISTMAS", "has_tags", "CHRISTMAS" ], [ "ONE MAGIC CHRISTMAS", "release_year", "1985" ], [ "PURE COUNTRY", "directed_by", "CHRISTOPHER CAIN" ], [ "PURE COUNTRY", "release_year", "1992" ], [ "ST. ELMO'S FIRE", "has_tags", "EMILIO ESTEVEZ" ], [ "ST. ELMO'S FIRE", "release_year", "1985" ], [ "ST. ELMO'S FIRE", "starred_actors", "EMILIO ESTEVEZ" ], [ "THAT WAS THEN... THIS IS NOW", "directed_by", "CHRISTOPHER CAIN" ], [ "THAT WAS THEN... THIS IS NOW", "release_year", "1985" ], [ "THAT WAS THEN... THIS IS NOW", "starred_actors", "EMILIO ESTEVEZ" ], [ "THAT WAS THEN... THIS IS NOW", "written_by", "EMILIO ESTEVEZ" ], [ "THE BREAKFAST CLUB", "has_tags", "EMILIO ESTEVEZ" ], [ "THE BREAKFAST CLUB", "release_year", "1985" ], [ "THE BREAKFAST CLUB", "starred_actors", "EMILIO ESTEVEZ" ], [ "THE HOLCROFT COVENANT", "release_year", "1985" ], [ "THE HOLCROFT COVENANT", "starred_actors", "MICHAEL CAINE" ], [ "THE MIGHTY DUCKS", "has_tags", "EMILIO ESTEVEZ" ], [ "THE MIGHTY DUCKS", "release_year", "1992" ], [ "THE MIGHTY DUCKS", "starred_actors", "EMILIO ESTEVEZ" ], [ "THE MUPPET CHRISTMAS CAROL", "has_tags", "CHRISTMAS" ], [ "THE MUPPET CHRISTMAS CAROL", "has_tags", "MICHAEL CAINE" ], [ "THE MUPPET CHRISTMAS CAROL", "release_year", "1992" ], [ "THE MUPPET CHRISTMAS CAROL", "starred_actors", "MICHAEL CAINE" ], [ "TO GRANDMOTHER'S HOUSE WE GO", "has_tags", "CHRISTMAS" ], [ "TO GRANDMOTHER'S HOUSE WE GO", "release_year", "1992" ], [ "YOUNG GUNS", "directed_by", "CHRISTOPHER CAIN" ], [ "YOUNG GUNS", "has_tags", "CHRISTOPHER CAIN" ], [ "YOUNG GUNS", "has_tags", "EMILIO ESTEVEZ" ], [ "YOUNG GUNS", "starred_actors", "EMILIO ESTEVEZ" ], [ "ZOOKEEPER", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9854, BEST DEFENSE 13164, BROADWAY 12903, DISNEY 37267, DREAMGIRLS 31411, EDDIE MURPHY 12956, GENE KELLY 3716, HELLO, DOLLY! 14774, THAT DARN CAT! 7816, THE THREE MUSKETEERS src, edge_attr, dst 9854, has_tags, 31411 9854, starred_actors, 31411 37267, has_tags, 13164 37267, has_tags, 31411 37267, starred_actors, 31411 3716, directed_by, 12956 3716, has_tags, 13164 3716, has_tags, 12956 14774, has_tags, 12903 7816, has_tags, 12903 7816, starred_actors, 12956 Question: In what context are BEST DEFENSE, HELLO, DOLLY!, and THAT DARN CAT! connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BEST DEFENSE", "HELLO, DOLLY!", "THAT DARN CAT!" ], "valid_edges": [ [ "BEST DEFENSE", "has_tags", "EDDIE MURPHY" ], [ "BEST DEFENSE", "starred_actors", "EDDIE MURPHY" ], [ "DREAMGIRLS", "has_tags", "BROADWAY" ], [ "DREAMGIRLS", "has_tags", "EDDIE MURPHY" ], [ "DREAMGIRLS", "starred_actors", "EDDIE MURPHY" ], [ "HELLO, DOLLY!", "directed_by", "GENE KELLY" ], [ "HELLO, DOLLY!", "has_tags", "BROADWAY" ], [ "HELLO, DOLLY!", "has_tags", "GENE KELLY" ], [ "THAT DARN CAT!", "has_tags", "DISNEY" ], [ "THE THREE MUSKETEERS", "has_tags", "DISNEY" ], [ "THE THREE MUSKETEERS", "starred_actors", "GENE KELLY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7698, ANIMATED 2313, BEN-HUR 12903, DISNEY 5191, HAYA HARAREET 23900, LARRY MOREY 23695, MULAN 37497, NATIONAL FILM REGISTRY 25353, ROBERT D. SAN SOUCI 4717, SNOW WHITE AND THE SEVEN DWARFS src, edge_attr, dst 2313, has_tags, 37497 2313, starred_actors, 5191 23695, has_tags, 7698 23695, has_tags, 12903 23695, written_by, 25353 4717, directed_by, 23900 4717, has_tags, 7698 4717, has_tags, 12903 4717, has_tags, 37497 Question: For what reason are HAYA HARAREET, LARRY MOREY, and ROBERT D. SAN SOUCI associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HAYA HARAREET", "LARRY MOREY", "ROBERT D. SAN SOUCI" ], "valid_edges": [ [ "BEN-HUR", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BEN-HUR", "starred_actors", "HAYA HARAREET" ], [ "MULAN", "has_tags", "ANIMATED" ], [ "MULAN", "has_tags", "DISNEY" ], [ "MULAN", "written_by", "ROBERT D. SAN SOUCI" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "directed_by", "LARRY MOREY" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "ANIMATED" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "DISNEY" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "NATIONAL FILM REGISTRY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39646, ALL THE WAY HOME 35689, ANGEL FACE 36212, DRAMA 21425, ELMER GANTRY 38937, JANETTE OKE 25901, JEAN SIMMONS 35948, LOVE COMES SOFTLY 1691, LOVE'S LONG JOURNEY 20042, MICHAEL LANDON JR. 32548, MIGUEL GOMES 27315, MISTER BUDDWING 18335, TABU 22407, THE ACTRESS src, edge_attr, dst 39646, has_genre, 36212 39646, starred_actors, 25901 35689, has_genre, 36212 35689, starred_actors, 25901 21425, has_genre, 36212 21425, starred_actors, 25901 35948, directed_by, 20042 35948, has_genre, 36212 35948, written_by, 38937 35948, written_by, 20042 1691, directed_by, 20042 1691, has_genre, 36212 1691, written_by, 38937 1691, written_by, 20042 27315, has_genre, 36212 27315, starred_actors, 25901 18335, directed_by, 32548 18335, has_genre, 36212 18335, starred_actors, 32548 18335, written_by, 32548 22407, has_genre, 36212 22407, starred_actors, 25901 Question: For what reason are JEAN SIMMONS, MICHAEL LANDON JR., and MIGUEL GOMES associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JEAN SIMMONS", "MICHAEL LANDON JR.", "MIGUEL GOMES" ], "valid_edges": [ [ "ALL THE WAY HOME", "has_genre", "DRAMA" ], [ "ALL THE WAY HOME", "starred_actors", "JEAN SIMMONS" ], [ "ANGEL FACE", "has_genre", "DRAMA" ], [ "ANGEL FACE", "starred_actors", "JEAN SIMMONS" ], [ "ELMER GANTRY", "has_genre", "DRAMA" ], [ "ELMER GANTRY", "starred_actors", "JEAN SIMMONS" ], [ "LOVE COMES SOFTLY", "directed_by", "MICHAEL LANDON JR." ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "written_by", "JANETTE OKE" ], [ "LOVE COMES SOFTLY", "written_by", "MICHAEL LANDON JR." ], [ "LOVE'S LONG JOURNEY", "directed_by", "MICHAEL LANDON JR." ], [ "LOVE'S LONG JOURNEY", "has_genre", "DRAMA" ], [ "LOVE'S LONG JOURNEY", "written_by", "JANETTE OKE" ], [ "LOVE'S LONG JOURNEY", "written_by", "MICHAEL LANDON JR." ], [ "MISTER BUDDWING", "has_genre", "DRAMA" ], [ "MISTER BUDDWING", "starred_actors", "JEAN SIMMONS" ], [ "TABU", "directed_by", "MIGUEL GOMES" ], [ "TABU", "has_genre", "DRAMA" ], [ "TABU", "starred_actors", "MIGUEL GOMES" ], [ "TABU", "written_by", "MIGUEL GOMES" ], [ "THE ACTRESS", "has_genre", "DRAMA" ], [ "THE ACTRESS", "starred_actors", "JEAN SIMMONS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 19220, 21 29273, 7 FACES OF DR. LAO 6965, BLACKJACK 36066, FANTASY 34164, KATE BOSWORTH 26477, NICOLE GARCIA 11599, PLACE VENDÔME 37516, THE WARRIOR'S WAY src, edge_attr, dst 19220, has_tags, 6965 19220, has_tags, 34164 19220, starred_actors, 34164 29273, has_genre, 36066 6965, release_year, 2133 11599, directed_by, 26477 11599, release_year, 2133 11599, written_by, 26477 37516, has_genre, 36066 37516, starred_actors, 34164 Question: In what context are 21, 7 FACES OF DR. LAO, and NICOLE GARCIA connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "21", "7 FACES OF DR. LAO", "NICOLE GARCIA" ], "valid_edges": [ [ "21", "has_tags", "BLACKJACK" ], [ "21", "has_tags", "KATE BOSWORTH" ], [ "21", "starred_actors", "KATE BOSWORTH" ], [ "7 FACES OF DR. LAO", "has_genre", "FANTASY" ], [ "BLACKJACK", "release_year", "1998" ], [ "PLACE VENDÔME", "directed_by", "NICOLE GARCIA" ], [ "PLACE VENDÔME", "release_year", "1998" ], [ "PLACE VENDÔME", "written_by", "NICOLE GARCIA" ], [ "THE WARRIOR'S WAY", "has_genre", "FANTASY" ], [ "THE WARRIOR'S WAY", "starred_actors", "KATE BOSWORTH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 38097, 1985 37484, 2004 20576, A WORLD WITHOUT THIEVES 17521, ACES 'N' EIGHTS 39289, ACTION 35731, ACTION JACKSON 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 36077, AFTER EARTH 33087, AFTER THE SUNSET 16486, AGENT CODY BANKS 39750, ALIENS 38520, ALISON DOODY 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 34104, AMERICAN NINJA 38772, AN AMERICAN HIPPIE IN ISRAEL 35915, ANDREW MARTON 18598, APPLESEED 694, ASSAULT ON PRECINCT 13 10045, BD-R 19552, BEAU GESTE 19826, BLACK DEATH 39895, BLAST 38249, BORN TO FIGHT 22374, BREAKING NEWS 16749, BROKEN ARROW 16659, CASINO ROYALE 31692, CATWOMAN 6261, CELLULAR 30222, CHARLES WINKLER 524, CHARLIE'S ANGELS 5995, CLIFFHANGER 38098, CODE OF SILENCE 9636, COMMANDO 4283, CONAN THE BARBARIAN 16, CONGO 28192, COTTON COMES TO HARLEM 30802, CUTTHROAT ISLAND 22220, D.E.B.S. 8803, DEATH WISH 3 18348, DHOOM 26944, DICK TRACY 27800, DIRECT ACTION 12674, DON PAYNE 27950, ENTER THE DRAGON 5829, FIRE DOWN BELOW 6853, FIREWALKER 819, FIST OF THE NORTH STAR 10550, GALAXY QUEST 30810, GENE QUINTANO 23299, GET CARTER 28778, GOTCHA! 23775, HARD TICKET TO HAWAII 20504, HATARI! 34982, HELLBOY 25951, HIGHWAYMEN 5068, HOT SHOTS! PART DEUX 358, HOWARD THE DUCK 20625, I, ROBOT 22790, INDIANA JONES AND THE LAST CRUSADE 6083, INVASION U.S.A. 19805, J. LEE THOMPSON 20567, JOHN CARTER 38986, JUNGLE BOOK 14017, JURASSIC PARK 37798, JURASSIC PARK III 14156, KING SOLOMON'S MINES 9821, KUNG FU HUSTLE 31678, LE MANS 34533, LOGAN'S RUN 17855, MACGRUBER 31496, MAD MAX BEYOND THUNDERDOME 27174, MAIN HOON NA 22373, MAN ON FIRE 39027, MORTAL KOMBAT 32058, MUPPET TREASURE ISLAND 20433, NEW POLICE STORY 12081, NEXT OF KIN 9504, ON DEADLY GROUND 11031, OUT OF REACH 11796, PAPARAZZI 27541, PARODY 20348, PATHFINDER 26616, PATRICK SWAYZE 16004, PLANET TERROR 38688, POINT BREAK 3705, POLICE STORY 29299, RAIDERS OF THE LOST ARK 9555, RED HEAT 39610, RED SONJA 26663, RETROACTIVE 6512, RETROGRADE 607, RICHARD CHAMBERLAIN 11201, ROAD HOUSE 28221, ROMANCING THE STONE 23813, RUNAWAY TRAIN 35586, SAHARA 27807, SHAFT 38231, SHANGHAI NOON 23192, SHARON STONE 2473, SHOLAY 29005, SIN CITY 27140, SKY CAPTAIN AND THE WORLD OF TOMORROW 14350, SMOKEY AND THE BANDIT 34600, SPIDER-MAN 33904, SPY HARD 28357, ST. IVES 34989, STAR TREK 29830, STREETS OF BLOOD 2237, SUDDEN DEATH 17768, TARZAN AND THE LOST CITY 11699, TARZAN THE APE MAN 39736, TARZAN'S GREATEST ADVENTURE 10732, TAXI 13521, THE ADVENTURES OF FORD FAIRLANE 16103, THE AVENGERS 29403, THE BOURNE SUPREMACY 19351, THE COUNT OF MONTE CRISTO 30857, THE DEFENDER 18263, THE DUKES OF HAZZARD 2878, THE EVIL THAT MEN DO 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 19685, THE FINAL CUT 4068, THE GENERAL 9375, THE GREAT LOCOMOTIVE CHASE 15616, THE GUARDIAN 9166, THE GUNS OF NAVARONE 37902, THE HUNGER GAMES 19104, THE IN-LAWS 7447, THE INCREDIBLES 1443, THE ITALIAN JOB 18150, THE JEWEL OF THE NILE 5567, THE KEEPER 27237, THE LONGEST DAY 13295, THE MARK OF ZORRO 9580, THE PIRATES OF BLOOD RIVER 11498, THE POSEIDON ADVENTURE 19236, THE PROTECTOR 32051, THE PUNISHER 20287, THE SPECIALIST 26575, THOR 20377, THUNDERBIRDS 36584, TORQUE 13259, TOTAL RECALL 37876, TROMA'S WAR 5729, TROY 5560, UNSTOPPABLE 19088, VAN HELSING 25527, VICE 30520, WAKE OF DEATH 34133, WALKING TALL 23537, WHERE EAGLES DARE 36150, WILD GEESE II 5888, YEAR OF THE DRAGON src, edge_attr, dst 20576, has_genre, 39289 20576, release_year, 37484 17521, has_genre, 39289 17521, has_genre, 4763 35731, has_genre, 39289 35731, has_tags, 39289 35731, has_tags, 23192 35731, starred_actors, 23192 16054, has_genre, 39289 16054, has_genre, 4763 16054, has_tags, 4763 16054, has_tags, 10045 36077, has_genre, 39289 36077, has_genre, 4763 33087, has_genre, 39289 33087, release_year, 37484 16486, has_genre, 39289 16486, has_genre, 4763 16486, has_tags, 39289 39750, has_genre, 39289 39750, has_genre, 4763 39750, has_tags, 39289 22412, has_genre, 4763 22412, has_tags, 4763 22412, has_tags, 23192 22412, starred_actors, 607 22412, starred_actors, 23192 34104, has_genre, 39289 34104, has_tags, 39289 34104, release_year, 38097 38772, has_genre, 39289 38772, has_tags, 10045 18598, has_genre, 39289 18598, release_year, 37484 694, has_genre, 39289 694, has_tags, 39289 694, has_tags, 10045 19552, has_genre, 39289 19552, has_genre, 4763 19552, has_tags, 4763 19826, has_genre, 39289 19826, has_tags, 10045 39895, has_genre, 39289 39895, release_year, 37484 38249, has_genre, 39289 38249, release_year, 37484 22374, has_genre, 39289 22374, has_tags, 39289 22374, release_year, 37484 16749, has_genre, 39289 16749, has_tags, 39289 16749, release_year, 26423 16659, has_genre, 39289 16659, has_tags, 10045 31692, release_year, 37484 31692, starred_actors, 23192 6261, has_tags, 39289 6261, release_year, 37484 524, has_genre, 39289 524, has_genre, 4763 5995, has_genre, 39289 5995, has_genre, 4763 5995, has_tags, 39289 38098, has_genre, 39289 38098, release_year, 38097 9636, has_genre, 39289 9636, has_tags, 39289 9636, release_year, 38097 4283, has_genre, 39289 4283, has_genre, 4763 4283, has_tags, 39289 4283, has_tags, 4763 16, has_genre, 39289 16, has_genre, 4763 28192, has_genre, 39289 28192, has_tags, 10045 30802, has_genre, 39289 30802, has_genre, 4763 30802, has_tags, 39289 30802, has_tags, 4763 22220, has_genre, 39289 22220, has_tags, 27541 22220, release_year, 37484 8803, has_genre, 39289 8803, release_year, 38097 18348, has_genre, 39289 18348, release_year, 37484 26944, has_genre, 39289 26944, has_tags, 10045 27800, has_genre, 39289 27800, release_year, 37484 27950, has_genre, 39289 27950, has_tags, 10045 5829, has_genre, 39289 5829, has_genre, 4763 6853, directed_by, 19805 6853, has_genre, 39289 6853, has_genre, 4763 819, has_genre, 39289 819, has_tags, 10045 10550, has_genre, 4763 10550, has_tags, 27541 23299, has_genre, 39289 23299, has_tags, 10045 28778, has_genre, 39289 28778, release_year, 38097 23775, has_genre, 39289 23775, has_genre, 4763 20504, has_genre, 39289 20504, has_genre, 4763 34982, has_genre, 39289 34982, has_tags, 39289 34982, release_year, 37484 25951, has_genre, 39289 25951, release_year, 37484 5068, has_genre, 39289 5068, has_tags, 27541 358, has_genre, 39289 358, has_genre, 4763 358, has_tags, 39289 20625, has_genre, 39289 20625, has_tags, 39289 20625, release_year, 37484 22790, has_genre, 39289 22790, has_genre, 4763 22790, has_tags, 39289 22790, has_tags, 4763 22790, starred_actors, 38520 6083, has_genre, 39289 6083, release_year, 38097 20567, has_genre, 39289 20567, has_genre, 4763 20567, has_tags, 39289 20567, has_tags, 10045 38986, has_genre, 39289 38986, has_genre, 4763 38986, has_tags, 10045 14017, has_genre, 4763 14017, has_tags, 39289 14017, has_tags, 4763 37798, has_genre, 39289 37798, has_genre, 4763 37798, has_tags, 4763 14156, directed_by, 35915 14156, directed_by, 19805 14156, has_genre, 39289 14156, has_genre, 4763 14156, has_tags, 39289 14156, has_tags, 4763 14156, has_tags, 10045 14156, has_tags, 27541 14156, release_year, 26423 14156, release_year, 38097 14156, release_year, 37484 14156, starred_actors, 38520 14156, starred_actors, 26616 14156, starred_actors, 607 14156, starred_actors, 23192 14156, written_by, 30810 9821, has_genre, 39289 9821, has_tags, 39289 9821, 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has_tags, 39289 29299, has_tags, 4763 9555, has_genre, 39289 9555, has_tags, 39289 9555, release_year, 38097 39610, has_genre, 39289 39610, release_year, 38097 26663, has_genre, 39289 26663, has_genre, 4763 6512, has_genre, 39289 6512, release_year, 37484 11201, has_genre, 39289 11201, starred_actors, 26616 28221, has_genre, 39289 28221, has_genre, 4763 28221, has_tags, 39289 28221, has_tags, 4763 23813, has_genre, 39289 23813, release_year, 38097 35586, has_genre, 39289 35586, has_genre, 4763 35586, has_tags, 39289 35586, has_tags, 10045 27807, has_genre, 39289 27807, has_tags, 10045 38231, has_genre, 39289 38231, has_genre, 4763 2473, has_genre, 39289 2473, has_genre, 4763 29005, has_tags, 39289 29005, has_tags, 10045 27140, has_genre, 39289 27140, has_genre, 4763 27140, release_year, 37484 14350, has_genre, 39289 14350, has_tags, 10045 34600, has_genre, 39289 34600, has_genre, 4763 34600, has_tags, 39289 33904, has_genre, 39289 33904, has_tags, 27541 28357, directed_by, 19805 28357, has_genre, 39289 34989, has_genre, 39289 34989, has_genre, 4763 34989, has_tags, 39289 34989, has_tags, 4763 29830, directed_by, 30222 29830, has_genre, 39289 29830, starred_actors, 23192 2237, has_genre, 39289 2237, has_tags, 39289 2237, written_by, 30810 17768, has_genre, 39289 17768, has_genre, 4763 11699, has_genre, 39289 11699, has_genre, 4763 11699, has_tags, 10045 39736, has_genre, 39289 39736, has_genre, 4763 10732, has_genre, 39289 10732, release_year, 37484 13521, has_genre, 39289 13521, has_genre, 4763 16103, has_genre, 39289 16103, has_tags, 26575 29403, has_genre, 39289 29403, has_tags, 39289 29403, release_year, 37484 19351, has_genre, 39289 19351, has_genre, 4763 19351, has_tags, 4763 30857, has_genre, 39289 30857, release_year, 37484 18263, has_genre, 39289 18263, has_genre, 4763 2878, directed_by, 19805 2878, has_genre, 39289 10344, has_genre, 39289 10344, has_genre, 4763 19685, has_genre, 39289 19685, release_year, 37484 4068, has_genre, 39289 4068, has_genre, 4763 9375, has_genre, 39289 9375, has_genre, 4763 15616, has_genre, 39289 15616, has_genre, 4763 15616, has_tags, 39289 9166, directed_by, 19805 9166, has_genre, 39289 9166, has_genre, 4763 9166, has_tags, 39289 9166, has_tags, 10045 9166, has_tags, 19805 37902, has_genre, 4763 37902, has_tags, 39289 19104, has_genre, 39289 19104, has_tags, 10045 7447, has_tags, 10045 7447, release_year, 37484 1443, has_genre, 39289 1443, has_tags, 39289 1443, has_tags, 10045 18150, has_genre, 39289 18150, has_genre, 4763 18150, has_tags, 4763 18150, release_year, 38097 5567, has_genre, 39289 5567, release_year, 37484 27237, directed_by, 35915 27237, has_genre, 39289 27237, has_tags, 39289 13295, has_genre, 39289 13295, has_genre, 4763 13295, has_tags, 10045 9580, has_genre, 39289 9580, has_tags, 10045 11498, has_genre, 39289 11498, has_genre, 4763 19236, has_genre, 39289 19236, release_year, 38097 32051, has_genre, 39289 32051, has_tags, 39289 32051, release_year, 37484 20287, has_genre, 39289 20287, has_tags, 23192 20287, starred_actors, 23192 26575, written_by, 12674 20377, has_genre, 39289 20377, has_genre, 4763 20377, release_year, 37484 36584, has_genre, 39289 36584, release_year, 37484 13259, has_genre, 39289 13259, has_tags, 39289 13259, has_tags, 23192 13259, starred_actors, 23192 37876, has_genre, 39289 37876, has_genre, 4763 5729, has_genre, 4763 5729, has_tags, 39289 5729, release_year, 37484 5560, has_genre, 39289 5560, release_year, 37484 19088, has_genre, 39289 19088, release_year, 37484 25527, has_genre, 39289 25527, has_genre, 4763 30520, has_genre, 39289 30520, release_year, 37484 34133, has_genre, 39289 34133, release_year, 37484 23537, has_genre, 39289 23537, has_tags, 10045 36150, has_genre, 39289 36150, release_year, 38097 5888, has_genre, 39289 5888, has_tags, 39289 5888, release_year, 38097 Question: For what reason are CHARLES WINKLER, DON PAYNE, and KING SOLOMON'S MINES associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHARLES WINKLER", "DON PAYNE", "KING SOLOMON'S MINES" ], "valid_edges": [ [ "A WORLD WITHOUT THIEVES", "has_genre", "ACTION" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "ACES 'N' EIGHTS", "has_genre", "ACTION" ], [ "ACES 'N' EIGHTS", "has_genre", "ADVENTURE" ], [ "ACTION JACKSON", "has_genre", "ACTION" ], [ "ACTION JACKSON", "has_tags", "ACTION" ], [ "ACTION JACKSON", "has_tags", "SHARON STONE" ], [ "ACTION JACKSON", "starred_actors", "SHARON STONE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ACTION" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "BD-R" ], [ "AFTER EARTH", "has_genre", "ACTION" ], [ "AFTER EARTH", "has_genre", "ADVENTURE" ], [ "AFTER THE SUNSET", "has_genre", "ACTION" ], [ "AFTER THE SUNSET", "release_year", "2004" ], [ "AGENT CODY BANKS", "has_genre", "ACTION" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_tags", "ACTION" ], [ "ALIENS", "has_genre", "ACTION" ], [ "ALIENS", "has_genre", "ADVENTURE" ], [ "ALIENS", "has_tags", "ACTION" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "SHARON STONE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "starred_actors", "RICHARD CHAMBERLAIN" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "starred_actors", "SHARON STONE" ], [ "AMERICAN NINJA", "has_genre", "ACTION" ], [ "AMERICAN NINJA", "has_tags", "ACTION" ], [ "AMERICAN NINJA", "release_year", "1985" ], [ "AN AMERICAN HIPPIE IN ISRAEL", "has_genre", "ACTION" ], [ "AN AMERICAN HIPPIE IN ISRAEL", "has_tags", "BD-R" ], [ "APPLESEED", "has_genre", "ACTION" ], [ "APPLESEED", "release_year", "2004" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "BD-R" ], [ "BEAU GESTE", "has_genre", "ACTION" ], [ "BEAU GESTE", "has_genre", "ADVENTURE" ], [ "BEAU GESTE", "has_tags", "ADVENTURE" ], [ "BLACK DEATH", "has_genre", "ACTION" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLAST", "has_genre", "ACTION" ], [ "BLAST", "release_year", "2004" ], [ "BORN TO FIGHT", "has_genre", "ACTION" ], [ "BORN TO FIGHT", "release_year", "2004" ], [ "BREAKING NEWS", "has_genre", "ACTION" ], [ "BREAKING NEWS", "has_tags", "ACTION" ], [ "BREAKING NEWS", "release_year", "2004" ], [ "BROKEN ARROW", "has_genre", "ACTION" ], [ "BROKEN ARROW", "has_tags", "ACTION" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "CASINO ROYALE", "has_genre", "ACTION" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CATWOMAN", "release_year", "2004" ], [ "CATWOMAN", "starred_actors", "SHARON STONE" ], [ "CELLULAR", "has_tags", "ACTION" ], [ "CELLULAR", "release_year", "2004" ], [ "CHARLIE'S ANGELS", "has_genre", "ACTION" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CLIFFHANGER", "has_genre", "ACTION" ], [ "CLIFFHANGER", "has_genre", "ADVENTURE" ], [ "CLIFFHANGER", "has_tags", "ACTION" ], [ "CODE OF SILENCE", "has_genre", "ACTION" ], [ "CODE OF SILENCE", "release_year", "1985" ], [ "COMMANDO", "has_genre", "ACTION" ], [ "COMMANDO", "has_tags", "ACTION" ], [ "COMMANDO", "release_year", "1985" ], [ "CONAN THE BARBARIAN", "has_genre", "ACTION" ], [ "CONAN THE BARBARIAN", "has_genre", "ADVENTURE" ], [ "CONAN THE BARBARIAN", "has_tags", "ACTION" ], [ "CONAN THE BARBARIAN", "has_tags", "ADVENTURE" ], [ "CONGO", "has_genre", "ACTION" ], [ "CONGO", "has_genre", "ADVENTURE" ], [ "COTTON COMES TO HARLEM", "has_genre", "ACTION" ], [ "COTTON COMES TO HARLEM", "has_tags", "BD-R" ], [ "CUTTHROAT ISLAND", "has_genre", "ACTION" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_tags", "ACTION" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "D.E.B.S.", "has_genre", "ACTION" ], [ "D.E.B.S.", "has_tags", "PARODY" ], [ "D.E.B.S.", "release_year", "2004" ], [ "DEATH WISH 3", "has_genre", "ACTION" ], [ "DEATH WISH 3", "release_year", "1985" ], [ "DHOOM", "has_genre", "ACTION" ], [ "DHOOM", "release_year", "2004" ], [ "DICK TRACY", "has_genre", "ACTION" ], [ "DICK TRACY", "has_tags", "BD-R" ], [ "DIRECT ACTION", "has_genre", "ACTION" ], [ "DIRECT ACTION", "release_year", "2004" ], [ "ENTER THE DRAGON", "has_genre", "ACTION" ], [ "ENTER THE DRAGON", "has_tags", "BD-R" ], [ "FIRE DOWN BELOW", "has_genre", "ACTION" ], [ "FIRE DOWN BELOW", "has_genre", "ADVENTURE" ], [ "FIREWALKER", "directed_by", "J. LEE THOMPSON" ], [ "FIREWALKER", "has_genre", "ACTION" ], [ "FIREWALKER", "has_genre", "ADVENTURE" ], [ "FIST OF THE NORTH STAR", "has_genre", "ACTION" ], [ "FIST OF THE NORTH STAR", "has_tags", "BD-R" ], [ "GALAXY QUEST", "has_genre", "ADVENTURE" ], [ "GALAXY QUEST", "has_tags", "PARODY" ], [ "GET CARTER", "has_genre", "ACTION" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GOTCHA!", "has_genre", "ACTION" ], [ "GOTCHA!", "release_year", "1985" ], [ "HARD TICKET TO HAWAII", "has_genre", "ACTION" ], [ "HARD TICKET TO HAWAII", "has_genre", "ADVENTURE" ], [ "HATARI!", "has_genre", "ACTION" ], [ "HATARI!", "has_genre", "ADVENTURE" ], [ "HELLBOY", "has_genre", "ACTION" ], [ "HELLBOY", "has_tags", "ACTION" ], [ "HELLBOY", "release_year", "2004" ], [ "HIGHWAYMEN", "has_genre", "ACTION" ], [ "HIGHWAYMEN", "release_year", "2004" ], [ "HOT SHOTS! PART DEUX", "has_genre", "ACTION" ], [ "HOT SHOTS! PART DEUX", "has_tags", "PARODY" ], [ "HOWARD THE DUCK", "has_genre", "ACTION" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_tags", "ACTION" ], [ "I, ROBOT", "has_genre", "ACTION" ], [ "I, ROBOT", "has_tags", "ACTION" ], [ "I, ROBOT", "release_year", "2004" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "ALISON DOODY" ], [ "INVASION U.S.A.", "has_genre", "ACTION" ], [ "INVASION U.S.A.", "release_year", "1985" ], [ "JOHN CARTER", "has_genre", "ACTION" ], [ "JOHN CARTER", "has_genre", "ADVENTURE" ], [ "JOHN CARTER", "has_tags", "ACTION" ], [ "JOHN CARTER", "has_tags", "BD-R" ], [ "JUNGLE BOOK", "has_genre", "ACTION" ], [ "JUNGLE BOOK", "has_genre", "ADVENTURE" ], [ "JUNGLE BOOK", "has_tags", "BD-R" ], [ "JURASSIC PARK", "has_genre", "ADVENTURE" ], [ "JURASSIC PARK", "has_tags", "ACTION" ], [ "JURASSIC PARK", "has_tags", "ADVENTURE" ], [ "JURASSIC PARK III", "has_genre", "ACTION" ], [ "JURASSIC PARK III", "has_genre", "ADVENTURE" ], [ "JURASSIC PARK III", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "directed_by", "ANDREW MARTON" ], [ "KING SOLOMON'S MINES", "directed_by", "J. LEE THOMPSON" ], [ "KING SOLOMON'S MINES", "has_genre", "ACTION" ], [ "KING SOLOMON'S MINES", "has_genre", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "ACTION" ], [ "KING SOLOMON'S MINES", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KING SOLOMON'S MINES", "has_tags", "PARODY" ], [ "KING SOLOMON'S MINES", "release_year", "1950" ], [ "KING SOLOMON'S MINES", "release_year", "1985" ], [ "KING SOLOMON'S MINES", "release_year", "2004" ], [ "KING SOLOMON'S MINES", "starred_actors", "ALISON DOODY" ], [ "KING SOLOMON'S MINES", "starred_actors", "PATRICK SWAYZE" ], [ "KING SOLOMON'S MINES", "starred_actors", "RICHARD CHAMBERLAIN" ], [ "KING SOLOMON'S MINES", "starred_actors", "SHARON STONE" ], [ "KING SOLOMON'S MINES", "written_by", "GENE QUINTANO" ], [ "KUNG FU HUSTLE", "has_genre", "ACTION" ], [ "KUNG FU HUSTLE", "has_tags", "ACTION" ], [ "KUNG FU HUSTLE", "release_year", "2004" ], [ "LE MANS", "has_genre", "ACTION" ], [ "LE MANS", "has_tags", "BD-R" ], [ "LOGAN'S RUN", "has_genre", "ACTION" ], [ "LOGAN'S RUN", "has_tags", "BD-R" ], [ "MACGRUBER", "has_genre", "ACTION" ], [ "MACGRUBER", "has_tags", "PARODY" ], [ "MAD MAX BEYOND THUNDERDOME", "has_genre", "ACTION" ], [ "MAD MAX BEYOND THUNDERDOME", "has_tags", "ACTION" ], [ "MAD MAX BEYOND THUNDERDOME", "release_year", "1985" ], [ "MAIN HOON NA", "has_genre", "ACTION" ], [ "MAIN HOON NA", "release_year", "2004" ], [ "MAN ON FIRE", "has_genre", "ACTION" ], [ "MAN ON FIRE", "has_tags", "ACTION" ], [ "MAN ON FIRE", "release_year", "2004" ], [ "MORTAL KOMBAT", "has_genre", "ACTION" ], [ "MORTAL KOMBAT", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ACTION" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "NEW POLICE STORY", "has_genre", "ACTION" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NEXT OF KIN", "has_genre", "ACTION" ], [ "NEXT OF KIN", "starred_actors", "PATRICK SWAYZE" ], [ "ON DEADLY GROUND", "has_genre", "ACTION" ], [ "ON DEADLY GROUND", "has_genre", "ADVENTURE" ], [ "OUT OF REACH", "has_genre", "ACTION" ], [ "OUT OF REACH", "release_year", "2004" ], [ "PAPARAZZI", "has_genre", "ACTION" ], [ "PAPARAZZI", "release_year", "2004" ], [ "PATHFINDER", "has_genre", "ACTION" ], [ "PATHFINDER", "has_genre", "ADVENTURE" ], [ "PLANET TERROR", "has_genre", "ACTION" ], [ "PLANET TERROR", "has_tags", "BD-R" ], [ "POINT BREAK", "has_genre", "ACTION" ], [ "POINT BREAK", "has_tags", "PATRICK SWAYZE" ], [ "POINT BREAK", "starred_actors", "PATRICK SWAYZE" ], [ "POLICE STORY", "has_genre", "ACTION" ], [ "POLICE STORY", "has_tags", "ACTION" ], [ "POLICE STORY", "release_year", "1985" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ADVENTURE" ], [ "RED HEAT", "has_genre", "ACTION" ], [ "RED HEAT", "has_tags", "ACTION" ], [ "RED HEAT", "release_year", "1985" ], [ "RED SONJA", "has_genre", "ACTION" ], [ "RED SONJA", "release_year", "1985" ], [ "RETROACTIVE", "has_genre", "ACTION" ], [ "RETROACTIVE", "has_genre", "ADVENTURE" ], [ "RETROGRADE", "has_genre", "ACTION" ], [ "RETROGRADE", "release_year", "2004" ], [ "ROAD HOUSE", "has_genre", "ACTION" ], [ "ROAD HOUSE", "starred_actors", "PATRICK SWAYZE" ], [ "ROMANCING THE STONE", "has_genre", "ACTION" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_tags", "ACTION" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "RUNAWAY TRAIN", "has_genre", "ACTION" ], [ "RUNAWAY TRAIN", "release_year", "1985" ], [ "SAHARA", "has_genre", "ACTION" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_tags", "ACTION" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SHAFT", "has_genre", "ACTION" ], [ "SHAFT", "has_tags", "BD-R" ], [ "SHANGHAI NOON", "has_genre", "ACTION" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHOLAY", "has_genre", "ACTION" ], [ "SHOLAY", "has_genre", "ADVENTURE" ], [ "SIN CITY", "has_tags", "ACTION" ], [ "SIN CITY", "has_tags", "BD-R" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "has_genre", "ACTION" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "has_genre", "ADVENTURE" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "release_year", "2004" ], [ "SMOKEY AND THE BANDIT", "has_genre", "ACTION" ], [ "SMOKEY AND THE BANDIT", "has_tags", "BD-R" ], [ "SPIDER-MAN", "has_genre", "ACTION" ], [ "SPIDER-MAN", "has_genre", "ADVENTURE" ], [ "SPIDER-MAN", "has_tags", "ACTION" ], [ "SPY HARD", "has_genre", "ACTION" ], [ "SPY HARD", "has_tags", "PARODY" ], [ "ST. IVES", "directed_by", "J. LEE THOMPSON" ], [ "ST. IVES", "has_genre", "ACTION" ], [ "STAR TREK", "has_genre", "ACTION" ], [ "STAR TREK", "has_genre", "ADVENTURE" ], [ "STAR TREK", "has_tags", "ACTION" ], [ "STAR TREK", "has_tags", "ADVENTURE" ], [ "STREETS OF BLOOD", "directed_by", "CHARLES WINKLER" ], [ "STREETS OF BLOOD", "has_genre", "ACTION" ], [ "STREETS OF BLOOD", "starred_actors", "SHARON STONE" ], [ "SUDDEN DEATH", "has_genre", "ACTION" ], [ "SUDDEN DEATH", "has_tags", "ACTION" ], [ "SUDDEN DEATH", "written_by", "GENE QUINTANO" ], [ "TARZAN AND THE LOST CITY", "has_genre", "ACTION" ], [ "TARZAN AND THE LOST CITY", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_genre", "ACTION" ], [ "TARZAN THE APE MAN", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_tags", "BD-R" ], [ "TARZAN'S GREATEST ADVENTURE", "has_genre", "ACTION" ], [ "TARZAN'S GREATEST ADVENTURE", "has_genre", "ADVENTURE" ], [ "TAXI", "has_genre", "ACTION" ], [ "TAXI", "release_year", "2004" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ACTION" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE AVENGERS", "has_genre", "ACTION" ], [ "THE AVENGERS", "has_tags", "THOR" ], [ "THE BOURNE SUPREMACY", "has_genre", "ACTION" ], [ "THE BOURNE SUPREMACY", "has_tags", "ACTION" ], [ "THE BOURNE SUPREMACY", "release_year", "2004" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ACTION" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ADVENTURE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "ADVENTURE" ], [ "THE DEFENDER", "has_genre", "ACTION" ], [ "THE DEFENDER", "release_year", "2004" ], [ "THE DUKES OF HAZZARD", "has_genre", "ACTION" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE EVIL THAT MEN DO", "directed_by", "J. LEE THOMPSON" ], [ "THE EVIL THAT MEN DO", "has_genre", "ACTION" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "ACTION" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "ADVENTURE" ], [ "THE FINAL CUT", "has_genre", "ACTION" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE GENERAL", "has_genre", "ACTION" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GREAT LOCOMOTIVE CHASE", "has_genre", "ACTION" ], [ "THE GREAT LOCOMOTIVE CHASE", "has_genre", "ADVENTURE" ], [ "THE GUARDIAN", "has_genre", "ACTION" ], [ "THE GUARDIAN", "has_genre", "ADVENTURE" ], [ "THE GUARDIAN", "has_tags", "ACTION" ], [ "THE GUNS OF NAVARONE", "directed_by", "J. LEE THOMPSON" ], [ "THE GUNS OF NAVARONE", "has_genre", "ACTION" ], [ "THE GUNS OF NAVARONE", "has_genre", "ADVENTURE" ], [ "THE GUNS OF NAVARONE", "has_tags", "ACTION" ], [ "THE GUNS OF NAVARONE", "has_tags", "BD-R" ], [ "THE GUNS OF NAVARONE", "has_tags", "J. LEE THOMPSON" ], [ "THE HUNGER GAMES", "has_genre", "ADVENTURE" ], [ "THE HUNGER GAMES", "has_tags", "ACTION" ], [ "THE IN-LAWS", "has_genre", "ACTION" ], [ "THE IN-LAWS", "has_tags", "BD-R" ], [ "THE INCREDIBLES", "has_tags", "BD-R" ], [ "THE INCREDIBLES", "release_year", "2004" ], [ "THE ITALIAN JOB", "has_genre", "ACTION" ], [ "THE ITALIAN JOB", "has_tags", "ACTION" ], [ "THE ITALIAN JOB", "has_tags", "BD-R" ], [ "THE JEWEL OF THE NILE", "has_genre", "ACTION" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "release_year", "1985" ], [ "THE KEEPER", "has_genre", "ACTION" ], [ "THE KEEPER", "release_year", "2004" ], [ "THE LONGEST DAY", "directed_by", "ANDREW MARTON" ], [ "THE LONGEST DAY", "has_genre", "ACTION" ], [ "THE LONGEST DAY", "has_tags", "ACTION" ], [ "THE MARK OF ZORRO", "has_genre", "ACTION" ], [ "THE MARK OF ZORRO", "has_genre", "ADVENTURE" ], [ "THE MARK OF ZORRO", "has_tags", "BD-R" ], [ "THE PIRATES OF BLOOD RIVER", "has_genre", "ACTION" ], [ "THE PIRATES OF BLOOD RIVER", "has_tags", "BD-R" ], [ "THE POSEIDON ADVENTURE", "has_genre", "ACTION" ], [ "THE POSEIDON ADVENTURE", "has_genre", "ADVENTURE" ], [ "THE PROTECTOR", "has_genre", "ACTION" ], [ "THE PROTECTOR", "release_year", "1985" ], [ "THE PUNISHER", "has_genre", "ACTION" ], [ "THE PUNISHER", "has_tags", "ACTION" ], [ "THE PUNISHER", "release_year", "2004" ], [ "THE SPECIALIST", "has_genre", "ACTION" ], [ "THE SPECIALIST", "has_tags", "SHARON STONE" ], [ "THE SPECIALIST", "starred_actors", "SHARON STONE" ], [ "THOR", "written_by", "DON PAYNE" ], [ "THUNDERBIRDS", "has_genre", "ACTION" ], [ "THUNDERBIRDS", "has_genre", "ADVENTURE" ], [ "THUNDERBIRDS", "release_year", "2004" ], [ "TORQUE", "has_genre", "ACTION" ], [ "TORQUE", "release_year", "2004" ], [ "TOTAL RECALL", "has_genre", "ACTION" ], [ "TOTAL RECALL", "has_tags", "ACTION" ], [ "TOTAL RECALL", "has_tags", "SHARON STONE" ], [ "TOTAL RECALL", "starred_actors", "SHARON STONE" ], [ "TROMA'S WAR", "has_genre", "ACTION" ], [ "TROMA'S WAR", "has_genre", "ADVENTURE" ], [ "TROY", "has_genre", "ADVENTURE" ], [ "TROY", "has_tags", "ACTION" ], [ "TROY", "release_year", "2004" ], [ "UNSTOPPABLE", "has_genre", "ACTION" ], [ "UNSTOPPABLE", "release_year", "2004" ], [ "VAN HELSING", "has_genre", "ACTION" ], [ "VAN HELSING", "release_year", "2004" ], [ "VICE", "has_genre", "ACTION" ], [ "VICE", "has_genre", "ADVENTURE" ], [ "WAKE OF DEATH", "has_genre", "ACTION" ], [ "WAKE OF DEATH", "release_year", "2004" ], [ "WALKING TALL", "has_genre", "ACTION" ], [ "WALKING TALL", "release_year", "2004" ], [ "WHERE EAGLES DARE", "has_genre", "ACTION" ], [ "WHERE EAGLES DARE", "has_tags", "BD-R" ], [ "WILD GEESE II", "has_genre", "ACTION" ], [ "WILD GEESE II", "release_year", "1985" ], [ "YEAR OF THE DRAGON", "has_genre", "ACTION" ], [ "YEAR OF THE DRAGON", "has_tags", "ACTION" ], [ "YEAR OF THE DRAGON", "release_year", "1985" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 20033, ANGEL 28344, ANGUS 39876, ANNIE 18131, BABE 12144, BAD BOYS 18725, BAREFOOT 20940, BEACHES 29743, BEST FRIENDS 9097, BLADE RUNNER 350, BOYS ON THE SIDE 30463, COMEDY 2171, COUSINS 39230, DAD 39164, DINER 20842, DR. JEKYLL AND MS. HYDE 36212, DRAMA 10941, DRIVING MISS DAISY 24672, EVERSMILE, NEW JERSEY 11065, FATAL INSTINCT 34555, FLAWLESS 6223, FUNNY BONES 2155, GEORGIA RULE 29107, HARLEM NIGHTS 33887, HOME FOR THE HOLIDAYS 2055, LIVING IN OBLIVION 27801, MAN OF THE YEAR 16428, MUMFORD 2654, NOTHING IN COMMON 25824, PARADISE 5023, PARENTHOOD 29620, POLICE 13081, R 5693, RAISING HELEN 27430, ROOMMATES 4689, SABRINA 22312, SAY ANYTHING... 34917, SEAN YOUNG 30536, SHIRLEY VALENTINE 9274, SIX PACK 13768, SLEEPY HOLLOW 20971, SOMETHING TO TALK ABOUT 20689, STARSTRUCK 25135, STAYING TOGETHER 29867, STEEL MAGNOLIAS 18733, STONEWALL 2819, TEMPEST 2633, THE AMERICAN PRESIDENT 4789, THE BROTHERS MCMULLEN 24493, THE FUNERAL 39138, THE GRASS HARP 20291, THE WIZARD 38787, THE WORLD ACCORDING TO GARP 37331, TO DIE FOR 1459, TOO BEAUTIFUL FOR YOU 30585, TWISTER 9183, UNSTRUNG HEROES 17257, WASHINGTON IRVING 18629, YOUNG DOCTORS IN LOVE src, edge_attr, dst 20033, has_genre, 30463 20033, has_genre, 36212 28344, has_genre, 30463 28344, has_genre, 36212 39876, has_genre, 30463 39876, has_genre, 36212 18131, has_genre, 30463 18131, has_genre, 36212 12144, has_genre, 30463 12144, has_genre, 36212 12144, has_tags, 30463 18725, has_genre, 30463 18725, has_genre, 36212 20940, has_genre, 30463 20940, has_genre, 36212 29743, has_genre, 30463 29743, has_genre, 36212 9097, has_tags, 29620 9097, has_tags, 13081 9097, has_tags, 34917 9097, release_year, 8539 9097, starred_actors, 34917 350, has_genre, 30463 350, has_genre, 36212 2171, has_genre, 30463 2171, starred_actors, 34917 39230, has_genre, 30463 39230, has_genre, 36212 39164, has_genre, 30463 39164, has_genre, 36212 20842, has_genre, 30463 20842, starred_actors, 34917 10941, has_genre, 30463 10941, has_genre, 36212 10941, has_tags, 36212 24672, has_genre, 30463 24672, has_genre, 36212 11065, has_genre, 30463 11065, starred_actors, 34917 34555, has_genre, 30463 34555, has_genre, 36212 6223, has_genre, 30463 6223, has_genre, 36212 2155, has_genre, 30463 2155, has_genre, 36212 29107, has_genre, 30463 29107, has_genre, 36212 33887, has_genre, 30463 33887, has_genre, 36212 2055, has_genre, 30463 2055, has_genre, 36212 27801, has_genre, 30463 27801, has_genre, 36212 27801, has_tags, 30463 16428, has_genre, 30463 16428, has_genre, 36212 2654, has_genre, 30463 2654, has_genre, 36212 25824, has_genre, 30463 25824, has_genre, 36212 5023, has_genre, 30463 5023, has_genre, 36212 5023, has_tags, 30463 29620, has_genre, 36212 5693, has_genre, 30463 5693, has_genre, 36212 27430, has_genre, 30463 27430, has_genre, 36212 4689, has_genre, 30463 4689, has_genre, 36212 4689, has_tags, 36212 22312, has_genre, 30463 22312, has_genre, 36212 30536, has_genre, 30463 30536, has_genre, 36212 9274, has_genre, 30463 9274, has_genre, 36212 13768, has_tags, 13081 13768, written_by, 17257 20971, has_genre, 30463 20971, has_genre, 36212 20689, has_genre, 30463 20689, has_genre, 36212 25135, has_genre, 30463 25135, has_genre, 36212 29867, has_genre, 30463 29867, has_genre, 36212 18733, has_genre, 30463 18733, has_genre, 36212 2819, has_genre, 30463 2819, has_genre, 36212 2633, has_genre, 30463 2633, has_genre, 36212 2633, has_tags, 36212 4789, has_genre, 30463 4789, has_genre, 36212 24493, has_genre, 30463 24493, has_genre, 36212 39138, has_genre, 30463 39138, has_genre, 36212 20291, has_genre, 30463 20291, has_genre, 36212 38787, has_genre, 30463 38787, has_genre, 36212 37331, has_genre, 30463 37331, has_genre, 36212 1459, has_genre, 30463 1459, has_genre, 36212 30585, has_genre, 30463 30585, has_genre, 36212 9183, has_genre, 30463 9183, has_genre, 36212 18629, has_genre, 30463 18629, release_year, 8539 18629, starred_actors, 34917 Question: For what reason are BAREFOOT, SEAN YOUNG, and WASHINGTON IRVING associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BAREFOOT", "SEAN YOUNG", "WASHINGTON IRVING" ], "valid_edges": [ [ "ANGEL", "has_genre", "COMEDY" ], [ "ANGEL", "has_genre", "DRAMA" ], [ "ANGUS", "has_genre", "COMEDY" ], [ "ANGUS", "has_genre", "DRAMA" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "BABE", "has_genre", "COMEDY" ], [ "BABE", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_genre", "COMEDY" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_tags", "COMEDY" ], [ "BAREFOOT", "has_genre", "COMEDY" ], [ "BAREFOOT", "has_genre", "DRAMA" ], [ "BEACHES", "has_genre", "COMEDY" ], [ "BEACHES", "has_genre", "DRAMA" ], [ "BEST FRIENDS", "has_genre", "COMEDY" ], [ "BEST FRIENDS", "has_genre", "DRAMA" ], [ "BLADE RUNNER", "has_tags", "POLICE" ], [ "BLADE RUNNER", "has_tags", "R" ], [ "BLADE RUNNER", "has_tags", "SEAN YOUNG" ], [ "BLADE RUNNER", "release_year", "1982" ], [ "BLADE RUNNER", "starred_actors", "SEAN YOUNG" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_genre", "DRAMA" ], [ "COUSINS", "has_genre", "COMEDY" ], [ "COUSINS", "starred_actors", "SEAN YOUNG" ], [ "DAD", "has_genre", "COMEDY" ], [ "DAD", "has_genre", "DRAMA" ], [ "DINER", "has_genre", "COMEDY" ], [ "DINER", "has_genre", "DRAMA" ], [ "DR. JEKYLL AND MS. HYDE", "has_genre", "COMEDY" ], [ "DR. JEKYLL AND MS. HYDE", "starred_actors", "SEAN YOUNG" ], [ "DRIVING MISS DAISY", "has_genre", "COMEDY" ], [ "DRIVING MISS DAISY", "has_genre", "DRAMA" ], [ "DRIVING MISS DAISY", "has_tags", "DRAMA" ], [ "EVERSMILE, NEW JERSEY", "has_genre", "COMEDY" ], [ "EVERSMILE, NEW JERSEY", "has_genre", "DRAMA" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "starred_actors", "SEAN YOUNG" ], [ "FLAWLESS", "has_genre", "COMEDY" ], [ "FLAWLESS", "has_genre", "DRAMA" ], [ "FUNNY BONES", "has_genre", "COMEDY" ], [ "FUNNY BONES", "has_genre", "DRAMA" ], [ "GEORGIA RULE", "has_genre", "COMEDY" ], [ "GEORGIA RULE", "has_genre", "DRAMA" ], [ "HARLEM NIGHTS", "has_genre", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "DRAMA" ], [ "HOME FOR THE HOLIDAYS", "has_genre", "COMEDY" ], [ "HOME FOR THE HOLIDAYS", "has_genre", "DRAMA" ], [ "LIVING IN OBLIVION", "has_genre", "COMEDY" ], [ "LIVING IN OBLIVION", "has_genre", "DRAMA" ], [ "MAN OF THE YEAR", "has_genre", "COMEDY" ], [ "MAN OF THE YEAR", "has_genre", "DRAMA" ], [ "MAN OF THE YEAR", "has_tags", "COMEDY" ], [ "MUMFORD", "has_genre", "COMEDY" ], [ "MUMFORD", "has_genre", "DRAMA" ], [ "NOTHING IN COMMON", "has_genre", "COMEDY" ], [ "NOTHING IN COMMON", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_genre", "COMEDY" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "COMEDY" ], [ "POLICE", "has_genre", "DRAMA" ], [ "RAISING HELEN", "has_genre", "COMEDY" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "ROOMMATES", "has_genre", "COMEDY" ], [ "ROOMMATES", "has_genre", "DRAMA" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "has_genre", "DRAMA" ], [ "SABRINA", "has_tags", "DRAMA" ], [ "SAY ANYTHING...", "has_genre", "COMEDY" ], [ "SAY ANYTHING...", "has_genre", "DRAMA" ], [ "SHIRLEY VALENTINE", "has_genre", "COMEDY" ], [ "SHIRLEY VALENTINE", "has_genre", "DRAMA" ], [ "SIX PACK", "has_genre", "COMEDY" ], [ "SIX PACK", "has_genre", "DRAMA" ], [ "SLEEPY HOLLOW", "has_tags", "R" ], [ "SLEEPY HOLLOW", "written_by", "WASHINGTON IRVING" ], [ "SOMETHING TO TALK ABOUT", "has_genre", "COMEDY" ], [ "SOMETHING TO TALK ABOUT", "has_genre", "DRAMA" ], [ "STARSTRUCK", "has_genre", "COMEDY" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "STAYING TOGETHER", "has_genre", "COMEDY" ], [ "STAYING TOGETHER", "has_genre", "DRAMA" ], [ "STEEL MAGNOLIAS", "has_genre", "COMEDY" ], [ "STEEL MAGNOLIAS", "has_genre", "DRAMA" ], [ "STONEWALL", "has_genre", "COMEDY" ], [ "STONEWALL", "has_genre", "DRAMA" ], [ "TEMPEST", "has_genre", "COMEDY" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_genre", "COMEDY" ], [ "THE AMERICAN PRESIDENT", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_tags", "DRAMA" ], [ "THE BROTHERS MCMULLEN", "has_genre", "COMEDY" ], [ "THE BROTHERS MCMULLEN", "has_genre", "DRAMA" ], [ "THE FUNERAL", "has_genre", "COMEDY" ], [ "THE FUNERAL", "has_genre", "DRAMA" ], [ "THE GRASS HARP", "has_genre", "COMEDY" ], [ "THE GRASS HARP", "has_genre", "DRAMA" ], [ "THE WIZARD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "DRAMA" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "COMEDY" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "DRAMA" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "COMEDY" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "DRAMA" ], [ "TWISTER", "has_genre", "COMEDY" ], [ "TWISTER", "has_genre", "DRAMA" ], [ "UNSTRUNG HEROES", "has_genre", "COMEDY" ], [ "UNSTRUNG HEROES", "has_genre", "DRAMA" ], [ "YOUNG DOCTORS IN LOVE", "has_genre", "COMEDY" ], [ "YOUNG DOCTORS IN LOVE", "release_year", "1982" ], [ "YOUNG DOCTORS IN LOVE", "starred_actors", "SEAN YOUNG" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 35798, 2010 17939, BURT REYNOLDS 32334, CANNONBALL RUN II 32696, CITY HEAT 28094, DELIVERANCE 26473, FRANCE NUYEN 1646, RAPE 20882, REMEMBER ME 25348, SATAN NEVER SLEEPS src, edge_attr, dst 35798, release_year, 24525 32334, release_year, 24525 32334, starred_actors, 17939 32696, release_year, 24525 32696, starred_actors, 17939 28094, has_tags, 17939 28094, has_tags, 1646 28094, starred_actors, 17939 20882, release_year, 35798 25348, has_tags, 1646 25348, starred_actors, 26473 Question: How are BURT REYNOLDS, FRANCE NUYEN, and REMEMBER ME related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BURT REYNOLDS", "FRANCE NUYEN", "REMEMBER ME" ], "valid_edges": [ [ "2010", "release_year", "1984" ], [ "CANNONBALL RUN II", "release_year", "1984" ], [ "CANNONBALL RUN II", "starred_actors", "BURT REYNOLDS" ], [ "CITY HEAT", "release_year", "1984" ], [ "CITY HEAT", "starred_actors", "BURT REYNOLDS" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "has_tags", "RAPE" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "REMEMBER ME", "release_year", "2010" ], [ "SATAN NEVER SLEEPS", "has_tags", "RAPE" ], [ "SATAN NEVER SLEEPS", "starred_actors", "FRANCE NUYEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 24447, A PURE FORMALITY 34157, BLINK 20616, CALLAN 13659, DISCLOSURE 6730, ERIC PORTER 30921, MUTE WITNESS 12972, NIGHT WATCH 20417, NIGHTWATCH 25419, PENN BADGLEY 34601, RUSSIA 6524, THE GETAWAY 35993, THE STEPFATHER 24811, THRILLER 8334, TRANSSIBERIAN 18233, TRIAL BY JURY src, edge_attr, dst 24447, has_genre, 24811 24447, release_year, 26257 34157, has_tags, 24811 34157, release_year, 26257 20616, has_genre, 24811 20616, starred_actors, 6730 13659, has_genre, 24811 13659, release_year, 26257 30921, has_genre, 24811 30921, has_tags, 34601 30921, release_year, 26257 12972, has_genre, 24811 12972, has_tags, 34601 20417, has_genre, 24811 20417, release_year, 26257 6524, has_genre, 24811 6524, release_year, 26257 35993, has_genre, 24811 35993, starred_actors, 25419 8334, has_tags, 34601 8334, has_tags, 24811 18233, has_genre, 24811 18233, release_year, 26257 Question: In what context are ERIC PORTER, MUTE WITNESS, and PENN BADGLEY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ERIC PORTER", "MUTE WITNESS", "PENN BADGLEY" ], "valid_edges": [ [ "A PURE FORMALITY", "has_genre", "THRILLER" ], [ "A PURE FORMALITY", "release_year", "1994" ], [ "BLINK", "has_tags", "THRILLER" ], [ "BLINK", "release_year", "1994" ], [ "CALLAN", "has_genre", "THRILLER" ], [ "CALLAN", "starred_actors", "ERIC PORTER" ], [ "DISCLOSURE", "has_genre", "THRILLER" ], [ "DISCLOSURE", "release_year", "1994" ], [ "MUTE WITNESS", "has_genre", "THRILLER" ], [ "MUTE WITNESS", "has_tags", "RUSSIA" ], [ "MUTE WITNESS", "release_year", "1994" ], [ "NIGHT WATCH", "has_genre", "THRILLER" ], [ "NIGHT WATCH", "has_tags", "RUSSIA" ], [ "NIGHTWATCH", "has_genre", "THRILLER" ], [ "NIGHTWATCH", "release_year", "1994" ], [ "THE GETAWAY", "has_genre", "THRILLER" ], [ "THE GETAWAY", "release_year", "1994" ], [ "THE STEPFATHER", "has_genre", "THRILLER" ], [ "THE STEPFATHER", "starred_actors", "PENN BADGLEY" ], [ "TRANSSIBERIAN", "has_tags", "RUSSIA" ], [ "TRANSSIBERIAN", "has_tags", "THRILLER" ], [ "TRIAL BY JURY", "has_genre", "THRILLER" ], [ "TRIAL BY JURY", "release_year", "1994" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 39289, ACTION 17256, DONNIE YEN 36212, DRAMA 13091, FLASH POINT 10121, IP MAN 38168, IP MAN 2 11564, JOEL BISSONNETTE 26301, MARTIAL ARTS 26904, PASSENGER SIDE 1398, SCOT ARMSTRONG 19595, THE HEARTBREAK KID 15676, WILSON YIP 5052, WING CHUN src, edge_attr, dst 13091, directed_by, 15676 13091, has_genre, 39289 13091, release_year, 17315 13091, starred_actors, 17256 10121, directed_by, 15676 10121, has_genre, 39289 10121, has_tags, 39289 10121, has_tags, 17256 10121, has_tags, 10121 10121, has_tags, 26301 10121, has_tags, 15676 10121, has_tags, 5052 10121, starred_actors, 17256 38168, directed_by, 15676 38168, has_genre, 36212 38168, has_tags, 17256 38168, has_tags, 10121 38168, has_tags, 26301 38168, has_tags, 15676 38168, has_tags, 5052 38168, starred_actors, 17256 26904, has_genre, 36212 26904, starred_actors, 11564 19595, release_year, 17315 19595, written_by, 1398 Question: How are JOEL BISSONNETTE, SCOT ARMSTRONG, and WILSON YIP related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOEL BISSONNETTE", "SCOT ARMSTRONG", "WILSON YIP" ], "valid_edges": [ [ "FLASH POINT", "directed_by", "WILSON YIP" ], [ "FLASH POINT", "has_genre", "ACTION" ], [ "FLASH POINT", "release_year", "2007" ], [ "FLASH POINT", "starred_actors", "DONNIE YEN" ], [ "IP MAN", "directed_by", "WILSON YIP" ], [ "IP MAN", "has_genre", "ACTION" ], [ "IP MAN", "has_tags", "ACTION" ], [ "IP MAN", "has_tags", "DONNIE YEN" ], [ "IP MAN", "has_tags", "IP MAN" ], [ "IP MAN", "has_tags", "MARTIAL ARTS" ], [ "IP MAN", "has_tags", "WILSON YIP" ], [ "IP MAN", "has_tags", "WING CHUN" ], [ "IP MAN", "starred_actors", "DONNIE YEN" ], [ "IP MAN 2", "directed_by", "WILSON YIP" ], [ "IP MAN 2", "has_genre", "DRAMA" ], [ "IP MAN 2", "has_tags", "DONNIE YEN" ], [ "IP MAN 2", "has_tags", "IP MAN" ], [ "IP MAN 2", "has_tags", "MARTIAL ARTS" ], [ "IP MAN 2", "has_tags", "WILSON YIP" ], [ "IP MAN 2", "has_tags", "WING CHUN" ], [ "IP MAN 2", "starred_actors", "DONNIE YEN" ], [ "PASSENGER SIDE", "has_genre", "DRAMA" ], [ "PASSENGER SIDE", "starred_actors", "JOEL BISSONNETTE" ], [ "THE HEARTBREAK KID", "release_year", "2007" ], [ "THE HEARTBREAK KID", "written_by", "SCOT ARMSTRONG" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18239, A RAISIN IN THE SUN 36212, DRAMA 7333, KAREN JOY FOWLER 36092, TEN NORTH FREDERICK 12191, THE JANE AUSTEN BOOK CLUB src, edge_attr, dst 18239, has_genre, 36212 36092, has_genre, 36212 12191, has_genre, 36212 12191, written_by, 7333 Question: In what context are A RAISIN IN THE SUN, KAREN JOY FOWLER, and TEN NORTH FREDERICK connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A RAISIN IN THE SUN", "KAREN JOY FOWLER", "TEN NORTH FREDERICK" ], "valid_edges": [ [ "A RAISIN IN THE SUN", "has_genre", "DRAMA" ], [ "TEN NORTH FREDERICK", "has_genre", "DRAMA" ], [ "THE JANE AUSTEN BOOK CLUB", "has_genre", "DRAMA" ], [ "THE JANE AUSTEN BOOK CLUB", "written_by", "KAREN JOY FOWLER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 1421, 2013 13546, ACTING 33132, ARNOLD SCHWARZENEGGER 22349, CRAWLSPACE 8491, ESCAPE PLAN 35533, GENERATION IRON 1897, OBLIVION 8342, OSCAR REDDING 23588, PROMETHEUS 24173, THE EXPENDABLES 2 14665, THE LAST STAND 32701, THE SEASONING HOUSE 13259, TOTAL RECALL 16793, VAN DIEMEN'S LAND src, edge_attr, dst 658, release_year, 27261 22349, release_year, 658 22349, release_year, 1421 8491, has_tags, 33132 8491, release_year, 1421 8491, starred_actors, 33132 35533, release_year, 1421 35533, starred_actors, 33132 1897, has_tags, 13546 1897, release_year, 1421 23588, has_tags, 13546 23588, release_year, 658 24173, has_tags, 33132 24173, release_year, 658 14665, has_tags, 13546 14665, has_tags, 33132 14665, release_year, 1421 14665, starred_actors, 33132 32701, release_year, 658 13259, has_tags, 33132 13259, release_year, 658 13259, starred_actors, 33132 16793, release_year, 27261 16793, starred_actors, 8342 16793, written_by, 8342 Question: In what context are OSCAR REDDING, THE LAST STAND, and THE SEASONING HOUSE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "OSCAR REDDING", "THE LAST STAND", "THE SEASONING HOUSE" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "CRAWLSPACE", "release_year", "2012" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "ESCAPE PLAN", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "ESCAPE PLAN", "release_year", "2013" ], [ "ESCAPE PLAN", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "GENERATION IRON", "release_year", "2013" ], [ "GENERATION IRON", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "OBLIVION", "has_tags", "ACTING" ], [ "OBLIVION", "release_year", "2013" ], [ "PROMETHEUS", "has_tags", "ACTING" ], [ "PROMETHEUS", "release_year", "2012" ], [ "THE EXPENDABLES 2", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "THE EXPENDABLES 2", "release_year", "2012" ], [ "THE LAST STAND", "has_tags", "ACTING" ], [ "THE LAST STAND", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "THE LAST STAND", "release_year", "2013" ], [ "THE LAST STAND", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "THE SEASONING HOUSE", "release_year", "2012" ], [ "TOTAL RECALL", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "TOTAL RECALL", "release_year", "2012" ], [ "TOTAL RECALL", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "VAN DIEMEN'S LAND", "release_year", "2009" ], [ "VAN DIEMEN'S LAND", "starred_actors", "OSCAR REDDING" ], [ "VAN DIEMEN'S LAND", "written_by", "OSCAR REDDING" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8783, 1977 7841, 1987 27261, 2009 658, 2012 1421, 2013 22078, ARBITRAGE 33105, BRIDE OF BOOGEDY 30463, COMEDY 10816, DEAD MAN WALKING 36212, DRAMA 37496, ELIZABETHTOWN 880, IRRESISTIBLE 37830, JEFF, WHO LIVES AT HOME 35629, JOE 17903, LEAVES OF GRASS 16441, LIGHT SLEEPER 6706, MARK JACOBSON 31735, MIDDLE OF NOWHERE 37353, NOEL 3564, OZ SCOTT 12008, PRETTY BABY 17353, SAFE PASSAGE 36442, SNITCH 33439, STEPMOM 38238, SUSAN SARANDON 2819, TEMPEST 267, THE BELIEVER 8847, THE GREAT WALDO PEPPER 33198, THE GREATEST 21326, THE LAST OF ROBIN HOOD 26894, THE LOVELY BONES 14975, THE OTHER SIDE OF MIDNIGHT 14621, THE WITCHES OF EASTWICK 9364, WHITE PALACE src, edge_attr, dst 22078, has_genre, 36212 22078, has_tags, 38238 22078, release_year, 658 22078, starred_actors, 38238 33105, directed_by, 3564 33105, release_year, 7841 10816, has_genre, 36212 10816, has_tags, 36212 10816, has_tags, 38238 10816, starred_actors, 38238 37496, has_genre, 30463 37496, has_genre, 36212 37496, has_tags, 38238 37496, starred_actors, 38238 880, has_genre, 36212 880, starred_actors, 38238 37830, has_genre, 30463 37830, has_genre, 36212 37830, starred_actors, 38238 35629, has_genre, 36212 35629, release_year, 1421 35629, starred_actors, 38238 17903, has_genre, 30463 17903, has_genre, 36212 17903, has_tags, 38238 17903, release_year, 27261 16441, has_genre, 36212 16441, starred_actors, 38238 31735, has_genre, 30463 31735, has_genre, 36212 31735, release_year, 658 31735, starred_actors, 38238 37353, has_genre, 36212 37353, has_tags, 36212 37353, starred_actors, 38238 12008, has_genre, 36212 12008, starred_actors, 38238 17353, has_genre, 36212 17353, starred_actors, 38238 36442, has_genre, 36212 36442, release_year, 1421 36442, starred_actors, 38238 33439, has_genre, 30463 33439, has_genre, 36212 33439, has_tags, 38238 33439, starred_actors, 38238 2819, has_genre, 30463 2819, has_genre, 36212 2819, starred_actors, 38238 267, has_genre, 36212 267, written_by, 6706 8847, has_genre, 36212 8847, starred_actors, 38238 33198, has_genre, 36212 33198, has_tags, 38238 33198, release_year, 8783 33198, release_year, 27261 33198, starred_actors, 38238 21326, has_genre, 36212 21326, release_year, 1421 21326, starred_actors, 38238 26894, has_genre, 36212 26894, has_tags, 38238 26894, release_year, 27261 26894, starred_actors, 38238 14975, has_genre, 36212 14975, release_year, 8783 14975, starred_actors, 38238 14621, has_genre, 30463 14621, release_year, 7841 14621, starred_actors, 38238 9364, has_genre, 36212 9364, starred_actors, 38238 Question: How are MARK JACOBSON, OZ SCOTT, and SUSAN SARANDON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MARK JACOBSON", "OZ SCOTT", "SUSAN SARANDON" ], "valid_edges": [ [ "ARBITRAGE", "has_genre", "DRAMA" ], [ "ARBITRAGE", "has_tags", "SUSAN SARANDON" ], [ "ARBITRAGE", "release_year", "2012" ], [ "ARBITRAGE", "starred_actors", "SUSAN SARANDON" ], [ "BRIDE OF BOOGEDY", "directed_by", "OZ SCOTT" ], [ "BRIDE OF BOOGEDY", "release_year", "1987" ], [ "DEAD MAN WALKING", "has_genre", "DRAMA" ], [ "DEAD MAN WALKING", "has_tags", "DRAMA" ], [ "DEAD MAN WALKING", "has_tags", "SUSAN SARANDON" ], [ "DEAD MAN WALKING", "starred_actors", "SUSAN SARANDON" ], [ "ELIZABETHTOWN", "has_genre", "COMEDY" ], [ "ELIZABETHTOWN", "has_genre", "DRAMA" ], [ "ELIZABETHTOWN", "has_tags", "SUSAN SARANDON" ], [ "ELIZABETHTOWN", "starred_actors", "SUSAN SARANDON" ], [ "IRRESISTIBLE", "has_genre", "DRAMA" ], [ "IRRESISTIBLE", "starred_actors", "SUSAN SARANDON" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "COMEDY" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "DRAMA" ], [ "JEFF, WHO LIVES AT HOME", "starred_actors", "SUSAN SARANDON" ], [ "JOE", "has_genre", "DRAMA" ], [ "JOE", "release_year", "2013" ], [ "JOE", "starred_actors", "SUSAN SARANDON" ], [ "LEAVES OF GRASS", "has_genre", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "DRAMA" ], [ "LEAVES OF GRASS", "has_tags", "SUSAN SARANDON" ], [ "LEAVES OF GRASS", "release_year", "2009" ], [ "LIGHT SLEEPER", "has_genre", "DRAMA" ], [ "LIGHT SLEEPER", "starred_actors", "SUSAN SARANDON" ], [ "MIDDLE OF NOWHERE", "has_genre", "COMEDY" ], [ "MIDDLE OF NOWHERE", "has_genre", "DRAMA" ], [ "MIDDLE OF NOWHERE", "release_year", "2012" ], [ "MIDDLE OF NOWHERE", "starred_actors", "SUSAN SARANDON" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "starred_actors", "SUSAN SARANDON" ], [ "PRETTY BABY", "has_genre", "DRAMA" ], [ "PRETTY BABY", "starred_actors", "SUSAN SARANDON" ], [ "SAFE PASSAGE", "has_genre", "DRAMA" ], [ "SAFE PASSAGE", "starred_actors", "SUSAN SARANDON" ], [ "SNITCH", "has_genre", "DRAMA" ], [ "SNITCH", "release_year", "2013" ], [ "SNITCH", "starred_actors", "SUSAN SARANDON" ], [ "STEPMOM", "has_genre", "COMEDY" ], [ "STEPMOM", "has_genre", "DRAMA" ], [ "STEPMOM", "has_tags", "SUSAN SARANDON" ], [ "STEPMOM", "starred_actors", "SUSAN SARANDON" ], [ "TEMPEST", "has_genre", "COMEDY" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "TEMPEST", "starred_actors", "SUSAN SARANDON" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "written_by", "MARK JACOBSON" ], [ "THE GREAT WALDO PEPPER", "has_genre", "DRAMA" ], [ "THE GREAT WALDO PEPPER", "starred_actors", "SUSAN SARANDON" ], [ "THE GREATEST", "has_genre", "DRAMA" ], [ "THE GREATEST", "has_tags", "SUSAN SARANDON" ], [ "THE GREATEST", "release_year", "1977" ], [ "THE GREATEST", "release_year", "2009" ], [ "THE GREATEST", "starred_actors", "SUSAN SARANDON" ], [ "THE LAST OF ROBIN HOOD", "has_genre", "DRAMA" ], [ "THE LAST OF ROBIN HOOD", "release_year", "2013" ], [ "THE LAST OF ROBIN HOOD", "starred_actors", "SUSAN SARANDON" ], [ "THE LOVELY BONES", "has_genre", "DRAMA" ], [ "THE LOVELY BONES", "has_tags", "SUSAN SARANDON" ], [ "THE LOVELY BONES", "release_year", "2009" ], [ "THE LOVELY BONES", "starred_actors", "SUSAN SARANDON" ], [ "THE OTHER SIDE OF MIDNIGHT", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF MIDNIGHT", "release_year", "1977" ], [ "THE OTHER SIDE OF MIDNIGHT", "starred_actors", "SUSAN SARANDON" ], [ "THE WITCHES OF EASTWICK", "has_genre", "COMEDY" ], [ "THE WITCHES OF EASTWICK", "release_year", "1987" ], [ "THE WITCHES OF EASTWICK", "starred_actors", "SUSAN SARANDON" ], [ "WHITE PALACE", "has_genre", "DRAMA" ], [ "WHITE PALACE", "starred_actors", "SUSAN SARANDON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 18243, A SCANNER DARKLY 24177, ANIMATION 2795, PENGUINS OF MADAGASCAR 36862, PHILIP K. DICK 34922, PK 34199, SANJAY DUTT 23344, SIMON J. SMITH src, edge_attr, dst 18243, has_genre, 24177 18243, has_tags, 24177 18243, has_tags, 36862 18243, written_by, 36862 2795, directed_by, 23344 2795, has_genre, 24177 2795, has_tags, 24177 2795, release_year, 9377 34922, release_year, 9377 34922, starred_actors, 34199 Question: For what reason are PHILIP K. DICK, SANJAY DUTT, and SIMON J. SMITH associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "PHILIP K. DICK", "SANJAY DUTT", "SIMON J. SMITH" ], "valid_edges": [ [ "A SCANNER DARKLY", "has_genre", "ANIMATION" ], [ "A SCANNER DARKLY", "has_tags", "ANIMATION" ], [ "A SCANNER DARKLY", "has_tags", "PHILIP K. DICK" ], [ "A SCANNER DARKLY", "written_by", "PHILIP K. DICK" ], [ "PENGUINS OF MADAGASCAR", "directed_by", "SIMON J. SMITH" ], [ "PENGUINS OF MADAGASCAR", "has_genre", "ANIMATION" ], [ "PENGUINS OF MADAGASCAR", "has_tags", "ANIMATION" ], [ "PENGUINS OF MADAGASCAR", "release_year", "2014" ], [ "PK", "release_year", "2014" ], [ "PK", "starred_actors", "SANJAY DUTT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7841, 1987 10702, 1991 4713, A RETURN TO SALEM'S LOT 25905, ANGEL HEART 6748, ANGUISH 12844, BAD KARMA 34587, BAD TASTE 36593, BLACK CHRISTMAS 16020, BODY PARTS 32401, CAST A DEADLY SPELL 37126, CASTLE FREAK 32780, CHILDREN OF THE NIGHT 19984, CREEPSHOW 2 4824, DAGON 23612, DOLLS 6158, EDGAR ALLAN POE 16661, EVIL DEAD II 3270, FROM BEYOND 12498, HELLRAISER 5870, HORROR 10955, HOUSE OF USHER 3995, KEIR DULLEA 36631, MUNCHIES 18744, MURDERS IN THE RUE MORGUE 14237, NEAR DARK 15661, NEKROMANTIK 38235, NEKROMANTIK 2 38962, OPERA 24431, PHANTOM OF THE RUE MORGUE 284, POISON 8138, POPCORN 4323, PRINCE OF DARKNESS 39358, RE-ANIMATOR 9184, RETURN TO HORROR HIGH 18856, ROCK 'N' ROLL NIGHTMARE 11041, SILENT NIGHT, DEADLY NIGHT PART 2 8436, SPIRITS OF THE DEAD 18809, STUART GORDON 20148, SUBSPECIES 26202, TALES OF TERROR 28739, THE BELIEVERS 27437, THE BLACK CAT 11327, THE BORROWER 10194, THE BRAVE LITTLE TOASTER 8063, THE CURSE 16105, THE DEAD 23699, THE DENTIST 17646, THE FALL OF THE HOUSE OF USHER 38230, THE GATE 25175, THE HAUNTED PALACE 3318, THE LOST BOYS 11243, THE MASQUE OF THE RED DEATH 33993, THE MONSTER SQUAD 36578, THE PEOPLE UNDER THE STAIRS 37211, THE PIT AND THE PENDULUM 18162, THE RAVEN 27836, THE SILENCE OF THE LAMBS 35993, THE STEPFATHER 21559, THE TOMB OF LIGEIA 37650, TWO EVIL EYES 8589, WICKED CITY 6037, WITCHFINDER GENERAL src, edge_attr, dst 4713, has_genre, 5870 4713, release_year, 7841 25905, has_genre, 5870 25905, release_year, 7841 6748, has_genre, 5870 6748, release_year, 7841 12844, has_genre, 5870 12844, release_year, 10702 34587, has_genre, 5870 34587, release_year, 7841 36593, has_genre, 5870 36593, has_tags, 5870 36593, starred_actors, 3995 16020, has_genre, 5870 16020, release_year, 10702 32401, has_genre, 5870 32401, release_year, 10702 37126, directed_by, 18809 37126, has_genre, 5870 37126, written_by, 18809 32780, has_genre, 5870 32780, release_year, 10702 19984, has_genre, 5870 19984, release_year, 7841 4824, directed_by, 18809 4824, has_genre, 5870 23612, directed_by, 18809 23612, has_genre, 5870 23612, release_year, 7841 16661, has_genre, 5870 16661, has_tags, 5870 16661, release_year, 7841 3270, directed_by, 18809 3270, has_genre, 5870 3270, written_by, 18809 12498, has_genre, 5870 12498, has_tags, 5870 12498, release_year, 7841 10955, has_genre, 5870 10955, has_tags, 6158 10955, has_tags, 5870 10955, written_by, 6158 36631, has_genre, 5870 36631, release_year, 7841 18744, has_genre, 5870 18744, has_tags, 6158 18744, written_by, 6158 14237, has_genre, 5870 14237, release_year, 7841 15661, has_genre, 5870 15661, release_year, 7841 38235, has_genre, 5870 38235, release_year, 10702 38962, has_genre, 5870 38962, release_year, 7841 24431, has_genre, 5870 24431, written_by, 6158 284, has_genre, 5870 284, release_year, 10702 8138, has_genre, 5870 8138, release_year, 10702 4323, has_genre, 5870 4323, release_year, 7841 39358, directed_by, 18809 39358, has_genre, 5870 39358, has_tags, 5870 39358, written_by, 18809 9184, has_genre, 5870 9184, release_year, 7841 18856, has_genre, 5870 18856, release_year, 7841 11041, has_genre, 5870 11041, release_year, 7841 8436, has_genre, 5870 8436, has_tags, 6158 8436, written_by, 6158 20148, has_genre, 5870 20148, release_year, 10702 26202, has_genre, 5870 26202, has_tags, 6158 26202, written_by, 6158 28739, has_genre, 5870 28739, release_year, 7841 27437, has_genre, 5870 27437, has_tags, 6158 27437, written_by, 6158 11327, has_genre, 5870 11327, release_year, 10702 10194, release_year, 7841 8063, has_genre, 5870 8063, release_year, 7841 16105, has_genre, 5870 16105, release_year, 7841 23699, has_genre, 5870 23699, written_by, 18809 17646, has_genre, 5870 17646, has_tags, 6158 17646, written_by, 6158 38230, has_genre, 5870 38230, release_year, 7841 25175, has_genre, 5870 25175, has_tags, 6158 25175, written_by, 6158 3318, has_genre, 5870 3318, has_tags, 5870 3318, release_year, 7841 11243, has_genre, 5870 11243, has_tags, 6158 11243, written_by, 6158 33993, has_tags, 5870 33993, release_year, 7841 36578, has_genre, 5870 36578, release_year, 10702 37211, directed_by, 18809 37211, has_genre, 5870 37211, has_tags, 6158 37211, release_year, 10702 37211, written_by, 6158 18162, has_genre, 5870 18162, has_tags, 6158 18162, has_tags, 5870 18162, written_by, 6158 27836, has_tags, 5870 27836, release_year, 10702 35993, has_genre, 5870 35993, release_year, 7841 21559, has_genre, 5870 21559, has_tags, 6158 21559, has_tags, 5870 21559, written_by, 6158 37650, has_genre, 5870 37650, has_tags, 6158 37650, written_by, 6158 8589, has_genre, 5870 8589, release_year, 7841 6037, has_genre, 5870 6037, has_tags, 6158 Question: How are KEIR DULLEA, THE BRAVE LITTLE TOASTER, and THE PIT AND THE PENDULUM related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KEIR DULLEA", "THE BRAVE LITTLE TOASTER", "THE PIT AND THE PENDULUM" ], "valid_edges": [ [ "A RETURN TO SALEM'S LOT", "has_genre", "HORROR" ], [ "A RETURN TO SALEM'S LOT", "release_year", "1987" ], [ "ANGEL HEART", "has_genre", "HORROR" ], [ "ANGEL HEART", "release_year", "1987" ], [ "ANGUISH", "has_genre", "HORROR" ], [ "ANGUISH", "release_year", "1987" ], [ "BAD KARMA", "has_genre", "HORROR" ], [ "BAD KARMA", "release_year", "1991" ], [ "BAD TASTE", "has_genre", "HORROR" ], [ "BAD TASTE", "release_year", "1987" ], [ "BLACK CHRISTMAS", "has_genre", "HORROR" ], [ "BLACK CHRISTMAS", "has_tags", "HORROR" ], [ "BLACK CHRISTMAS", "starred_actors", "KEIR DULLEA" ], [ "BODY PARTS", "has_genre", "HORROR" ], [ "BODY PARTS", "release_year", "1991" ], [ "CAST A DEADLY SPELL", "has_genre", "HORROR" ], [ "CAST A DEADLY SPELL", "release_year", "1991" ], [ "CASTLE FREAK", "directed_by", "STUART GORDON" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "written_by", "STUART GORDON" ], [ "CHILDREN OF THE NIGHT", "has_genre", "HORROR" ], [ "CHILDREN OF THE NIGHT", "release_year", "1991" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "release_year", "1987" ], [ "DAGON", "directed_by", "STUART GORDON" ], [ "DAGON", "has_genre", "HORROR" ], [ "DOLLS", "directed_by", "STUART GORDON" ], [ "DOLLS", "has_genre", "HORROR" ], [ "DOLLS", "release_year", "1987" ], [ "EVIL DEAD II", "has_genre", "HORROR" ], [ "EVIL DEAD II", "has_tags", "HORROR" ], [ "EVIL DEAD II", "release_year", "1987" ], [ "FROM BEYOND", "directed_by", "STUART GORDON" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "written_by", "STUART GORDON" ], [ "HELLRAISER", "has_genre", "HORROR" ], [ "HELLRAISER", "has_tags", "HORROR" ], [ "HELLRAISER", "release_year", "1987" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "EDGAR ALLAN POE" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF USHER", "written_by", "EDGAR ALLAN POE" ], [ "MUNCHIES", "has_genre", "HORROR" ], [ "MUNCHIES", "release_year", "1987" ], [ "MURDERS IN THE RUE MORGUE", "has_genre", "HORROR" ], [ "MURDERS IN THE RUE MORGUE", "has_tags", "EDGAR ALLAN POE" ], [ "MURDERS IN THE RUE MORGUE", "written_by", "EDGAR ALLAN POE" ], [ "NEAR DARK", "has_genre", "HORROR" ], [ "NEAR DARK", "release_year", "1987" ], [ "NEKROMANTIK", "has_genre", "HORROR" ], [ "NEKROMANTIK", "release_year", "1987" ], [ "NEKROMANTIK 2", "has_genre", "HORROR" ], [ "NEKROMANTIK 2", "release_year", "1991" ], [ "OPERA", "has_genre", "HORROR" ], [ "OPERA", "release_year", "1987" ], [ "PHANTOM OF THE RUE MORGUE", "has_genre", "HORROR" ], [ "PHANTOM OF THE RUE MORGUE", "written_by", "EDGAR ALLAN POE" ], [ "POISON", "has_genre", "HORROR" ], [ "POISON", "release_year", "1991" ], [ "POPCORN", "has_genre", "HORROR" ], [ "POPCORN", "release_year", "1991" ], [ "PRINCE OF DARKNESS", "has_genre", "HORROR" ], [ "PRINCE OF DARKNESS", "release_year", "1987" ], [ "RE-ANIMATOR", "directed_by", "STUART GORDON" ], [ "RE-ANIMATOR", "has_genre", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "HORROR" ], [ "RE-ANIMATOR", "written_by", "STUART GORDON" ], [ "RETURN TO HORROR HIGH", "has_genre", "HORROR" ], [ "RETURN TO HORROR HIGH", "release_year", "1987" ], [ "ROCK 'N' ROLL NIGHTMARE", "has_genre", "HORROR" ], [ "ROCK 'N' ROLL NIGHTMARE", "release_year", "1987" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "has_genre", "HORROR" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "release_year", "1987" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "EDGAR ALLAN POE" ], [ "SPIRITS OF THE DEAD", "written_by", "EDGAR ALLAN POE" ], [ "SUBSPECIES", "has_genre", "HORROR" ], [ "SUBSPECIES", "release_year", "1991" ], [ "TALES OF TERROR", "has_genre", "HORROR" ], [ "TALES OF TERROR", "has_tags", "EDGAR ALLAN POE" ], [ "TALES OF TERROR", "written_by", "EDGAR ALLAN POE" ], [ "THE BELIEVERS", "has_genre", "HORROR" ], [ "THE BELIEVERS", "release_year", "1987" ], [ "THE BLACK CAT", "has_genre", "HORROR" ], [ "THE BLACK CAT", "has_tags", "EDGAR ALLAN POE" ], [ "THE BLACK CAT", "written_by", "EDGAR ALLAN POE" ], [ "THE BORROWER", "has_genre", "HORROR" ], [ "THE BORROWER", "release_year", "1991" ], [ "THE BRAVE LITTLE TOASTER", "release_year", "1987" ], [ "THE CURSE", "has_genre", "HORROR" ], [ "THE CURSE", "release_year", "1987" ], [ "THE DEAD", "has_genre", "HORROR" ], [ "THE DEAD", "release_year", "1987" ], [ "THE DENTIST", "has_genre", "HORROR" ], [ "THE DENTIST", "written_by", "STUART GORDON" ], [ "THE FALL OF THE HOUSE OF USHER", "has_genre", "HORROR" ], [ "THE FALL OF THE HOUSE OF USHER", "has_tags", "EDGAR ALLAN POE" ], [ "THE FALL OF THE HOUSE OF USHER", "written_by", "EDGAR ALLAN POE" ], [ "THE GATE", "has_genre", "HORROR" ], [ "THE GATE", "release_year", "1987" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "EDGAR ALLAN POE" ], [ "THE HAUNTED PALACE", "written_by", "EDGAR ALLAN POE" ], [ "THE LOST BOYS", "has_genre", "HORROR" ], [ "THE LOST BOYS", "has_tags", "HORROR" ], [ "THE LOST BOYS", "release_year", "1987" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "EDGAR ALLAN POE" ], [ "THE MASQUE OF THE RED DEATH", "written_by", "EDGAR ALLAN POE" ], [ "THE MONSTER SQUAD", "has_tags", "HORROR" ], [ "THE MONSTER SQUAD", "release_year", "1987" ], [ "THE PEOPLE UNDER THE STAIRS", "has_genre", "HORROR" ], [ "THE PEOPLE UNDER THE STAIRS", "release_year", "1991" ], [ "THE PIT AND THE PENDULUM", "directed_by", "STUART GORDON" ], [ "THE PIT AND THE PENDULUM", "has_genre", "HORROR" ], [ "THE PIT AND THE PENDULUM", "has_tags", "EDGAR ALLAN POE" ], [ "THE PIT AND THE PENDULUM", "release_year", "1991" ], [ "THE PIT AND THE PENDULUM", "written_by", "EDGAR ALLAN POE" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "EDGAR ALLAN POE" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE RAVEN", "written_by", "EDGAR ALLAN POE" ], [ "THE SILENCE OF THE LAMBS", "has_tags", "HORROR" ], [ "THE SILENCE OF THE LAMBS", "release_year", "1991" ], [ "THE STEPFATHER", "has_genre", "HORROR" ], [ "THE STEPFATHER", "release_year", "1987" ], [ "THE TOMB OF LIGEIA", "has_genre", "HORROR" ], [ "THE TOMB OF LIGEIA", "has_tags", "EDGAR ALLAN POE" ], [ "THE TOMB OF LIGEIA", "has_tags", "HORROR" ], [ "THE TOMB OF LIGEIA", "written_by", "EDGAR ALLAN POE" ], [ "TWO EVIL EYES", "has_genre", "HORROR" ], [ "TWO EVIL EYES", "has_tags", "EDGAR ALLAN POE" ], [ "TWO EVIL EYES", "written_by", "EDGAR ALLAN POE" ], [ "WICKED CITY", "has_genre", "HORROR" ], [ "WICKED CITY", "release_year", "1987" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "EDGAR ALLAN POE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18656, 1944 2133, 1998 26163, 20,000 YEARS IN SING SING 37484, 2004 6139, A STOLEN LIFE 22709, ALL ABOUT EVE 4617, ALL THIS, AND HEAVEN TOO 26158, ANOTHER MAN'S POISON 37608, AUSTRALIA 9367, BETTE DAVIS 11929, CASABLANCA 21072, CLAUDE RAINS 1968, COBRA WOMAN 19193, DANGEROUS 37778, DARK VICTORY 20161, DECEPTION 18074, DRAGON SEED 36212, DRAMA 26366, EDWARD NORTON 18210, FOUR DAUGHTERS 39145, FURY 8612, GEORGE COULOURIS 25033, GOING MY WAY 35248, HARRIET CRAIG 3259, I'LL BE SEEING YOU 34341, IN THIS OUR LIFE 26372, JERRY SPRINGER 29848, JEZEBEL 19209, JOHN CURRAN 18688, MARKED WOMAN 10202, MOONTIDE 37704, MR. SKEFFINGTON 26086, MR. SMITH GOES TO WASHINGTON 36406, MRS. PARKINGTON 18389, NOW, VOYAGER 4435, OF HUMAN BONDAGE 18256, OLD ACQUAINTANCE 9090, PRAISE 24415, RINGMASTER 4504, STONE 10358, STORM CENTER 15199, THE CABIN IN THE COTTON 31280, THE CATERED AFFAIR 14219, THE CHILDREN ARE WATCHING US 39333, THE CLAIRVOYANT 32516, THE CORN IS GREEN 30857, THE DEFENDER 4610, THE GREAT LIE 32102, THE HARD WAY 33948, THE LETTER 15492, THE MASK OF DIMITRIOS 23084, THE PAINTED VEIL 12160, THE PRIVATE LIVES OF ELIZABETH AND ESSEX 279, THE VERDICT 39634, THE VIRGIN QUEEN 36275, THE WAY AHEAD 6138, THE WOLF MAN 16460, THE YOUNG PHILADELPHIANS 873, THEY MADE ME A CRIMINAL 14471, THIS HAPPY BREED 18596, THREE ON A MATCH 35615, TRACKS 31737, VINCENT SHERMAN 40060, WALTER ABEL 30597, WATCH ON THE RHINE 37859, WE DON'T LIVE HERE ANYMORE 29044, WHERE LOVE HAS GONE 26049, WHITE BANNERS 11934, WILSON src, edge_attr, dst 26163, has_genre, 36212 26163, starred_actors, 9367 6139, has_genre, 36212 6139, starred_actors, 9367 22709, has_genre, 36212 22709, has_tags, 9367 22709, starred_actors, 9367 4617, has_genre, 36212 4617, starred_actors, 9367 26158, has_genre, 36212 26158, starred_actors, 9367 37608, has_genre, 36212 11929, has_genre, 36212 11929, has_tags, 21072 11929, has_tags, 36212 11929, starred_actors, 21072 1968, has_genre, 36212 1968, release_year, 18656 19193, has_genre, 36212 19193, starred_actors, 9367 37778, has_genre, 36212 37778, has_tags, 9367 37778, starred_actors, 9367 20161, has_genre, 36212 20161, starred_actors, 9367 20161, starred_actors, 21072 18074, has_genre, 36212 18074, release_year, 18656 18210, has_genre, 36212 18210, starred_actors, 21072 39145, has_genre, 36212 39145, starred_actors, 40060 25033, has_genre, 36212 25033, release_year, 18656 35248, directed_by, 31737 35248, has_genre, 36212 35248, has_tags, 31737 3259, has_genre, 36212 3259, release_year, 18656 34341, has_genre, 36212 34341, starred_actors, 9367 29848, has_genre, 36212 29848, has_tags, 9367 29848, starred_actors, 9367 18688, has_genre, 36212 18688, has_tags, 9367 18688, starred_actors, 9367 10202, has_genre, 36212 10202, starred_actors, 21072 37704, directed_by, 31737 37704, has_genre, 36212 37704, has_tags, 31737 37704, release_year, 18656 37704, starred_actors, 9367 37704, starred_actors, 21072 37704, starred_actors, 8612 37704, starred_actors, 40060 26086, has_genre, 36212 26086, has_tags, 21072 26086, has_tags, 36212 26086, starred_actors, 21072 36406, has_genre, 36212 36406, release_year, 18656 18389, has_genre, 36212 18389, has_tags, 9367 18389, has_tags, 21072 18389, starred_actors, 9367 18389, starred_actors, 21072 4435, has_genre, 36212 4435, has_tags, 9367 4435, starred_actors, 9367 18256, directed_by, 31737 18256, has_genre, 36212 18256, has_tags, 9367 18256, has_tags, 31737 18256, starred_actors, 9367 9090, directed_by, 19209 9090, has_tags, 19209 9090, release_year, 2133 24415, release_year, 2133 24415, starred_actors, 26372 4504, directed_by, 19209 4504, starred_actors, 26366 10358, has_genre, 36212 10358, starred_actors, 9367 15199, has_genre, 36212 15199, starred_actors, 9367 31280, has_genre, 36212 31280, starred_actors, 9367 14219, has_genre, 36212 14219, release_year, 18656 39333, has_genre, 36212 39333, starred_actors, 21072 32516, has_genre, 36212 32516, starred_actors, 9367 30857, release_year, 37484 30857, starred_actors, 26372 4610, has_genre, 36212 4610, starred_actors, 9367 32102, directed_by, 31737 32102, has_genre, 36212 32102, has_tags, 31737 33948, has_genre, 36212 33948, has_tags, 9367 33948, starred_actors, 9367 15492, has_genre, 36212 15492, release_year, 18656 23084, directed_by, 19209 23084, has_genre, 36212 23084, has_tags, 26366 23084, has_tags, 19209 12160, has_genre, 36212 12160, has_tags, 9367 12160, starred_actors, 9367 279, has_genre, 36212 279, starred_actors, 8612 39634, has_genre, 36212 39634, starred_actors, 9367 36275, has_genre, 36212 36275, release_year, 18656 6138, has_genre, 36212 6138, starred_actors, 21072 16460, directed_by, 31737 16460, has_genre, 36212 16460, has_tags, 31737 873, has_genre, 36212 873, starred_actors, 21072 14471, has_genre, 36212 14471, release_year, 18656 18596, has_genre, 36212 18596, has_tags, 9367 35615, directed_by, 19209 35615, has_genre, 36212 35615, has_tags, 37608 35615, has_tags, 19209 30597, has_genre, 36212 30597, starred_actors, 9367 37859, directed_by, 19209 37859, has_genre, 36212 37859, release_year, 37484 29044, has_genre, 36212 29044, starred_actors, 9367 26049, has_genre, 36212 26049, starred_actors, 21072 11934, has_genre, 36212 11934, release_year, 18656 Question: In what context are JERRY SPRINGER, JOHN CURRAN, and MR. SKEFFINGTON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JERRY SPRINGER", "JOHN CURRAN", "MR. SKEFFINGTON" ], "valid_edges": [ [ "20,000 YEARS IN SING SING", "has_genre", "DRAMA" ], [ "20,000 YEARS IN SING SING", "starred_actors", "BETTE DAVIS" ], [ "A STOLEN LIFE", "has_genre", "DRAMA" ], [ "A STOLEN LIFE", "starred_actors", "BETTE DAVIS" ], [ "ALL ABOUT EVE", "has_genre", "DRAMA" ], [ "ALL ABOUT EVE", "has_tags", "BETTE DAVIS" ], [ "ALL ABOUT EVE", "starred_actors", "BETTE DAVIS" ], [ "ALL THIS, AND HEAVEN TOO", "has_genre", "DRAMA" ], [ "ALL THIS, AND HEAVEN TOO", "starred_actors", "BETTE DAVIS" ], [ "ANOTHER MAN'S POISON", "has_genre", "DRAMA" ], [ "ANOTHER MAN'S POISON", "starred_actors", "BETTE DAVIS" ], [ "AUSTRALIA", "has_genre", "DRAMA" ], [ "CASABLANCA", "has_genre", "DRAMA" ], [ "CASABLANCA", "has_tags", "CLAUDE RAINS" ], [ "CASABLANCA", "has_tags", "DRAMA" ], [ "CASABLANCA", "starred_actors", "CLAUDE RAINS" ], [ "COBRA WOMAN", "has_genre", "DRAMA" ], [ "COBRA WOMAN", "release_year", "1944" ], [ "DANGEROUS", "has_genre", "DRAMA" ], [ "DANGEROUS", "starred_actors", "BETTE DAVIS" ], [ "DARK VICTORY", "has_genre", "DRAMA" ], [ "DARK VICTORY", "has_tags", "BETTE DAVIS" ], [ "DARK VICTORY", "starred_actors", "BETTE DAVIS" ], [ "DECEPTION", "has_genre", "DRAMA" ], [ "DECEPTION", "starred_actors", "BETTE DAVIS" ], [ "DECEPTION", "starred_actors", "CLAUDE RAINS" ], [ "DRAGON SEED", "has_genre", "DRAMA" ], [ "DRAGON SEED", "release_year", "1944" ], [ "FOUR DAUGHTERS", "has_genre", "DRAMA" ], [ "FOUR DAUGHTERS", "starred_actors", "CLAUDE RAINS" ], [ "FURY", "has_genre", "DRAMA" ], [ "FURY", "starred_actors", "WALTER ABEL" ], [ "GOING MY WAY", "has_genre", "DRAMA" ], [ "GOING MY WAY", "release_year", "1944" ], [ "HARRIET CRAIG", "directed_by", "VINCENT SHERMAN" ], [ "HARRIET CRAIG", "has_genre", "DRAMA" ], [ "HARRIET CRAIG", "has_tags", "VINCENT SHERMAN" ], [ "I'LL BE SEEING YOU", "has_genre", "DRAMA" ], [ "I'LL BE SEEING YOU", "release_year", "1944" ], [ "IN THIS OUR LIFE", "has_genre", "DRAMA" ], [ "IN THIS OUR LIFE", "starred_actors", "BETTE DAVIS" ], [ "JEZEBEL", "has_genre", "DRAMA" ], [ "JEZEBEL", "has_tags", "BETTE DAVIS" ], [ "JEZEBEL", "starred_actors", "BETTE DAVIS" ], [ "MARKED WOMAN", "has_genre", "DRAMA" ], [ "MARKED WOMAN", "has_tags", "BETTE DAVIS" ], [ "MARKED WOMAN", "starred_actors", "BETTE DAVIS" ], [ "MOONTIDE", "has_genre", "DRAMA" ], [ "MOONTIDE", "starred_actors", "CLAUDE RAINS" ], [ "MR. SKEFFINGTON", "directed_by", "VINCENT SHERMAN" ], [ "MR. SKEFFINGTON", "has_genre", "DRAMA" ], [ "MR. SKEFFINGTON", "has_tags", "VINCENT SHERMAN" ], [ "MR. SKEFFINGTON", "release_year", "1944" ], [ "MR. SKEFFINGTON", "starred_actors", "BETTE DAVIS" ], [ "MR. SKEFFINGTON", "starred_actors", "CLAUDE RAINS" ], [ "MR. SKEFFINGTON", "starred_actors", "GEORGE COULOURIS" ], [ "MR. SKEFFINGTON", "starred_actors", "WALTER ABEL" ], [ "MR. SMITH GOES TO WASHINGTON", "has_genre", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "CLAUDE RAINS" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "CLAUDE RAINS" ], [ "MRS. PARKINGTON", "has_genre", "DRAMA" ], [ "MRS. PARKINGTON", "release_year", "1944" ], [ "NOW, VOYAGER", "has_genre", "DRAMA" ], [ "NOW, VOYAGER", "has_tags", "BETTE DAVIS" ], [ "NOW, VOYAGER", "has_tags", "CLAUDE RAINS" ], [ "NOW, VOYAGER", "starred_actors", "BETTE DAVIS" ], [ "NOW, VOYAGER", "starred_actors", "CLAUDE RAINS" ], [ "OF HUMAN BONDAGE", "has_genre", "DRAMA" ], [ "OF HUMAN BONDAGE", "has_tags", "BETTE DAVIS" ], [ "OF HUMAN BONDAGE", "starred_actors", "BETTE DAVIS" ], [ "OLD ACQUAINTANCE", "directed_by", "VINCENT SHERMAN" ], [ "OLD ACQUAINTANCE", "has_genre", "DRAMA" ], [ "OLD ACQUAINTANCE", "has_tags", "BETTE DAVIS" ], [ "OLD ACQUAINTANCE", "has_tags", "VINCENT SHERMAN" ], [ "OLD ACQUAINTANCE", "starred_actors", "BETTE DAVIS" ], [ "PRAISE", "directed_by", "JOHN CURRAN" ], [ "PRAISE", "has_tags", "JOHN CURRAN" ], [ "PRAISE", "release_year", "1998" ], [ "RINGMASTER", "release_year", "1998" ], [ "RINGMASTER", "starred_actors", "JERRY SPRINGER" ], [ "STONE", "directed_by", "JOHN CURRAN" ], [ "STONE", "starred_actors", "EDWARD NORTON" ], [ "STORM CENTER", "has_genre", "DRAMA" ], [ "STORM CENTER", "starred_actors", "BETTE DAVIS" ], [ "THE CABIN IN THE COTTON", "has_genre", "DRAMA" ], [ "THE CABIN IN THE COTTON", "starred_actors", "BETTE DAVIS" ], [ "THE CATERED AFFAIR", "has_genre", "DRAMA" ], [ "THE CATERED AFFAIR", "starred_actors", "BETTE DAVIS" ], [ "THE CHILDREN ARE WATCHING US", "has_genre", "DRAMA" ], [ "THE CHILDREN ARE WATCHING US", "release_year", "1944" ], [ "THE CLAIRVOYANT", "has_genre", "DRAMA" ], [ "THE CLAIRVOYANT", "starred_actors", "CLAUDE RAINS" ], [ "THE CORN IS GREEN", "has_genre", "DRAMA" ], [ "THE CORN IS GREEN", "starred_actors", "BETTE DAVIS" ], [ "THE DEFENDER", "release_year", "2004" ], [ "THE DEFENDER", "starred_actors", "JERRY SPRINGER" ], [ "THE GREAT LIE", "has_genre", "DRAMA" ], [ "THE GREAT LIE", "starred_actors", "BETTE DAVIS" ], [ "THE HARD WAY", "directed_by", "VINCENT SHERMAN" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_tags", "VINCENT SHERMAN" ], [ "THE LETTER", "has_genre", "DRAMA" ], [ "THE LETTER", "has_tags", "BETTE DAVIS" ], [ "THE LETTER", "starred_actors", "BETTE DAVIS" ], [ "THE MASK OF DIMITRIOS", "has_genre", "DRAMA" ], [ "THE MASK OF DIMITRIOS", "release_year", "1944" ], [ "THE PAINTED VEIL", "directed_by", "JOHN CURRAN" ], [ "THE PAINTED VEIL", "has_genre", "DRAMA" ], [ "THE PAINTED VEIL", "has_tags", "EDWARD NORTON" ], [ "THE PAINTED VEIL", "has_tags", "JOHN CURRAN" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_genre", "DRAMA" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_tags", "BETTE DAVIS" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "starred_actors", "BETTE DAVIS" ], [ "THE VERDICT", "has_genre", "DRAMA" ], [ "THE VERDICT", "starred_actors", "GEORGE COULOURIS" ], [ "THE VIRGIN QUEEN", "has_genre", "DRAMA" ], [ "THE VIRGIN QUEEN", "starred_actors", "BETTE DAVIS" ], [ "THE WAY AHEAD", "has_genre", "DRAMA" ], [ "THE WAY AHEAD", "release_year", "1944" ], [ "THE WOLF MAN", "has_genre", "DRAMA" ], [ "THE WOLF MAN", "starred_actors", "CLAUDE RAINS" ], [ "THE YOUNG PHILADELPHIANS", "directed_by", "VINCENT SHERMAN" ], [ "THE YOUNG PHILADELPHIANS", "has_genre", "DRAMA" ], [ "THE YOUNG PHILADELPHIANS", "has_tags", "VINCENT SHERMAN" ], [ "THEY MADE ME A CRIMINAL", "has_genre", "DRAMA" ], [ "THEY MADE ME A CRIMINAL", "starred_actors", "CLAUDE RAINS" ], [ "THIS HAPPY BREED", "has_genre", "DRAMA" ], [ "THIS HAPPY BREED", "release_year", "1944" ], [ "THREE ON A MATCH", "has_genre", "DRAMA" ], [ "THREE ON A MATCH", "has_tags", "BETTE DAVIS" ], [ "TRACKS", "directed_by", "JOHN CURRAN" ], [ "TRACKS", "has_genre", "DRAMA" ], [ "TRACKS", "has_tags", "AUSTRALIA" ], [ "TRACKS", "has_tags", "JOHN CURRAN" ], [ "WATCH ON THE RHINE", "has_genre", "DRAMA" ], [ "WATCH ON THE RHINE", "starred_actors", "BETTE DAVIS" ], [ "WE DON'T LIVE HERE ANYMORE", "directed_by", "JOHN CURRAN" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHERE LOVE HAS GONE", "has_genre", "DRAMA" ], [ "WHERE LOVE HAS GONE", "starred_actors", "BETTE DAVIS" ], [ "WHITE BANNERS", "has_genre", "DRAMA" ], [ "WHITE BANNERS", "starred_actors", "CLAUDE RAINS" ], [ "WILSON", "has_genre", "DRAMA" ], [ "WILSON", "release_year", "1944" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 37987, A ROOM WITH A VIEW 6594, AGNES OF GOD 23412, ALAMO BAY 30265, BRAZIL 3757, COLONEL REDL 25285, COME AND SEE 31143, DANCE WITH A STRANGER 6806, DEATH OF A SALESMAN 2890, DESERT HEARTS 2382, DESPERATELY SEEKING SUSAN 36212, DRAMA 28373, DREAMCHILD 30833, DÉJÀ VU 21621, ENEMY MINE 27266, FANDANGO 33902, FOOL FOR LOVE 35540, HEAVEN HELP US 33488, INSIGNIFICANCE 33821, KING DAVID 39574, KISS OF THE SPIDER WOMAN 39046, MASK 125, MY BEAUTIFUL LAUNDRETTE 31562, MY LIFE AS A DOG 34938, OUT OF AFRICA 24355, PERFECT 17206, PLENTY 29620, POLICE 27191, RENDEZ-VOUS 10832, REVOLUTION 6016, SEANN WILLIAM SCOTT 3856, SMOOTH TALK 39270, SUBWAY 15048, THAT WAS THEN... THIS IS NOW 6439, THE AVIATOR 17931, THE BREAKFAST CLUB 6882, THE COLOR PURPLE 4802, THE OFFICIAL STORY 18926, THE RUNDOWN 2986, THE YEAR MY VOICE BROKE 18355, TUFF TURF 37279, TURTLE DIARY 12294, VAGABOND 33060, VISION QUEST 30879, WETHERBY 17271, WHEN FATHER WAS AWAY ON BUSINESS 28023, WHITE NIGHTS 5888, YEAR OF THE DRAGON 3398, ZONE TROOPERS src, edge_attr, dst 37987, has_genre, 36212 37987, release_year, 38097 6594, has_genre, 36212 6594, has_tags, 36212 6594, release_year, 38097 23412, has_genre, 36212 23412, release_year, 38097 30265, release_year, 38097 3757, has_genre, 36212 3757, release_year, 38097 25285, has_genre, 36212 25285, release_year, 38097 31143, has_genre, 36212 31143, release_year, 38097 6806, has_genre, 36212 6806, release_year, 38097 2890, has_genre, 36212 2890, release_year, 38097 2382, has_genre, 36212 2382, release_year, 38097 28373, has_genre, 36212 28373, release_year, 38097 30833, has_genre, 36212 30833, release_year, 38097 21621, has_genre, 36212 21621, release_year, 38097 27266, has_genre, 36212 27266, release_year, 38097 33902, has_genre, 36212 33902, release_year, 38097 35540, has_genre, 36212 35540, release_year, 38097 33488, has_genre, 36212 33488, release_year, 38097 33821, has_genre, 36212 33821, release_year, 38097 39574, has_genre, 36212 39574, release_year, 38097 39046, has_genre, 36212 39046, release_year, 38097 125, has_genre, 36212 125, release_year, 38097 31562, has_genre, 36212 31562, release_year, 38097 34938, has_genre, 36212 34938, has_tags, 36212 34938, release_year, 38097 24355, has_genre, 36212 24355, release_year, 38097 17206, has_genre, 36212 17206, release_year, 38097 29620, has_genre, 36212 29620, release_year, 38097 27191, has_genre, 36212 27191, release_year, 38097 10832, has_genre, 36212 10832, release_year, 38097 3856, has_genre, 36212 3856, release_year, 38097 39270, has_genre, 36212 39270, release_year, 38097 15048, has_genre, 36212 15048, release_year, 38097 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 38097 17931, has_genre, 36212 17931, has_tags, 36212 17931, release_year, 38097 6882, has_genre, 36212 6882, release_year, 38097 4802, has_genre, 36212 4802, release_year, 38097 18926, has_tags, 30265 18926, has_tags, 6016 18926, starred_actors, 6016 2986, has_genre, 36212 18355, has_genre, 36212 18355, release_year, 38097 37279, has_genre, 36212 37279, release_year, 38097 12294, has_genre, 36212 12294, release_year, 38097 33060, has_genre, 36212 33060, release_year, 38097 30879, has_genre, 36212 30879, release_year, 38097 17271, has_genre, 36212 17271, release_year, 38097 28023, has_genre, 36212 28023, release_year, 38097 5888, has_genre, 36212 5888, release_year, 38097 3398, release_year, 38097 Question: How are SEANN WILLIAM SCOTT, THE YEAR MY VOICE BROKE, and ZONE TROOPERS related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "SEANN WILLIAM SCOTT", "THE YEAR MY VOICE BROKE", "ZONE TROOPERS" ], "valid_edges": [ [ "A ROOM WITH A VIEW", "has_genre", "DRAMA" ], [ "A ROOM WITH A VIEW", "release_year", "1985" ], [ "AGNES OF GOD", "has_genre", "DRAMA" ], [ "AGNES OF GOD", "has_tags", "DRAMA" ], [ "AGNES OF GOD", "release_year", "1985" ], [ "ALAMO BAY", "has_genre", "DRAMA" ], [ "ALAMO BAY", "release_year", "1985" ], [ "BRAZIL", "release_year", "1985" ], [ "COLONEL REDL", "has_genre", "DRAMA" ], [ "COLONEL REDL", "release_year", "1985" ], [ "COME AND SEE", "has_genre", "DRAMA" ], [ "COME AND SEE", "release_year", "1985" ], [ "DANCE WITH A STRANGER", "has_genre", "DRAMA" ], [ "DANCE WITH A STRANGER", "release_year", "1985" ], [ "DEATH OF A SALESMAN", "has_genre", "DRAMA" ], [ "DEATH OF A SALESMAN", "release_year", "1985" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "release_year", "1985" ], [ "DESPERATELY SEEKING SUSAN", "has_genre", "DRAMA" ], [ "DESPERATELY SEEKING SUSAN", "release_year", "1985" ], [ "DREAMCHILD", "has_genre", "DRAMA" ], [ "DREAMCHILD", "release_year", "1985" ], [ "DÉJÀ VU", "has_genre", "DRAMA" ], [ "DÉJÀ VU", "release_year", "1985" ], [ "ENEMY MINE", "has_genre", "DRAMA" ], [ "ENEMY MINE", "release_year", "1985" ], [ "FANDANGO", "has_genre", "DRAMA" ], [ "FANDANGO", "release_year", "1985" ], [ "FOOL FOR LOVE", "has_genre", "DRAMA" ], [ "FOOL FOR LOVE", "release_year", "1985" ], [ "HEAVEN HELP US", "has_genre", "DRAMA" ], [ "HEAVEN HELP US", "release_year", "1985" ], [ "INSIGNIFICANCE", "has_genre", "DRAMA" ], [ "INSIGNIFICANCE", "release_year", "1985" ], [ "KING DAVID", "has_genre", "DRAMA" ], [ "KING DAVID", "release_year", "1985" ], [ "KISS OF THE SPIDER WOMAN", "has_genre", "DRAMA" ], [ "KISS OF THE SPIDER WOMAN", "release_year", "1985" ], [ "MASK", "has_genre", "DRAMA" ], [ "MASK", "release_year", "1985" ], [ "MY BEAUTIFUL LAUNDRETTE", "has_genre", "DRAMA" ], [ "MY BEAUTIFUL LAUNDRETTE", "release_year", "1985" ], [ "MY LIFE AS A DOG", "has_genre", "DRAMA" ], [ "MY LIFE AS A DOG", "release_year", "1985" ], [ "OUT OF AFRICA", "has_genre", "DRAMA" ], [ "OUT OF AFRICA", "has_tags", "DRAMA" ], [ "OUT OF AFRICA", "release_year", "1985" ], [ "PERFECT", "has_genre", "DRAMA" ], [ "PERFECT", "release_year", "1985" ], [ "PLENTY", "has_genre", "DRAMA" ], [ "PLENTY", "release_year", "1985" ], [ "POLICE", "has_genre", "DRAMA" ], [ "POLICE", "release_year", "1985" ], [ "RENDEZ-VOUS", "has_genre", "DRAMA" ], [ "RENDEZ-VOUS", "release_year", "1985" ], [ "REVOLUTION", "has_genre", "DRAMA" ], [ "REVOLUTION", "release_year", "1985" ], [ "SMOOTH TALK", "has_genre", "DRAMA" ], [ "SMOOTH TALK", "release_year", "1985" ], [ "SUBWAY", "has_genre", "DRAMA" ], [ "SUBWAY", "release_year", "1985" ], [ "THAT WAS THEN... THIS IS NOW", "has_genre", "DRAMA" ], [ "THAT WAS THEN... THIS IS NOW", "release_year", "1985" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "1985" ], [ "THE BREAKFAST CLUB", "has_genre", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "DRAMA" ], [ "THE BREAKFAST CLUB", "release_year", "1985" ], [ "THE COLOR PURPLE", "has_genre", "DRAMA" ], [ "THE COLOR PURPLE", "release_year", "1985" ], [ "THE OFFICIAL STORY", "has_genre", "DRAMA" ], [ "THE OFFICIAL STORY", "release_year", "1985" ], [ "THE RUNDOWN", "has_tags", "BRAZIL" ], [ "THE RUNDOWN", "has_tags", "SEANN WILLIAM SCOTT" ], [ "THE RUNDOWN", "starred_actors", "SEANN WILLIAM SCOTT" ], [ "THE YEAR MY VOICE BROKE", "has_genre", "DRAMA" ], [ "TUFF TURF", "has_genre", "DRAMA" ], [ "TUFF TURF", "release_year", "1985" ], [ "TURTLE DIARY", "has_genre", "DRAMA" ], [ "TURTLE DIARY", "release_year", "1985" ], [ "VAGABOND", "has_genre", "DRAMA" ], [ "VAGABOND", "release_year", "1985" ], [ "VISION QUEST", "has_genre", "DRAMA" ], [ "VISION QUEST", "release_year", "1985" ], [ "WETHERBY", "has_genre", "DRAMA" ], [ "WETHERBY", "release_year", "1985" ], [ "WHEN FATHER WAS AWAY ON BUSINESS", "has_genre", "DRAMA" ], [ "WHEN FATHER WAS AWAY ON BUSINESS", "release_year", "1985" ], [ "WHITE NIGHTS", "has_genre", "DRAMA" ], [ "WHITE NIGHTS", "release_year", "1985" ], [ "YEAR OF THE DRAGON", "has_genre", "DRAMA" ], [ "YEAR OF THE DRAGON", "release_year", "1985" ], [ "ZONE TROOPERS", "release_year", "1985" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 24525, 1984 21004, A CRY IN THE NIGHT 21151, AGAINST ALL ODDS 31137, ALEX KARRAS 30463, COMEDY 15253, COMIC BOOK 36212, DRAMA 12359, KICK-ASS 25894, KICK-ASS 2 20996, MARK MILLAR 36867, PAPER LION 2980, SUPERHERO 12438, WRITTEN ON THE WIND src, edge_attr, dst 24525, release_year, 9177 21004, has_genre, 36212 21004, release_year, 9177 21151, release_year, 24525 21151, starred_actors, 31137 12359, has_genre, 30463 12359, has_tags, 15253 12359, has_tags, 2980 12359, written_by, 20996 25894, has_genre, 30463 25894, has_tags, 15253 25894, has_tags, 2980 25894, written_by, 20996 36867, has_genre, 30463 36867, starred_actors, 31137 12438, has_genre, 36212 12438, release_year, 9177 Question: In what context are ALEX KARRAS, MARK MILLAR, and WRITTEN ON THE WIND connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALEX KARRAS", "MARK MILLAR", "WRITTEN ON THE WIND" ], "valid_edges": [ [ "1984", "release_year", "1956" ], [ "A CRY IN THE NIGHT", "has_genre", "DRAMA" ], [ "A CRY IN THE NIGHT", "release_year", "1956" ], [ "AGAINST ALL ODDS", "release_year", "1984" ], [ "AGAINST ALL ODDS", "starred_actors", "ALEX KARRAS" ], [ "KICK-ASS", "has_genre", "COMEDY" ], [ "KICK-ASS", "has_tags", "COMIC BOOK" ], [ "KICK-ASS", "has_tags", "SUPERHERO" ], [ "KICK-ASS", "written_by", "MARK MILLAR" ], [ "KICK-ASS 2", "has_genre", "COMEDY" ], [ "KICK-ASS 2", "has_tags", "COMIC BOOK" ], [ "KICK-ASS 2", "has_tags", "SUPERHERO" ], [ "KICK-ASS 2", "written_by", "MARK MILLAR" ], [ "PAPER LION", "has_genre", "COMEDY" ], [ "PAPER LION", "starred_actors", "ALEX KARRAS" ], [ "WRITTEN ON THE WIND", "has_genre", "DRAMA" ], [ "WRITTEN ON THE WIND", "release_year", "1956" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1097, 2003 27261, 2009 12914, A DANGEROUS MAN 11454, AGAINST THE DARK 1822, AWAY WE GO 14839, BELLY OF THE BEAST 2856, BROTHERS 34645, CROSSING OVER 6052, DRIVEN TO KILL 30179, I CAPTURE THE CASTLE 34072, I'M NOT SCARED 16560, INGLOURIOUS BASTERDS 11898, JON GUNN 19474, KEONI WAXMAN 27212, KONTROLL 25587, LIKE DANDELION DUST 15814, LOST IN TRANSLATION 13672, LOVE ACTUALLY 3876, MELVIN GOES TO DINNER 5641, MONSIEUR IBRAHIM 12944, MY LIFE WITHOUT ME 21889, OLD SCHOOL 32954, OLDBOY 9357, OUT FOR A KILL 13081, R 14589, S. DARKO 3416, SARABAND 38596, SPREAD 11177, STEVEN SEAGAL 38965, THE BARBARIAN INVASIONS 12623, THE BEST OF YOUTH 39110, THE FOREIGNER 21338, THE GIRL WHO PLAYED WITH FIRE 7240, THE GIRL WITH THE DRAGON TATTOO 29952, THE INTERNATIONAL 5567, THE KEEPER 28024, THE MEN WHO STARE AT GOATS 37148, THE SECRET IN THEIR EYES 38108, THE STATION AGENT 22820, THE UNITED STATES OF LELAND 26758, THICK AS THIEVES 1411, THIRTEEN 25406, UP IN THE AIR 22588, WANTED 20465, WATCHMEN src, edge_attr, dst 12914, directed_by, 19474 12914, release_year, 27261 12914, starred_actors, 11177 12914, written_by, 19474 11454, has_tags, 11177 11454, release_year, 27261 11454, starred_actors, 11177 1822, has_tags, 13081 1822, release_year, 27261 14839, release_year, 1097 14839, starred_actors, 11177 2856, has_tags, 13081 2856, release_year, 27261 34645, has_tags, 13081 34645, release_year, 27261 6052, release_year, 27261 6052, starred_actors, 11177 30179, has_tags, 13081 30179, release_year, 1097 34072, has_tags, 13081 34072, release_year, 1097 16560, has_tags, 13081 16560, release_year, 27261 27212, has_tags, 13081 27212, release_year, 1097 25587, directed_by, 11898 25587, release_year, 27261 15814, has_tags, 13081 15814, release_year, 1097 13672, has_tags, 13081 13672, release_year, 1097 3876, has_tags, 13081 3876, release_year, 1097 5641, has_tags, 13081 5641, release_year, 1097 12944, has_tags, 13081 12944, release_year, 1097 21889, has_tags, 13081 21889, release_year, 1097 32954, has_tags, 13081 32954, release_year, 1097 9357, release_year, 1097 9357, starred_actors, 11177 14589, has_tags, 13081 14589, release_year, 27261 3416, has_tags, 13081 3416, release_year, 1097 38596, has_tags, 13081 38596, release_year, 27261 38965, has_tags, 13081 38965, release_year, 1097 12623, has_tags, 13081 12623, release_year, 1097 39110, release_year, 1097 39110, starred_actors, 11177 21338, has_tags, 13081 21338, release_year, 27261 7240, has_tags, 13081 7240, release_year, 27261 29952, has_tags, 13081 29952, release_year, 27261 5567, directed_by, 19474 5567, release_year, 27261 5567, starred_actors, 11177 28024, has_tags, 13081 28024, release_year, 27261 37148, has_tags, 13081 37148, release_year, 27261 38108, has_tags, 13081 38108, release_year, 1097 22820, has_tags, 13081 22820, release_year, 1097 26758, has_tags, 13081 26758, release_year, 27261 1411, has_tags, 13081 1411, release_year, 1097 25406, has_tags, 13081 25406, release_year, 27261 22588, has_tags, 13081 22588, release_year, 27261 20465, has_tags, 13081 20465, release_year, 27261 Question: In what context are A DANGEROUS MAN, JON GUNN, and THE STATION AGENT connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A DANGEROUS MAN", "JON GUNN", "THE STATION AGENT" ], "valid_edges": [ [ "A DANGEROUS MAN", "directed_by", "KEONI WAXMAN" ], [ "A DANGEROUS MAN", "release_year", "2009" ], [ "A DANGEROUS MAN", "starred_actors", "STEVEN SEAGAL" ], [ "A DANGEROUS MAN", "written_by", "KEONI WAXMAN" ], [ "AGAINST THE DARK", "has_tags", "STEVEN SEAGAL" ], [ "AGAINST THE DARK", "release_year", "2009" ], [ "AGAINST THE DARK", "starred_actors", "STEVEN SEAGAL" ], [ "AWAY WE GO", "has_tags", "R" ], [ "AWAY WE GO", "release_year", "2009" ], [ "BELLY OF THE BEAST", "release_year", "2003" ], [ "BELLY OF THE BEAST", "starred_actors", "STEVEN SEAGAL" ], [ "BROTHERS", "has_tags", "R" ], [ "BROTHERS", "release_year", "2009" ], [ "CROSSING OVER", "has_tags", "R" ], [ "CROSSING OVER", "release_year", "2009" ], [ "DRIVEN TO KILL", "release_year", "2009" ], [ "DRIVEN TO KILL", "starred_actors", "STEVEN SEAGAL" ], [ "I CAPTURE THE CASTLE", "has_tags", "R" ], [ "I CAPTURE THE CASTLE", "release_year", "2003" ], [ "I'M NOT SCARED", "has_tags", "R" ], [ "I'M NOT SCARED", "release_year", "2003" ], [ "INGLOURIOUS BASTERDS", "has_tags", "R" ], [ "INGLOURIOUS BASTERDS", "release_year", "2009" ], [ "KONTROLL", "has_tags", "R" ], [ "KONTROLL", "release_year", "2003" ], [ "LIKE DANDELION DUST", "directed_by", "JON GUNN" ], [ "LIKE DANDELION DUST", "release_year", "2009" ], [ "LOST IN TRANSLATION", "has_tags", "R" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE ACTUALLY", "has_tags", "R" ], [ "LOVE ACTUALLY", "release_year", "2003" ], [ "MELVIN GOES TO DINNER", "has_tags", "R" ], [ "MELVIN GOES TO DINNER", "release_year", "2003" ], [ "MONSIEUR IBRAHIM", "has_tags", "R" ], [ "MONSIEUR IBRAHIM", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_tags", "R" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "OLD SCHOOL", "has_tags", "R" ], [ "OLD SCHOOL", "release_year", "2003" ], [ "OLDBOY", "has_tags", "R" ], [ "OLDBOY", "release_year", "2003" ], [ "OUT FOR A KILL", "release_year", "2003" ], [ "OUT FOR A KILL", "starred_actors", "STEVEN SEAGAL" ], [ "S. DARKO", "has_tags", "R" ], [ "S. DARKO", "release_year", "2009" ], [ "SARABAND", "has_tags", "R" ], [ "SARABAND", "release_year", "2003" ], [ "SPREAD", "has_tags", "R" ], [ "SPREAD", "release_year", "2009" ], [ "THE BARBARIAN INVASIONS", "has_tags", "R" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BEST OF YOUTH", "has_tags", "R" ], [ "THE BEST OF YOUTH", "release_year", "2003" ], [ "THE FOREIGNER", "release_year", "2003" ], [ "THE FOREIGNER", "starred_actors", "STEVEN SEAGAL" ], [ "THE GIRL WHO PLAYED WITH FIRE", "has_tags", "R" ], [ "THE GIRL WHO PLAYED WITH FIRE", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "R" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE INTERNATIONAL", "has_tags", "R" ], [ "THE INTERNATIONAL", "release_year", "2009" ], [ "THE KEEPER", "directed_by", "KEONI WAXMAN" ], [ "THE KEEPER", "release_year", "2009" ], [ "THE KEEPER", "starred_actors", "STEVEN SEAGAL" ], [ "THE MEN WHO STARE AT GOATS", "has_tags", "R" ], [ "THE MEN WHO STARE AT GOATS", "release_year", "2009" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE SECRET IN THEIR EYES", "release_year", "2009" ], [ "THE STATION AGENT", "has_tags", "R" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_tags", "R" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THICK AS THIEVES", "has_tags", "R" ], [ "THICK AS THIEVES", "release_year", "2009" ], [ "THIRTEEN", "has_tags", "R" ], [ "THIRTEEN", "release_year", "2003" ], [ "UP IN THE AIR", "has_tags", "R" ], [ "UP IN THE AIR", "release_year", "2009" ], [ "WANTED", "has_tags", "R" ], [ "WANTED", "release_year", "2009" ], [ "WATCHMEN", "has_tags", "R" ], [ "WATCHMEN", "release_year", "2009" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 25611, 4 FOR TEXAS 17505, A LOW DOWN DIRTY SHAME 431, A MAN OF NO IMPORTANCE 36629, A MILLION TO JUAN 39864, A MILLION WAYS TO DIE IN THE WEST 29838, A SIMPLE TWIST OF FATE 10110, A TIME FOR KILLING 7687, ADVANCE TO THE REAR 8841, AIR AMERICA 8837, AIRHEADS 39641, ALONG CAME JONES 27410, ANGELS IN THE OUTFIELD 24704, ANGIE 35639, BABY'S DAY OUT 23899, BAD COMPANY 1868, BARCELONA 10890, BEVERLY HILLS COP III 29301, BLANK CHECK 24639, BLANKMAN 12492, BLAZING SADDLES 34318, CABIN BOY 22539, CAR 54, WHERE ARE YOU? 6588, CAT BALLOU 26883, CEMETERY MAN 16350, CHASERS 38333, CHRIS EIGEMAN 14442, CHRISTOPHER ROBBINS 26781, CIMARRON 15585, CITY SLICKERS 35468, CLEAN SLATE 35351, CLERKS 9387, CLIFFORD 30463, COMEDY 18170, COWBOY 21391, CRACKERJACK 10316, DAMSELS IN DISTRESS 25978, DEADLY ADVICE 19009, DEAR HEART 13424, DON'T DRINK THE WATER 31475, DON'T GO NEAR THE WATER 3893, ED WOOD 26709, ERNEST GOES TO SCHOOL 34967, EVIL ROY SLADE 20441, EXIT TO EDEN 24028, FLOUNDERING 22371, FORREST GUMP 6215, FOUR WEDDINGS AND A FUNERAL 36927, FROM BEIJING WITH LOVE 34775, GETTING EVEN WITH DAD 9142, GETTING IN 25442, GLENN FORD 25721, GOIN' SOUTH 10519, GOLD RAIDERS 5585, GREEDY 34489, GUARDING TESS 25670, HAIL CAESAR 35856, HEARTS OF THE WEST 20990, HOLY MATRIMONY 34412, I LIKE IT LIKE THAT 13163, I LOVE TROUBLE 18096, I.Q. 24832, IN THE ARMY NOW 14341, IT COULD HAPPEN TO YOU 39987, IT RUNS IN THE FAMILY 37202, IT'S PAT 8819, JUBAL 29404, JUNIOR 14878, KABHI HAAN KABHI NAA 18648, LEPRECHAUN 2 19862, LIGHTNING JACK 33575, LITTLE BIG MAN 16780, LITTLE GIANTS 6417, LUST FOR GOLD 25283, MAVERICK 7495, MCLINTOCK! 12620, MILK MONEY 17491, MIRA SORVINO 12371, MIXED NUTS 9817, MONKEY TROUBLE 25796, MURIEL'S WEDDING 28963, MY GIRL 2 24611, MY LITTLE CHICKADEE 4398, NOBODY'S FOOL 32358, NORTH 36883, ONLY YOU 24732, PCU 30595, POCKETFUL OF MIRACLES 11042, PRINCESS CARABOO 26174, PULP FICTION 22395, RADIOLAND MURDERS 34930, RANCHO DELUXE 18664, RANGO 26180, REALITY BITES 25577, RENAISSANCE MAN 14913, ROMY AND MICHELE'S HIGH SCHOOL REUNION 11370, RUSTLERS' RHAPSODY 24642, SERIAL MOM 6468, SKIN GAME 1374, SLEEP WITH ME 16907, SON OF PALEFACE 24664, SPAIN 6144, SPANKING THE MONKEY 7010, SPEECHLESS 35026, STAGGERED 38038, STRAIGHT TO HELL 20877, SWIMMING WITH SHARKS 2567, TAMMY AND THE T-REX 15063, TAMPOPO 7585, TEXAS 34235, TEXAS ACROSS THE RIVER 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 30090, THE AIR UP THERE 13685, THE CHASE 7763, THE CHEYENNE SOCIAL CLUB 37288, THE COURTSHIP OF EDDIE'S FATHER 22164, THE COWBOY WAY 18466, THE DESPERADOES 10084, THE FASTEST GUN ALIVE 9215, THE FAVOR 17956, THE FLINTSTONES 28510, THE FRISCO KID 10878, THE HUDSUCKER PROXY 38210, THE INKWELL 9059, THE LAST DAYS OF DISCO 38550, THE LITTLE RASCALS 35340, THE MAN FROM THE ALAMO 23802, THE MASK 32, THE MATING OF MILLIE 29233, THE MONSTER 17513, THE PALEFACE 33982, THE PAPER 26061, THE REF 13917, THE ROAD TO WELLVILLE 17314, THE SANTA CLAUSE 36289, THE SCOUT 33905, THE SEARCH FOR ONE-EYE JIMMY 28829, THE SECRET OF CONVICT LAKE 33083, THE SHAKIEST GUN IN THE WEST 5394, THE SHEEPMAN 4767, THE SUM OF US 14580, THE TREATMENT 37184, THE TRIUMPH OF LOVE 30942, THE VIOLENT MEN 7342, THEY CALL ME TRINITY 16762, THREESOME 18195, TRAPPED IN PARADISE 12860, TRUE LIES 33767, TWIN SITTERS 36026, WESTERN 9006, WHIT STILLMAN 1790, WILD WILD WEST 39623, WITH HONORS 28489, ZINDAGI NA MILEGI DOBARA 33462, ¡THREE AMIGOS! src, edge_attr, dst 25611, has_genre, 30463 25611, has_genre, 36026 17505, has_genre, 30463 17505, release_year, 26257 431, has_genre, 30463 431, release_year, 26257 36629, has_genre, 30463 36629, release_year, 26257 39864, has_genre, 30463 39864, has_genre, 36026 29838, has_genre, 30463 29838, release_year, 26257 10110, has_genre, 36026 10110, starred_actors, 25442 7687, has_genre, 30463 7687, has_genre, 36026 7687, starred_actors, 25442 8841, has_genre, 30463 8841, written_by, 14442 8837, has_genre, 30463 8837, has_tags, 30463 8837, release_year, 26257 39641, has_genre, 30463 39641, has_genre, 36026 27410, has_genre, 30463 27410, release_year, 26257 24704, has_genre, 30463 24704, release_year, 26257 35639, has_genre, 30463 35639, release_year, 26257 23899, has_genre, 30463 23899, has_genre, 36026 1868, directed_by, 9006 1868, has_genre, 30463 1868, has_tags, 1868 1868, has_tags, 24664 1868, has_tags, 9006 1868, release_year, 26257 1868, starred_actors, 38333 1868, starred_actors, 17491 1868, written_by, 9006 10890, has_genre, 30463 10890, has_tags, 30463 10890, release_year, 26257 29301, has_genre, 30463 29301, release_year, 26257 24639, has_genre, 30463 24639, release_year, 26257 12492, has_genre, 30463 12492, has_genre, 36026 12492, has_tags, 30463 12492, has_tags, 36026 34318, has_genre, 30463 34318, release_year, 26257 22539, has_genre, 30463 22539, release_year, 26257 6588, has_genre, 30463 6588, has_genre, 36026 26883, has_genre, 30463 26883, release_year, 26257 16350, has_genre, 30463 16350, release_year, 26257 26781, has_genre, 36026 26781, starred_actors, 25442 15585, has_genre, 30463 15585, has_genre, 36026 35468, has_genre, 30463 35468, release_year, 26257 35351, has_genre, 30463 35351, has_tags, 30463 35351, release_year, 26257 9387, has_genre, 30463 9387, release_year, 26257 18170, has_genre, 36026 18170, starred_actors, 25442 21391, has_genre, 30463 21391, release_year, 26257 10316, directed_by, 9006 10316, has_genre, 30463 10316, has_tags, 9006 10316, written_by, 9006 25978, has_genre, 30463 25978, release_year, 26257 19009, has_genre, 30463 19009, starred_actors, 25442 13424, has_genre, 30463 13424, release_year, 26257 31475, has_genre, 30463 31475, starred_actors, 25442 3893, has_genre, 30463 3893, release_year, 26257 26709, has_genre, 30463 26709, release_year, 26257 34967, has_genre, 30463 34967, has_genre, 36026 20441, has_genre, 30463 20441, release_year, 26257 24028, has_genre, 30463 24028, release_year, 26257 22371, has_tags, 30463 22371, release_year, 26257 6215, has_genre, 30463 6215, has_tags, 30463 6215, release_year, 26257 36927, has_genre, 30463 36927, release_year, 26257 34775, has_genre, 30463 34775, release_year, 26257 9142, has_genre, 30463 9142, release_year, 26257 25721, has_genre, 30463 25721, has_genre, 36026 10519, has_genre, 30463 10519, has_genre, 36026 5585, has_genre, 30463 5585, release_year, 26257 34489, has_genre, 30463 34489, release_year, 26257 25670, has_genre, 30463 25670, release_year, 26257 35856, has_genre, 30463 35856, has_genre, 36026 20990, has_genre, 30463 20990, release_year, 26257 34412, has_genre, 30463 34412, release_year, 26257 13163, has_genre, 30463 13163, release_year, 26257 18096, has_genre, 30463 18096, release_year, 26257 24832, has_genre, 30463 24832, release_year, 26257 14341, has_genre, 30463 14341, has_tags, 30463 14341, release_year, 26257 39987, has_genre, 30463 39987, release_year, 26257 37202, has_genre, 30463 37202, release_year, 26257 8819, has_genre, 36026 8819, starred_actors, 25442 29404, has_genre, 30463 29404, release_year, 26257 14878, has_genre, 30463 14878, release_year, 26257 18648, has_genre, 30463 18648, release_year, 26257 19862, has_genre, 30463 19862, has_genre, 36026 19862, release_year, 26257 33575, has_genre, 30463 33575, has_genre, 36026 16780, has_genre, 30463 16780, release_year, 26257 6417, has_genre, 36026 6417, starred_actors, 25442 25283, has_genre, 30463 25283, has_tags, 30463 25283, has_tags, 36026 25283, release_year, 26257 7495, has_genre, 30463 7495, has_genre, 36026 12620, has_genre, 30463 12620, release_year, 26257 12371, has_genre, 30463 12371, release_year, 26257 9817, has_genre, 30463 9817, release_year, 26257 25796, has_genre, 30463 25796, has_tags, 30463 25796, release_year, 26257 28963, has_genre, 30463 28963, release_year, 26257 24611, has_genre, 30463 24611, has_genre, 36026 4398, has_genre, 30463 4398, release_year, 26257 32358, has_genre, 30463 32358, release_year, 26257 36883, has_genre, 30463 36883, release_year, 26257 24732, has_genre, 30463 24732, release_year, 26257 30595, has_genre, 30463 30595, has_tags, 30463 30595, starred_actors, 25442 11042, has_genre, 30463 11042, release_year, 26257 26174, has_tags, 30463 26174, release_year, 26257 22395, has_genre, 30463 22395, release_year, 26257 34930, has_genre, 30463 34930, has_genre, 36026 18664, has_genre, 30463 18664, has_tags, 36026 26180, has_genre, 30463 26180, release_year, 26257 25577, has_genre, 30463 25577, release_year, 26257 14913, has_genre, 30463 14913, has_tags, 30463 14913, has_tags, 17491 14913, starred_actors, 17491 11370, has_genre, 30463 11370, has_genre, 36026 24642, has_genre, 30463 24642, has_tags, 30463 24642, release_year, 26257 6468, has_genre, 30463 6468, has_genre, 36026 1374, has_genre, 30463 1374, release_year, 26257 16907, has_genre, 30463 16907, has_genre, 36026 6144, has_genre, 30463 6144, release_year, 26257 7010, has_genre, 30463 7010, release_year, 26257 35026, has_genre, 30463 35026, release_year, 26257 38038, has_genre, 30463 38038, has_genre, 36026 20877, has_genre, 30463 20877, release_year, 26257 2567, has_genre, 30463 2567, release_year, 26257 15063, has_genre, 30463 15063, has_genre, 36026 7585, has_genre, 36026 7585, starred_actors, 25442 34235, has_genre, 30463 34235, has_genre, 36026 25270, has_genre, 30463 25270, release_year, 26257 30090, has_genre, 30463 30090, has_tags, 30463 30090, release_year, 26257 13685, has_genre, 30463 13685, release_year, 26257 7763, has_genre, 30463 7763, has_genre, 36026 37288, has_genre, 30463 37288, starred_actors, 25442 22164, has_genre, 30463 22164, release_year, 26257 18466, has_genre, 36026 18466, starred_actors, 25442 10084, has_genre, 36026 10084, starred_actors, 25442 9215, has_genre, 30463 9215, release_year, 26257 17956, has_genre, 30463 17956, has_tags, 30463 17956, release_year, 26257 28510, has_genre, 30463 28510, has_genre, 36026 10878, has_genre, 30463 10878, has_tags, 30463 10878, release_year, 26257 38210, has_genre, 30463 38210, release_year, 26257 9059, directed_by, 9006 9059, has_genre, 30463 9059, has_tags, 9006 9059, written_by, 9006 38550, has_genre, 30463 38550, release_year, 26257 35340, has_genre, 36026 35340, starred_actors, 25442 23802, has_genre, 30463 23802, has_tags, 30463 23802, release_year, 26257 32, has_genre, 30463 32, starred_actors, 25442 29233, has_genre, 30463 29233, has_tags, 30463 29233, release_year, 26257 17513, has_genre, 30463 17513, has_genre, 36026 33982, has_genre, 30463 33982, release_year, 26257 26061, has_genre, 30463 26061, has_tags, 30463 26061, release_year, 26257 13917, has_genre, 30463 13917, release_year, 26257 17314, has_genre, 30463 17314, release_year, 26257 36289, has_genre, 30463 36289, release_year, 26257 33905, has_genre, 30463 33905, release_year, 26257 28829, has_genre, 36026 28829, starred_actors, 25442 33083, has_genre, 30463 33083, has_genre, 36026 33083, has_tags, 36026 5394, has_genre, 36026 5394, starred_actors, 25442 4767, has_genre, 30463 4767, release_year, 26257 14580, has_genre, 30463 14580, starred_actors, 38333 37184, has_genre, 30463 37184, starred_actors, 17491 30942, has_genre, 36026 30942, starred_actors, 25442 7342, has_genre, 30463 7342, has_genre, 36026 16762, has_genre, 30463 16762, has_tags, 30463 16762, release_year, 26257 18195, has_genre, 30463 18195, release_year, 26257 12860, has_genre, 30463 12860, has_tags, 30463 12860, release_year, 26257 33767, has_genre, 30463 33767, release_year, 26257 1790, has_genre, 30463 1790, has_genre, 36026 1790, has_tags, 30463 39623, has_genre, 30463 39623, release_year, 26257 28489, has_genre, 30463 28489, has_tags, 24664 33462, has_genre, 30463 33462, has_genre, 36026 33462, has_tags, 30463 Question: How are BARCELONA, CHRISTOPHER ROBBINS, and COWBOY related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BARCELONA", "CHRISTOPHER ROBBINS", "COWBOY" ], "valid_edges": [ [ "4 FOR TEXAS", "has_genre", "COMEDY" ], [ "4 FOR TEXAS", "has_genre", "WESTERN" ], [ "A LOW DOWN DIRTY SHAME", "has_genre", "COMEDY" ], [ "A LOW DOWN DIRTY SHAME", "release_year", "1994" ], [ "A MAN OF NO IMPORTANCE", "has_genre", "COMEDY" ], [ "A MAN OF NO IMPORTANCE", "release_year", "1994" ], [ "A MILLION TO JUAN", "has_genre", "COMEDY" ], [ "A MILLION TO JUAN", "release_year", "1994" ], [ "A MILLION WAYS TO DIE IN THE WEST", "has_genre", "COMEDY" ], [ "A MILLION WAYS TO DIE IN THE WEST", "has_genre", "WESTERN" ], [ "A SIMPLE TWIST OF FATE", "has_genre", "COMEDY" ], [ "A SIMPLE TWIST OF FATE", "release_year", "1994" ], [ "A TIME FOR KILLING", "has_genre", "WESTERN" ], [ "A TIME FOR KILLING", "starred_actors", "GLENN FORD" ], [ "ADVANCE TO THE REAR", "has_genre", "COMEDY" ], [ "ADVANCE TO THE REAR", "has_genre", "WESTERN" ], [ "ADVANCE TO THE REAR", "starred_actors", "GLENN FORD" ], [ "AIR AMERICA", "has_genre", "COMEDY" ], [ "AIR AMERICA", "written_by", "CHRISTOPHER ROBBINS" ], [ "AIRHEADS", "has_genre", "COMEDY" ], [ "AIRHEADS", "has_tags", "COMEDY" ], [ "AIRHEADS", "release_year", "1994" ], [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "has_genre", "WESTERN" ], [ "ANGELS IN THE OUTFIELD", "has_genre", "COMEDY" ], [ "ANGELS IN THE OUTFIELD", "release_year", "1994" ], [ "ANGIE", "has_genre", "COMEDY" ], [ "ANGIE", "release_year", "1994" ], [ "BABY'S DAY OUT", "has_genre", "COMEDY" ], [ "BABY'S DAY OUT", "release_year", "1994" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "has_genre", "WESTERN" ], [ "BARCELONA", "directed_by", "WHIT STILLMAN" ], [ "BARCELONA", "has_genre", "COMEDY" ], [ "BARCELONA", "has_tags", "BARCELONA" ], [ "BARCELONA", "has_tags", "SPAIN" ], [ "BARCELONA", "has_tags", "WHIT STILLMAN" ], [ "BARCELONA", "release_year", "1994" ], [ "BARCELONA", "starred_actors", "CHRIS EIGEMAN" ], [ "BARCELONA", "starred_actors", "MIRA SORVINO" ], [ "BARCELONA", "written_by", "WHIT STILLMAN" ], [ "BEVERLY HILLS COP III", "has_genre", "COMEDY" ], [ "BEVERLY HILLS COP III", "has_tags", "COMEDY" ], [ "BEVERLY HILLS COP III", "release_year", "1994" ], [ "BLANK CHECK", "has_genre", "COMEDY" ], [ "BLANK CHECK", "release_year", "1994" ], [ "BLANKMAN", "has_genre", "COMEDY" ], [ "BLANKMAN", "release_year", "1994" ], [ "BLAZING SADDLES", "has_genre", "COMEDY" ], [ "BLAZING SADDLES", "has_genre", "WESTERN" ], [ "BLAZING SADDLES", "has_tags", "COMEDY" ], [ "BLAZING SADDLES", "has_tags", "WESTERN" ], [ "CABIN BOY", "has_genre", "COMEDY" ], [ "CABIN BOY", "release_year", "1994" ], [ "CAR 54, WHERE ARE YOU?", "has_genre", "COMEDY" ], [ "CAR 54, WHERE ARE YOU?", "release_year", "1994" ], [ "CAT BALLOU", "has_genre", "COMEDY" ], [ "CAT BALLOU", "has_genre", "WESTERN" ], [ "CEMETERY MAN", "has_genre", "COMEDY" ], [ "CEMETERY MAN", "release_year", "1994" ], [ "CHASERS", "has_genre", "COMEDY" ], [ "CHASERS", "release_year", "1994" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "starred_actors", "GLENN FORD" ], [ "CITY SLICKERS", "has_genre", "COMEDY" ], [ "CITY SLICKERS", "has_genre", "WESTERN" ], [ "CLEAN SLATE", "has_genre", "COMEDY" ], [ "CLEAN SLATE", "release_year", "1994" ], [ "CLERKS", "has_genre", "COMEDY" ], [ "CLERKS", "has_tags", "COMEDY" ], [ "CLERKS", "release_year", "1994" ], [ "CLIFFORD", "has_genre", "COMEDY" ], [ "CLIFFORD", "release_year", "1994" ], [ "COWBOY", "has_genre", "WESTERN" ], [ "COWBOY", "starred_actors", "GLENN FORD" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "1994" ], [ "DAMSELS IN DISTRESS", "directed_by", "WHIT STILLMAN" ], [ "DAMSELS IN DISTRESS", "has_genre", "COMEDY" ], [ "DAMSELS IN DISTRESS", "has_tags", "WHIT STILLMAN" ], [ "DAMSELS IN DISTRESS", "written_by", "WHIT STILLMAN" ], [ "DEADLY ADVICE", "has_genre", "COMEDY" ], [ "DEADLY ADVICE", "release_year", "1994" ], [ "DEAR HEART", "has_genre", "COMEDY" ], [ "DEAR HEART", "starred_actors", "GLENN FORD" ], [ "DON'T DRINK THE WATER", "has_genre", "COMEDY" ], [ "DON'T DRINK THE WATER", "release_year", "1994" ], [ "DON'T GO NEAR THE WATER", "has_genre", "COMEDY" ], [ "DON'T GO NEAR THE WATER", "starred_actors", "GLENN FORD" ], [ "ED WOOD", "has_genre", "COMEDY" ], [ "ED WOOD", "release_year", "1994" ], [ "ERNEST GOES TO SCHOOL", "has_genre", "COMEDY" ], [ "ERNEST GOES TO SCHOOL", "release_year", "1994" ], [ "EVIL ROY SLADE", "has_genre", "COMEDY" ], [ "EVIL ROY SLADE", "has_genre", "WESTERN" ], [ "EXIT TO EDEN", "has_genre", "COMEDY" ], [ "EXIT TO EDEN", "release_year", "1994" ], [ "FLOUNDERING", "has_genre", "COMEDY" ], [ "FLOUNDERING", "release_year", "1994" ], [ "FORREST GUMP", "has_tags", "COMEDY" ], [ "FORREST GUMP", "release_year", "1994" ], [ "FOUR WEDDINGS AND A FUNERAL", "has_genre", "COMEDY" ], [ "FOUR WEDDINGS AND A FUNERAL", "has_tags", "COMEDY" ], [ "FOUR WEDDINGS AND A FUNERAL", "release_year", "1994" ], [ "FROM BEIJING WITH LOVE", "has_genre", "COMEDY" ], [ "FROM BEIJING WITH LOVE", "release_year", "1994" ], [ "GETTING EVEN WITH DAD", "has_genre", "COMEDY" ], [ "GETTING EVEN WITH DAD", "release_year", "1994" ], [ "GETTING IN", "has_genre", "COMEDY" ], [ "GETTING IN", "release_year", "1994" ], [ "GOIN' SOUTH", "has_genre", "COMEDY" ], [ "GOIN' SOUTH", "has_genre", "WESTERN" ], [ "GOLD RAIDERS", "has_genre", "COMEDY" ], [ "GOLD RAIDERS", "has_genre", "WESTERN" ], [ "GREEDY", "has_genre", "COMEDY" ], [ "GREEDY", "release_year", "1994" ], [ "GUARDING TESS", "has_genre", "COMEDY" ], [ "GUARDING TESS", "release_year", "1994" ], [ "HAIL CAESAR", "has_genre", "COMEDY" ], [ "HAIL CAESAR", "release_year", "1994" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_genre", "WESTERN" ], [ "HOLY MATRIMONY", "has_genre", "COMEDY" ], [ "HOLY MATRIMONY", "release_year", "1994" ], [ "I LIKE IT LIKE THAT", "has_genre", "COMEDY" ], [ "I LIKE IT LIKE THAT", "release_year", "1994" ], [ "I LOVE TROUBLE", "has_genre", "COMEDY" ], [ "I LOVE TROUBLE", "release_year", "1994" ], [ "I.Q.", "has_genre", "COMEDY" ], [ "I.Q.", "release_year", "1994" ], [ "IN THE ARMY NOW", "has_genre", "COMEDY" ], [ "IN THE ARMY NOW", "release_year", "1994" ], [ "IT COULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "release_year", "1994" ], [ "IT RUNS IN THE FAMILY", "has_genre", "COMEDY" ], [ "IT RUNS IN THE FAMILY", "release_year", "1994" ], [ "IT'S PAT", "has_genre", "COMEDY" ], [ "IT'S PAT", "release_year", "1994" ], [ "JUBAL", "has_genre", "WESTERN" ], [ "JUBAL", "starred_actors", "GLENN FORD" ], [ "JUNIOR", "has_genre", "COMEDY" ], [ "JUNIOR", "release_year", "1994" ], [ "KABHI HAAN KABHI NAA", "has_genre", "COMEDY" ], [ "KABHI HAAN KABHI NAA", "release_year", "1994" ], [ "LEPRECHAUN 2", "has_genre", "COMEDY" ], [ "LEPRECHAUN 2", "release_year", "1994" ], [ "LIGHTNING JACK", "has_genre", "COMEDY" ], [ "LIGHTNING JACK", "has_genre", "WESTERN" ], [ "LIGHTNING JACK", "release_year", "1994" ], [ "LITTLE BIG MAN", "has_genre", "COMEDY" ], [ "LITTLE BIG MAN", "has_genre", "WESTERN" ], [ "LITTLE GIANTS", "has_genre", "COMEDY" ], [ "LITTLE GIANTS", "release_year", "1994" ], [ "LUST FOR GOLD", "has_genre", "WESTERN" ], [ "LUST FOR GOLD", "starred_actors", "GLENN FORD" ], [ "MAVERICK", "has_genre", "COMEDY" ], [ "MAVERICK", "has_tags", "COMEDY" ], [ "MAVERICK", "has_tags", "WESTERN" ], [ "MAVERICK", "release_year", "1994" ], [ "MCLINTOCK!", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_genre", "WESTERN" ], [ "MILK MONEY", "has_genre", "COMEDY" ], [ "MILK MONEY", "release_year", "1994" ], [ "MIXED NUTS", "has_genre", "COMEDY" ], [ "MIXED NUTS", "release_year", "1994" ], [ "MONKEY TROUBLE", "has_genre", "COMEDY" ], [ "MONKEY TROUBLE", "release_year", "1994" ], [ "MURIEL'S WEDDING", "has_genre", "COMEDY" ], [ "MURIEL'S WEDDING", "has_tags", "COMEDY" ], [ "MURIEL'S WEDDING", "release_year", "1994" ], [ "MY GIRL 2", "has_genre", "COMEDY" ], [ "MY GIRL 2", "release_year", "1994" ], [ "MY LITTLE CHICKADEE", "has_genre", "COMEDY" ], [ "MY LITTLE CHICKADEE", "has_genre", "WESTERN" ], [ "NOBODY'S FOOL", "has_genre", "COMEDY" ], [ "NOBODY'S FOOL", "release_year", "1994" ], [ "NORTH", "has_genre", "COMEDY" ], [ "NORTH", "release_year", "1994" ], [ "ONLY YOU", "has_genre", "COMEDY" ], [ "ONLY YOU", "release_year", "1994" ], [ "PCU", "has_genre", "COMEDY" ], [ "PCU", "release_year", "1994" ], [ "POCKETFUL OF MIRACLES", "has_genre", "COMEDY" ], [ "POCKETFUL OF MIRACLES", "has_tags", "COMEDY" ], [ "POCKETFUL OF MIRACLES", "starred_actors", "GLENN FORD" ], [ "PRINCESS CARABOO", "has_genre", "COMEDY" ], [ "PRINCESS CARABOO", "release_year", "1994" ], [ "PULP FICTION", "has_tags", "COMEDY" ], [ "PULP FICTION", "release_year", "1994" ], [ "RADIOLAND MURDERS", "has_genre", "COMEDY" ], [ "RADIOLAND MURDERS", "release_year", "1994" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "has_genre", "WESTERN" ], [ "RANGO", "has_genre", "COMEDY" ], [ "RANGO", "has_tags", "WESTERN" ], [ "REALITY BITES", "has_genre", "COMEDY" ], [ "REALITY BITES", "release_year", "1994" ], [ "RENAISSANCE MAN", "has_genre", "COMEDY" ], [ "RENAISSANCE MAN", "release_year", "1994" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_genre", "COMEDY" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_tags", "COMEDY" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_tags", "MIRA SORVINO" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "starred_actors", "MIRA SORVINO" ], [ "RUSTLERS' RHAPSODY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_genre", "WESTERN" ], [ "SERIAL MOM", "has_genre", "COMEDY" ], [ "SERIAL MOM", "has_tags", "COMEDY" ], [ "SERIAL MOM", "release_year", "1994" ], [ "SKIN GAME", "has_genre", "COMEDY" ], [ "SKIN GAME", "has_genre", "WESTERN" ], [ "SLEEP WITH ME", "has_genre", "COMEDY" ], [ "SLEEP WITH ME", "release_year", "1994" ], [ "SON OF PALEFACE", "has_genre", "COMEDY" ], [ "SON OF PALEFACE", "has_genre", "WESTERN" ], [ "SPANKING THE MONKEY", "has_genre", "COMEDY" ], [ "SPANKING THE MONKEY", "release_year", "1994" ], [ "SPEECHLESS", "has_genre", "COMEDY" ], [ "SPEECHLESS", "release_year", "1994" ], [ "STAGGERED", "has_genre", "COMEDY" ], [ "STAGGERED", "release_year", "1994" ], [ "STRAIGHT TO HELL", "has_genre", "COMEDY" ], [ "STRAIGHT TO HELL", "has_genre", "WESTERN" ], [ "SWIMMING WITH SHARKS", "has_genre", "COMEDY" ], [ "SWIMMING WITH SHARKS", "release_year", "1994" ], [ "TAMMY AND THE T-REX", "has_genre", "COMEDY" ], [ "TAMMY AND THE T-REX", "release_year", "1994" ], [ "TAMPOPO", "has_genre", "COMEDY" ], [ "TAMPOPO", "has_genre", "WESTERN" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "TEXAS", "starred_actors", "GLENN FORD" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "COMEDY" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "WESTERN" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "release_year", "1994" ], [ "THE AIR UP THERE", "has_genre", "COMEDY" ], [ "THE AIR UP THERE", "has_tags", "COMEDY" ], [ "THE AIR UP THERE", "release_year", "1994" ], [ "THE CHASE", "has_genre", "COMEDY" ], [ "THE CHASE", "release_year", "1994" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "COMEDY" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "has_genre", "COMEDY" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "starred_actors", "GLENN FORD" ], [ "THE COWBOY WAY", "has_genre", "COMEDY" ], [ "THE COWBOY WAY", "release_year", "1994" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "GLENN FORD" ], [ "THE FASTEST GUN ALIVE", "has_genre", "WESTERN" ], [ "THE FASTEST GUN ALIVE", "starred_actors", "GLENN FORD" ], [ "THE FAVOR", "has_genre", "COMEDY" ], [ "THE FAVOR", "release_year", "1994" ], [ "THE FLINTSTONES", "has_genre", "COMEDY" ], [ "THE FLINTSTONES", "has_tags", "COMEDY" ], [ "THE FLINTSTONES", "release_year", "1994" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "has_genre", "WESTERN" ], [ "THE HUDSUCKER PROXY", "has_genre", "COMEDY" ], [ "THE HUDSUCKER PROXY", "has_tags", "COMEDY" ], [ "THE HUDSUCKER PROXY", "release_year", "1994" ], [ "THE INKWELL", "has_genre", "COMEDY" ], [ "THE INKWELL", "release_year", "1994" ], [ "THE LAST DAYS OF DISCO", "directed_by", "WHIT STILLMAN" ], [ "THE LAST DAYS OF DISCO", "has_genre", "COMEDY" ], [ "THE LAST DAYS OF DISCO", "has_tags", "WHIT STILLMAN" ], [ "THE LAST DAYS OF DISCO", "written_by", "WHIT STILLMAN" ], [ "THE LITTLE RASCALS", "has_genre", "COMEDY" ], [ "THE LITTLE RASCALS", "release_year", "1994" ], [ "THE MAN FROM THE ALAMO", "has_genre", "WESTERN" ], [ "THE MAN FROM THE ALAMO", "starred_actors", "GLENN FORD" ], [ "THE MASK", "has_genre", "COMEDY" ], [ "THE MASK", "has_tags", "COMEDY" ], [ "THE MASK", "release_year", "1994" ], [ "THE MATING OF MILLIE", "has_genre", "COMEDY" ], [ "THE MATING OF MILLIE", "starred_actors", "GLENN FORD" ], [ "THE MONSTER", "has_genre", "COMEDY" ], [ "THE MONSTER", "has_tags", "COMEDY" ], [ "THE MONSTER", "release_year", "1994" ], [ "THE PALEFACE", "has_genre", "COMEDY" ], [ "THE PALEFACE", "has_genre", "WESTERN" ], [ "THE PAPER", "has_genre", "COMEDY" ], [ "THE PAPER", "release_year", "1994" ], [ "THE REF", "has_genre", "COMEDY" ], [ "THE REF", "has_tags", "COMEDY" ], [ "THE REF", "release_year", "1994" ], [ "THE ROAD TO WELLVILLE", "has_genre", "COMEDY" ], [ "THE ROAD TO WELLVILLE", "release_year", "1994" ], [ "THE SANTA CLAUSE", "has_genre", "COMEDY" ], [ "THE SANTA CLAUSE", "release_year", "1994" ], [ "THE SCOUT", "has_genre", "COMEDY" ], [ "THE SCOUT", "release_year", "1994" ], [ "THE SEARCH FOR ONE-EYE JIMMY", "has_genre", "COMEDY" ], [ "THE SEARCH FOR ONE-EYE JIMMY", "release_year", "1994" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "starred_actors", "GLENN FORD" ], [ "THE SHAKIEST GUN IN THE WEST", "has_genre", "COMEDY" ], [ "THE SHAKIEST GUN IN THE WEST", "has_genre", "WESTERN" ], [ "THE SHAKIEST GUN IN THE WEST", "has_tags", "WESTERN" ], [ "THE SHEEPMAN", "has_genre", "WESTERN" ], [ "THE SHEEPMAN", "starred_actors", "GLENN FORD" ], [ "THE SUM OF US", "has_genre", "COMEDY" ], [ "THE SUM OF US", "release_year", "1994" ], [ "THE TREATMENT", "has_genre", "COMEDY" ], [ "THE TREATMENT", "starred_actors", "CHRIS EIGEMAN" ], [ "THE TRIUMPH OF LOVE", "has_genre", "COMEDY" ], [ "THE TRIUMPH OF LOVE", "starred_actors", "MIRA SORVINO" ], [ "THE VIOLENT MEN", "has_genre", "WESTERN" ], [ "THE VIOLENT MEN", "starred_actors", "GLENN FORD" ], [ "THEY CALL ME TRINITY", "has_genre", "COMEDY" ], [ "THEY CALL ME TRINITY", "has_genre", "WESTERN" ], [ "THREESOME", "has_genre", "COMEDY" ], [ "THREESOME", "has_tags", "COMEDY" ], [ "THREESOME", "release_year", "1994" ], [ "TRAPPED IN PARADISE", "has_genre", "COMEDY" ], [ "TRAPPED IN PARADISE", "release_year", "1994" ], [ "TRUE LIES", "has_genre", "COMEDY" ], [ "TRUE LIES", "has_tags", "COMEDY" ], [ "TRUE LIES", "release_year", "1994" ], [ "TWIN SITTERS", "has_genre", "COMEDY" ], [ "TWIN SITTERS", "release_year", "1994" ], [ "WILD WILD WEST", "has_genre", "COMEDY" ], [ "WILD WILD WEST", "has_genre", "WESTERN" ], [ "WILD WILD WEST", "has_tags", "COMEDY" ], [ "WITH HONORS", "has_genre", "COMEDY" ], [ "WITH HONORS", "release_year", "1994" ], [ "ZINDAGI NA MILEGI DOBARA", "has_genre", "COMEDY" ], [ "ZINDAGI NA MILEGI DOBARA", "has_tags", "SPAIN" ], [ "¡THREE AMIGOS!", "has_genre", "COMEDY" ], [ "¡THREE AMIGOS!", "has_genre", "WESTERN" ], [ "¡THREE AMIGOS!", "has_tags", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 34380, AARON KWOK 27587, ADRIAN SHERGOLD 32539, BREAKFAST WITH SCOT 800, CLAPHAM JUNCTION 23589, EVAN GOLDBERG 15855, GAY 12825, PERSUASION 23152, PRIDE 14802, SAVE ME 26129, SHELTER 35875, SUPERBAD 4175, THE DETECTIVE src, edge_attr, dst 32539, has_tags, 15855 32539, release_year, 17315 800, directed_by, 27587 800, has_tags, 15855 800, release_year, 17315 12825, directed_by, 27587 12825, release_year, 17315 23152, has_tags, 15855 23152, release_year, 17315 14802, has_tags, 15855 14802, release_year, 17315 26129, has_tags, 15855 26129, release_year, 17315 35875, release_year, 17315 35875, written_by, 23589 4175, release_year, 17315 4175, starred_actors, 34380 Question: How are AARON KWOK, CLAPHAM JUNCTION, and EVAN GOLDBERG related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AARON KWOK", "CLAPHAM JUNCTION", "EVAN GOLDBERG" ], "valid_edges": [ [ "BREAKFAST WITH SCOT", "has_tags", "GAY" ], [ "BREAKFAST WITH SCOT", "release_year", "2007" ], [ "CLAPHAM JUNCTION", "directed_by", "ADRIAN SHERGOLD" ], [ "CLAPHAM JUNCTION", "has_tags", "GAY" ], [ "CLAPHAM JUNCTION", "release_year", "2007" ], [ "PERSUASION", "directed_by", "ADRIAN SHERGOLD" ], [ "PERSUASION", "release_year", "2007" ], [ "PRIDE", "has_tags", "GAY" ], [ "PRIDE", "release_year", "2007" ], [ "SAVE ME", "has_tags", "GAY" ], [ "SAVE ME", "release_year", "2007" ], [ "SHELTER", "has_tags", "GAY" ], [ "SHELTER", "release_year", "2007" ], [ "SUPERBAD", "release_year", "2007" ], [ "SUPERBAD", "written_by", "EVAN GOLDBERG" ], [ "THE DETECTIVE", "release_year", "2007" ], [ "THE DETECTIVE", "starred_actors", "AARON KWOK" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 27261, 2009 658, 2012 739, 2081 4020, ARMIE HAMMER 13085, HANDSOME HARRY 424, MIRROR MIRROR 7181, NIGHTHAWKS 10371, SAINT JOHN OF LAS VEGAS 36325, STALLONE 33193, STEVE BUSCEMI 28292, THE MESSENGER 12576, YOUTH IN REVOLT src, edge_attr, dst 25221, release_year, 27261 658, release_year, 27261 739, release_year, 27261 739, starred_actors, 4020 13085, release_year, 27261 13085, starred_actors, 33193 424, release_year, 658 424, starred_actors, 4020 7181, has_tags, 36325 7181, release_year, 25221 10371, release_year, 27261 10371, starred_actors, 33193 28292, has_tags, 33193 28292, release_year, 27261 12576, has_tags, 33193 12576, release_year, 27261 Question: For what reason are ARMIE HAMMER, HANDSOME HARRY, and STALLONE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ARMIE HAMMER", "HANDSOME HARRY", "STALLONE" ], "valid_edges": [ [ "1981", "release_year", "2009" ], [ "2012", "release_year", "2009" ], [ "2081", "release_year", "2009" ], [ "2081", "starred_actors", "ARMIE HAMMER" ], [ "HANDSOME HARRY", "release_year", "2009" ], [ "HANDSOME HARRY", "starred_actors", "STEVE BUSCEMI" ], [ "MIRROR MIRROR", "release_year", "2012" ], [ "MIRROR MIRROR", "starred_actors", "ARMIE HAMMER" ], [ "NIGHTHAWKS", "has_tags", "STALLONE" ], [ "NIGHTHAWKS", "release_year", "1981" ], [ "SAINT JOHN OF LAS VEGAS", "release_year", "2009" ], [ "SAINT JOHN OF LAS VEGAS", "starred_actors", "STEVE BUSCEMI" ], [ "THE MESSENGER", "has_tags", "STEVE BUSCEMI" ], [ "THE MESSENGER", "release_year", "2009" ], [ "YOUTH IN REVOLT", "has_tags", "STEVE BUSCEMI" ], [ "YOUTH IN REVOLT", "release_year", "2009" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 9594, ALZHEIMER'S DISEASE 20038, IRIS 35621, MILLENNIUM ACTRESS 29096, MONSOON WEDDING 20096, SABRINA DHAWAN 18935, SATOSHI KON src, edge_attr, dst 20038, has_tags, 9594 20038, release_year, 13408 35621, directed_by, 18935 35621, has_tags, 18935 35621, release_year, 13408 35621, written_by, 18935 29096, release_year, 13408 29096, written_by, 20096 Question: In what context are ALZHEIMER'S DISEASE, SABRINA DHAWAN, and SATOSHI KON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALZHEIMER'S DISEASE", "SABRINA DHAWAN", "SATOSHI KON" ], "valid_edges": [ [ "IRIS", "has_tags", "ALZHEIMER'S DISEASE" ], [ "IRIS", "release_year", "2001" ], [ "MILLENNIUM ACTRESS", "directed_by", "SATOSHI KON" ], [ "MILLENNIUM ACTRESS", "has_tags", "SATOSHI KON" ], [ "MILLENNIUM ACTRESS", "release_year", "2001" ], [ "MILLENNIUM ACTRESS", "written_by", "SATOSHI KON" ], [ "MONSOON WEDDING", "release_year", "2001" ], [ "MONSOON WEDDING", "written_by", "SABRINA DHAWAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 23409, AN IDEAL HUSBAND 2297, CHRISTMAS EVE 30463, COMEDY 20519, FRONT PAGE WOMAN 12053, HONEYMOON 14226, IT HAPPENED ON FIFTH AVENUE 38412, LIFE WITH FATHER 27297, MAGIC TOWN 13889, MICHAEL CURTIZ 30166, MONSIEUR VERDOUX 26612, MY FAVORITE BRUNETTE 31713, ROAD TO RIO 31600, RUBIN AND ED 10804, SOMETHING IN THE WIND 18711, SON OF FLUBBER 35507, SONG OF THE THIN MAN 8318, THE BACHELOR AND THE BOBBY-SOXER 28719, THE BISHOP'S WIFE 17991, THE EGG AND I 25837, THE PERILS OF PAULINE 30746, THE SECRET LIFE OF WALTER MITTY 15558, THE SIN OF HAROLD DIDDLEBOCK 262, THE UNSUSPECTED 7486, THIS IS THE ARMY 22241, WE'RE NO ANGELS src, edge_attr, dst 23409, has_genre, 30463 23409, has_tags, 30463 23409, release_year, 26310 2297, has_genre, 30463 2297, release_year, 26310 20519, directed_by, 13889 20519, has_genre, 30463 20519, has_tags, 13889 12053, has_genre, 30463 12053, release_year, 26310 14226, has_genre, 30463 14226, release_year, 26310 38412, has_genre, 30463 38412, release_year, 26310 27297, has_genre, 30463 27297, release_year, 26310 30166, has_genre, 30463 30166, release_year, 26310 26612, has_genre, 30463 26612, release_year, 26310 31713, has_genre, 30463 31713, release_year, 26310 31600, has_genre, 30463 10804, has_genre, 30463 10804, release_year, 26310 18711, has_genre, 30463 35507, has_genre, 30463 35507, release_year, 26310 8318, has_genre, 30463 8318, release_year, 26310 28719, has_genre, 30463 28719, release_year, 26310 17991, has_genre, 30463 17991, release_year, 26310 25837, has_genre, 30463 25837, release_year, 26310 30746, has_genre, 30463 30746, release_year, 26310 15558, has_genre, 30463 15558, release_year, 26310 262, directed_by, 13889 262, has_tags, 13889 262, release_year, 26310 7486, directed_by, 13889 7486, has_genre, 30463 22241, directed_by, 13889 22241, has_genre, 30463 22241, has_tags, 30463 22241, has_tags, 13889 Question: In what context are RUBIN AND ED, SON OF FLUBBER, and THE UNSUSPECTED connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "RUBIN AND ED", "SON OF FLUBBER", "THE UNSUSPECTED" ], "valid_edges": [ [ "AN IDEAL HUSBAND", "has_genre", "COMEDY" ], [ "AN IDEAL HUSBAND", "has_tags", "COMEDY" ], [ "AN IDEAL HUSBAND", "release_year", "1947" ], [ "CHRISTMAS EVE", "has_genre", "COMEDY" ], [ "CHRISTMAS EVE", "release_year", "1947" ], [ "FRONT PAGE WOMAN", "directed_by", "MICHAEL CURTIZ" ], [ "FRONT PAGE WOMAN", "has_genre", "COMEDY" ], [ "FRONT PAGE WOMAN", "has_tags", "MICHAEL CURTIZ" ], [ "HONEYMOON", "has_genre", "COMEDY" ], [ "HONEYMOON", "release_year", "1947" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_genre", "COMEDY" ], [ "IT HAPPENED ON FIFTH AVENUE", "release_year", "1947" ], [ "LIFE WITH FATHER", "has_genre", "COMEDY" ], [ "LIFE WITH FATHER", "release_year", "1947" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "release_year", "1947" ], [ "MONSIEUR VERDOUX", "has_genre", "COMEDY" ], [ "MONSIEUR VERDOUX", "release_year", "1947" ], [ "MY FAVORITE BRUNETTE", "has_genre", "COMEDY" ], [ "MY FAVORITE BRUNETTE", "release_year", "1947" ], [ "ROAD TO RIO", "has_genre", "COMEDY" ], [ "ROAD TO RIO", "release_year", "1947" ], [ "RUBIN AND ED", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "release_year", "1947" ], [ "SON OF FLUBBER", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "release_year", "1947" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "has_genre", "COMEDY" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "release_year", "1947" ], [ "THE BISHOP'S WIFE", "has_genre", "COMEDY" ], [ "THE BISHOP'S WIFE", "release_year", "1947" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "release_year", "1947" ], [ "THE PERILS OF PAULINE", "has_genre", "COMEDY" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "has_genre", "COMEDY" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "release_year", "1947" ], [ "THE UNSUSPECTED", "directed_by", "MICHAEL CURTIZ" ], [ "THE UNSUSPECTED", "has_tags", "MICHAEL CURTIZ" ], [ "THE UNSUSPECTED", "release_year", "1947" ], [ "THIS IS THE ARMY", "directed_by", "MICHAEL CURTIZ" ], [ "THIS IS THE ARMY", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "directed_by", "MICHAEL CURTIZ" ], [ "WE'RE NO ANGELS", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "MICHAEL CURTIZ" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 1421, 2013 3536, ASS BACKWARDS 17215, FIRE IN THE BLOOD 30746, THE SECRET LIFE OF WALTER MITTY 18315, THE UNFAITHFUL 19852, ZACKIE ACHMAT src, edge_attr, dst 3536, release_year, 1421 17215, release_year, 1421 17215, starred_actors, 19852 30746, release_year, 26310 30746, release_year, 1421 18315, release_year, 26310 Question: How are ASS BACKWARDS, THE UNFAITHFUL, and ZACKIE ACHMAT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ASS BACKWARDS", "THE UNFAITHFUL", "ZACKIE ACHMAT" ], "valid_edges": [ [ "ASS BACKWARDS", "release_year", "2013" ], [ "FIRE IN THE BLOOD", "release_year", "2013" ], [ "FIRE IN THE BLOOD", "starred_actors", "ZACKIE ACHMAT" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "2013" ], [ "THE UNFAITHFUL", "release_year", "1947" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4058, 16 YEARS OF ALCOHOL 8779, 1945 1097, 2003 31345, 21 GRAMS 26501, ALILA 39500, ALL THE REAL GIRLS 16391, AMERICAN SPLENDOR 30281, ANA AND THE OTHERS 12144, BAD BOYS 33140, BAGHBAN 2419, BEYOND BORDERS 18822, BIG FISH 39878, BRIGHT FUTURE 22639, BRIGHT YOUNG THINGS 29448, CARANDIRU 19510, CLEOPATRA 4890, COLD MOUNTAIN 28659, DEAD END 28862, DOGVILLE 23182, DOPAMINE 36212, DRAMA 34486, EILA 14257, ELEPHANT 9048, EVIL 7866, FLYWHEEL 24226, FREDDY VS. JASON 39946, GACY 3674, GAMES OF LOVE AND CHANCE 7599, GIRL WITH A PEARL EARRING 25324, HER HIGHNESS AND THE BELLBOY 27350, HITCHCOCK 39494, HOLES 35319, HOPE SPRINGS 20309, HOUSE OF SAND AND FOG 19839, I ACCUSE 6684, I'LL SLEEP WHEN I'M DEAD 21437, IN THE CITY 31900, INCANTATO 39987, IT RUNS IN THE FAMILY 6425, IT'S ALL ABOUT LOVE 21614, JAPANESE STORY 8844, JONNY VANG 31245, KAL HO NAA HO 26853, LATTER DAYS 13296, LEVITY 15814, LOST IN TRANSLATION 35948, LOVE COMES SOFTLY 2088, MAIN PREM KI DIWANI HOON 11334, MASKED AND ANONYMOUS 18198, MATCHSTICK MEN 25936, MONA LISA SMILE 27827, MONSTER 12944, MY LIFE WITHOUT ME 25424, MY SON JOHN 9343, MYSTIC RIVER 37329, NATHALIE... 34705, NORMAL 21446, OFF THE MAP 10789, OPEN WATER 35341, ORFEU 34120, OSAMA 23553, OUR TOWN 24769, OUT OF THE ASHES 23801, PARTY MONSTER 26350, PIECES OF APRIL 29357, RECONSTRUCTION 16708, ROADS TO KOKTEBEL 12932, ROBERT WALKER 16356, ROBOT STORIES 5145, SAINTS AND SOLDIERS 3416, SARABAND 39821, SECONDHAND LIONS 4027, SHARA 38114, SHATTERED GLASS 5710, SOLDIER'S GIRL 19971, SPIN 40046, STRANGERS ON A TRAIN 6323, STRAYED 16954, SYLVIA 7985, SYMMETRY 11605, TAKE MY EYES 38965, THE BARBARIAN INVASIONS 38410, THE BATTLE OF SHAKER HEIGHTS 5144, THE BIG EMPTY 16923, THE CLOCK 25461, THE COOLER 21345, THE DREAMERS 12047, THE EVENT 20929, THE FIGHTING TEMPTATIONS 12447, THE HUMAN STAIN 32030, THE LOST PRINCE 24434, THE MUDGE BOY 28919, THE RETURN 30906, THE ROOM 38858, THE SHAPE OF THINGS 12883, THE SLEEPING DICTIONARY 2259, THE STATEMENT 38108, THE STATION AGENT 39036, THE STORY OF MARIE AND JULIEN 39883, THE STORY OF THE WEEPING CAMEL 22820, THE UNITED STATES OF LELAND 1411, THIRTEEN 10628, TIME OF THE WOLF 35264, TWO DAYS 11544, UNDER THE TUSCAN SUN 14956, VOICES OF A DISTANT STAR 31862, WONDERLAND 27708, WUTHERING HEIGHTS 39834, YOUNG ADAM src, edge_attr, dst 4058, has_genre, 36212 4058, release_year, 1097 31345, has_genre, 36212 31345, has_tags, 36212 31345, release_year, 1097 26501, has_genre, 36212 26501, release_year, 1097 39500, has_genre, 36212 39500, release_year, 1097 16391, has_genre, 36212 16391, release_year, 1097 30281, has_genre, 36212 30281, release_year, 1097 12144, has_genre, 36212 12144, release_year, 1097 33140, has_genre, 36212 33140, release_year, 1097 2419, has_genre, 36212 2419, release_year, 1097 18822, has_genre, 36212 18822, release_year, 1097 39878, has_genre, 36212 39878, release_year, 1097 22639, has_genre, 36212 22639, release_year, 1097 29448, has_genre, 36212 29448, release_year, 1097 19510, has_genre, 36212 19510, release_year, 1097 4890, has_genre, 36212 4890, has_tags, 36212 4890, release_year, 1097 28659, has_genre, 36212 28659, release_year, 1097 28862, has_genre, 36212 28862, has_tags, 36212 28862, release_year, 1097 23182, has_genre, 36212 23182, release_year, 1097 34486, has_genre, 36212 34486, release_year, 1097 14257, has_genre, 36212 14257, release_year, 1097 9048, has_genre, 36212 9048, release_year, 1097 7866, has_genre, 36212 7866, release_year, 1097 24226, release_year, 1097 39946, has_genre, 36212 39946, release_year, 1097 3674, has_genre, 36212 3674, release_year, 1097 7599, has_genre, 36212 7599, has_tags, 36212 7599, release_year, 1097 25324, release_year, 8779 25324, starred_actors, 12932 27350, has_genre, 36212 39494, has_genre, 36212 39494, release_year, 1097 35319, has_genre, 36212 35319, release_year, 1097 20309, has_genre, 36212 20309, release_year, 1097 19839, has_genre, 36212 19839, release_year, 1097 6684, has_genre, 36212 6684, release_year, 1097 21437, has_genre, 36212 21437, release_year, 1097 31900, has_genre, 36212 31900, release_year, 1097 39987, has_genre, 36212 39987, release_year, 1097 6425, has_genre, 36212 6425, release_year, 1097 21614, has_genre, 36212 21614, release_year, 1097 8844, has_genre, 36212 8844, release_year, 1097 31245, has_genre, 36212 31245, release_year, 1097 26853, has_genre, 36212 26853, release_year, 1097 13296, has_genre, 36212 13296, release_year, 1097 15814, has_genre, 36212 15814, release_year, 1097 35948, has_genre, 36212 35948, release_year, 1097 2088, has_genre, 36212 2088, release_year, 1097 11334, has_genre, 36212 11334, release_year, 1097 18198, has_genre, 36212 18198, has_tags, 36212 18198, release_year, 1097 25936, has_genre, 36212 25936, release_year, 1097 27827, has_genre, 36212 27827, has_tags, 36212 27827, release_year, 1097 12944, has_genre, 36212 12944, release_year, 1097 25424, has_genre, 36212 25424, starred_actors, 12932 9343, has_genre, 36212 9343, has_tags, 36212 9343, release_year, 1097 37329, has_genre, 36212 37329, release_year, 1097 34705, has_genre, 36212 34705, release_year, 1097 21446, has_genre, 36212 21446, has_tags, 36212 21446, release_year, 1097 10789, has_genre, 36212 10789, release_year, 1097 35341, has_genre, 36212 34120, has_genre, 36212 34120, release_year, 1097 23553, has_genre, 36212 23553, release_year, 1097 24769, has_genre, 36212 24769, release_year, 1097 23801, has_genre, 36212 23801, release_year, 1097 26350, has_genre, 36212 26350, release_year, 1097 29357, has_genre, 36212 29357, release_year, 1097 16708, has_genre, 36212 16708, release_year, 1097 16356, has_genre, 36212 16356, release_year, 1097 5145, has_genre, 36212 5145, release_year, 1097 3416, has_genre, 36212 3416, has_tags, 36212 3416, release_year, 1097 39821, has_genre, 36212 39821, release_year, 1097 4027, has_genre, 36212 4027, release_year, 1097 38114, has_genre, 36212 38114, release_year, 1097 5710, has_genre, 36212 5710, release_year, 1097 19971, has_genre, 36212 19971, release_year, 1097 40046, has_tags, 27350 40046, starred_actors, 12932 6323, has_genre, 36212 6323, release_year, 1097 16954, has_genre, 36212 16954, release_year, 1097 7985, has_genre, 36212 7985, release_year, 1097 11605, has_genre, 36212 11605, release_year, 1097 38965, has_genre, 36212 38965, release_year, 1097 38410, has_genre, 36212 38410, release_year, 1097 5144, has_genre, 36212 5144, release_year, 1097 16923, has_genre, 36212 16923, release_year, 8779 16923, starred_actors, 12932 25461, has_genre, 36212 25461, release_year, 1097 21345, has_genre, 36212 21345, release_year, 1097 12047, has_genre, 36212 12047, release_year, 1097 20929, has_genre, 36212 20929, release_year, 1097 12447, has_genre, 36212 12447, release_year, 1097 32030, has_genre, 36212 32030, release_year, 1097 24434, has_genre, 36212 24434, release_year, 1097 28919, has_genre, 36212 28919, release_year, 1097 30906, has_genre, 36212 30906, release_year, 1097 38858, has_genre, 36212 38858, release_year, 1097 12883, has_genre, 36212 12883, release_year, 1097 2259, has_genre, 36212 2259, release_year, 1097 38108, has_genre, 36212 38108, release_year, 1097 39036, has_genre, 36212 39036, release_year, 1097 39883, has_genre, 36212 39883, release_year, 1097 22820, has_genre, 36212 22820, release_year, 1097 1411, has_genre, 36212 1411, has_tags, 36212 1411, release_year, 1097 10628, has_genre, 36212 10628, release_year, 1097 35264, has_genre, 36212 35264, release_year, 1097 11544, has_genre, 36212 11544, release_year, 1097 14956, has_genre, 36212 14956, release_year, 1097 31862, has_genre, 36212 31862, release_year, 1097 27708, has_genre, 36212 27708, release_year, 1097 39834, has_genre, 36212 39834, release_year, 1097 Question: For what reason are FREDDY VS. JASON, ORFEU, and ROBERT WALKER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FREDDY VS. JASON", "ORFEU", "ROBERT WALKER" ], "valid_edges": [ [ "16 YEARS OF ALCOHOL", "has_genre", "DRAMA" ], [ "16 YEARS OF ALCOHOL", "release_year", "2003" ], [ "21 GRAMS", "has_genre", "DRAMA" ], [ "21 GRAMS", "has_tags", "DRAMA" ], [ "21 GRAMS", "release_year", "2003" ], [ "ALILA", "has_genre", "DRAMA" ], [ "ALILA", "release_year", "2003" ], [ "ALL THE REAL GIRLS", "has_genre", "DRAMA" ], [ "ALL THE REAL GIRLS", "release_year", "2003" ], [ "AMERICAN SPLENDOR", "has_genre", "DRAMA" ], [ "AMERICAN SPLENDOR", "release_year", "2003" ], [ "ANA AND THE OTHERS", "has_genre", "DRAMA" ], [ "ANA AND THE OTHERS", "release_year", "2003" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "release_year", "2003" ], [ "BAGHBAN", "has_genre", "DRAMA" ], [ "BAGHBAN", "release_year", "2003" ], [ "BEYOND BORDERS", "has_genre", "DRAMA" ], [ "BEYOND BORDERS", "release_year", "2003" ], [ "BIG FISH", "has_genre", "DRAMA" ], [ "BIG FISH", "release_year", "2003" ], [ "BRIGHT FUTURE", "has_genre", "DRAMA" ], [ "BRIGHT FUTURE", "release_year", "2003" ], [ "BRIGHT YOUNG THINGS", "has_genre", "DRAMA" ], [ "BRIGHT YOUNG THINGS", "release_year", "2003" ], [ "CARANDIRU", "has_genre", "DRAMA" ], [ "CARANDIRU", "release_year", "2003" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "2003" ], [ "COLD MOUNTAIN", "has_genre", "DRAMA" ], [ "COLD MOUNTAIN", "has_tags", "DRAMA" ], [ "COLD MOUNTAIN", "release_year", "2003" ], [ "DEAD END", "has_genre", "DRAMA" ], [ "DEAD END", "release_year", "2003" ], [ "DOGVILLE", "has_genre", "DRAMA" ], [ "DOGVILLE", "has_tags", "DRAMA" ], [ "DOGVILLE", "release_year", "2003" ], [ "DOPAMINE", "has_genre", "DRAMA" ], [ "DOPAMINE", "release_year", "2003" ], [ "EILA", "has_genre", "DRAMA" ], [ "EILA", "release_year", "2003" ], [ "ELEPHANT", "has_genre", "DRAMA" ], [ "ELEPHANT", "release_year", "2003" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "release_year", "2003" ], [ "FLYWHEEL", "has_genre", "DRAMA" ], [ "FLYWHEEL", "release_year", "2003" ], [ "FREDDY VS. JASON", "release_year", "2003" ], [ "GACY", "has_genre", "DRAMA" ], [ "GACY", "release_year", "2003" ], [ "GAMES OF LOVE AND CHANCE", "has_genre", "DRAMA" ], [ "GAMES OF LOVE AND CHANCE", "release_year", "2003" ], [ "GIRL WITH A PEARL EARRING", "has_genre", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "has_tags", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "release_year", "2003" ], [ "HER HIGHNESS AND THE BELLBOY", "release_year", "1945" ], [ "HER HIGHNESS AND THE BELLBOY", "starred_actors", "ROBERT WALKER" ], [ "HITCHCOCK", "has_genre", "DRAMA" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HOLES", "release_year", "2003" ], [ "HOPE SPRINGS", "has_genre", "DRAMA" ], [ "HOPE SPRINGS", "release_year", "2003" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "release_year", "2003" ], [ "I ACCUSE", "has_genre", "DRAMA" ], [ "I ACCUSE", "release_year", "2003" ], [ "I'LL SLEEP WHEN I'M DEAD", "has_genre", "DRAMA" ], [ "I'LL SLEEP WHEN I'M DEAD", "release_year", "2003" ], [ "IN THE CITY", "has_genre", "DRAMA" ], [ "IN THE CITY", "release_year", "2003" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "release_year", "2003" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "IT RUNS IN THE FAMILY", "release_year", "2003" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "release_year", "2003" ], [ "JAPANESE STORY", "has_genre", "DRAMA" ], [ "JAPANESE STORY", "release_year", "2003" ], [ "JONNY VANG", "has_genre", "DRAMA" ], [ "JONNY VANG", "release_year", "2003" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KAL HO NAA HO", "release_year", "2003" ], [ "LATTER DAYS", "has_genre", "DRAMA" ], [ "LATTER DAYS", "release_year", "2003" ], [ "LEVITY", "has_genre", "DRAMA" ], [ "LEVITY", "release_year", "2003" ], [ "LOST IN TRANSLATION", "has_genre", "DRAMA" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "release_year", "2003" ], [ "MAIN PREM KI DIWANI HOON", "has_genre", "DRAMA" ], [ "MAIN PREM KI DIWANI HOON", "release_year", "2003" ], [ "MASKED AND ANONYMOUS", "has_genre", "DRAMA" ], [ "MASKED AND ANONYMOUS", "release_year", "2003" ], [ "MATCHSTICK MEN", "has_genre", "DRAMA" ], [ "MATCHSTICK MEN", "has_tags", "DRAMA" ], [ "MATCHSTICK MEN", "release_year", "2003" ], [ "MONA LISA SMILE", "has_genre", "DRAMA" ], [ "MONA LISA SMILE", "release_year", "2003" ], [ "MONSTER", "has_genre", "DRAMA" ], [ "MONSTER", "has_tags", "DRAMA" ], [ "MONSTER", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "MY SON JOHN", "has_genre", "DRAMA" ], [ "MY SON JOHN", "starred_actors", "ROBERT WALKER" ], [ "MYSTIC RIVER", "has_genre", "DRAMA" ], [ "MYSTIC RIVER", "has_tags", "DRAMA" ], [ "MYSTIC RIVER", "release_year", "2003" ], [ "NATHALIE...", "has_genre", "DRAMA" ], [ "NATHALIE...", "release_year", "2003" ], [ "NORMAL", "has_genre", "DRAMA" ], [ "NORMAL", "release_year", "2003" ], [ "OFF THE MAP", "has_genre", "DRAMA" ], [ "OFF THE MAP", "has_tags", "DRAMA" ], [ "OFF THE MAP", "release_year", "2003" ], [ "OPEN WATER", "has_genre", "DRAMA" ], [ "OPEN WATER", "release_year", "2003" ], [ "ORFEU", "has_genre", "DRAMA" ], [ "OSAMA", "has_genre", "DRAMA" ], [ "OSAMA", "release_year", "2003" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "release_year", "2003" ], [ "OUT OF THE ASHES", "has_genre", "DRAMA" ], [ "OUT OF THE ASHES", "release_year", "2003" ], [ "PARTY MONSTER", "has_genre", "DRAMA" ], [ "PARTY MONSTER", "release_year", "2003" ], [ "PIECES OF APRIL", "has_genre", "DRAMA" ], [ "PIECES OF APRIL", "release_year", "2003" ], [ "RECONSTRUCTION", "has_genre", "DRAMA" ], [ "RECONSTRUCTION", "release_year", "2003" ], [ "ROADS TO KOKTEBEL", "has_genre", "DRAMA" ], [ "ROADS TO KOKTEBEL", "release_year", "2003" ], [ "ROBOT STORIES", "has_genre", "DRAMA" ], [ "ROBOT STORIES", "release_year", "2003" ], [ "SAINTS AND SOLDIERS", "has_genre", "DRAMA" ], [ "SAINTS AND SOLDIERS", "release_year", "2003" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "release_year", "2003" ], [ "SECONDHAND LIONS", "has_genre", "DRAMA" ], [ "SECONDHAND LIONS", "release_year", "2003" ], [ "SHARA", "has_genre", "DRAMA" ], [ "SHARA", "release_year", "2003" ], [ "SHATTERED GLASS", "has_genre", "DRAMA" ], [ "SHATTERED GLASS", "release_year", "2003" ], [ "SOLDIER'S GIRL", "has_genre", "DRAMA" ], [ "SOLDIER'S GIRL", "release_year", "2003" ], [ "SPIN", "has_genre", "DRAMA" ], [ "SPIN", "release_year", "2003" ], [ "STRANGERS ON A TRAIN", "has_tags", "HITCHCOCK" ], [ "STRANGERS ON A TRAIN", "starred_actors", "ROBERT WALKER" ], [ "STRAYED", "has_genre", "DRAMA" ], [ "STRAYED", "release_year", "2003" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "release_year", "2003" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "release_year", "2003" ], [ "TAKE MY EYES", "has_genre", "DRAMA" ], [ "TAKE MY EYES", "release_year", "2003" ], [ "THE BARBARIAN INVASIONS", "has_genre", "DRAMA" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BATTLE OF SHAKER HEIGHTS", "has_genre", "DRAMA" ], [ "THE BATTLE OF SHAKER HEIGHTS", "release_year", "2003" ], [ "THE BIG EMPTY", "has_genre", "DRAMA" ], [ "THE BIG EMPTY", "release_year", "2003" ], [ "THE CLOCK", "has_genre", "DRAMA" ], [ "THE CLOCK", "release_year", "1945" ], [ "THE CLOCK", "starred_actors", "ROBERT WALKER" ], [ "THE COOLER", "has_genre", "DRAMA" ], [ "THE COOLER", "release_year", "2003" ], [ "THE DREAMERS", "has_genre", "DRAMA" ], [ "THE DREAMERS", "release_year", "2003" ], [ "THE EVENT", "has_genre", "DRAMA" ], [ "THE EVENT", "release_year", "2003" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "DRAMA" ], [ "THE FIGHTING TEMPTATIONS", "release_year", "2003" ], [ "THE HUMAN STAIN", "has_genre", "DRAMA" ], [ "THE HUMAN STAIN", "release_year", "2003" ], [ "THE LOST PRINCE", "has_genre", "DRAMA" ], [ "THE LOST PRINCE", "release_year", "2003" ], [ "THE MUDGE BOY", "has_genre", "DRAMA" ], [ "THE MUDGE BOY", "release_year", "2003" ], [ "THE RETURN", "has_genre", "DRAMA" ], [ "THE RETURN", "release_year", "2003" ], [ "THE ROOM", "has_genre", "DRAMA" ], [ "THE ROOM", "release_year", "2003" ], [ "THE SHAPE OF THINGS", "has_genre", "DRAMA" ], [ "THE SHAPE OF THINGS", "release_year", "2003" ], [ "THE SLEEPING DICTIONARY", "has_genre", "DRAMA" ], [ "THE SLEEPING DICTIONARY", "release_year", "2003" ], [ "THE STATEMENT", "has_genre", "DRAMA" ], [ "THE STATEMENT", "release_year", "2003" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE STORY OF MARIE AND JULIEN", "has_genre", "DRAMA" ], [ "THE STORY OF MARIE AND JULIEN", "release_year", "2003" ], [ "THE STORY OF THE WEEPING CAMEL", "has_genre", "DRAMA" ], [ "THE STORY OF THE WEEPING CAMEL", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_genre", "DRAMA" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THIRTEEN", "has_genre", "DRAMA" ], [ "THIRTEEN", "has_tags", "DRAMA" ], [ "THIRTEEN", "release_year", "2003" ], [ "TIME OF THE WOLF", "has_genre", "DRAMA" ], [ "TIME OF THE WOLF", "release_year", "2003" ], [ "TWO DAYS", "has_genre", "DRAMA" ], [ "TWO DAYS", "release_year", "2003" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "release_year", "2003" ], [ "VOICES OF A DISTANT STAR", "has_genre", "DRAMA" ], [ "VOICES OF A DISTANT STAR", "release_year", "2003" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "2003" ], [ "WUTHERING HEIGHTS", "has_genre", "DRAMA" ], [ "WUTHERING HEIGHTS", "release_year", "2003" ], [ "YOUNG ADAM", "has_genre", "DRAMA" ], [ "YOUNG ADAM", "release_year", "2003" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25535, 1950S 6721, 1972 15374, 2005 38707, ASYLUM 38578, BEAUTY SHOP 17939, BURT REYNOLDS 28094, DELIVERANCE 3677, FUZZ 19802, LOVE 20223, THE LONGEST YARD 24108, THE MAN 14967, THE NOTORIOUS BETTIE PAGE 2013, THE TREE OF LIFE src, edge_attr, dst 38707, release_year, 6721 38707, release_year, 15374 38578, release_year, 15374 28094, has_tags, 17939 28094, release_year, 6721 28094, starred_actors, 17939 3677, release_year, 6721 3677, starred_actors, 17939 19802, release_year, 15374 20223, has_tags, 17939 20223, release_year, 15374 20223, starred_actors, 17939 24108, release_year, 6721 24108, release_year, 15374 14967, has_tags, 25535 14967, release_year, 15374 2013, has_tags, 25535 2013, has_tags, 19802 Question: In what context are 1950S, BEAUTY SHOP, and FUZZ connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1950S", "BEAUTY SHOP", "FUZZ" ], "valid_edges": [ [ "ASYLUM", "release_year", "1972" ], [ "ASYLUM", "release_year", "2005" ], [ "BEAUTY SHOP", "release_year", "2005" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "release_year", "1972" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "FUZZ", "release_year", "1972" ], [ "FUZZ", "starred_actors", "BURT REYNOLDS" ], [ "LOVE", "release_year", "2005" ], [ "THE LONGEST YARD", "has_tags", "BURT REYNOLDS" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE LONGEST YARD", "starred_actors", "BURT REYNOLDS" ], [ "THE MAN", "release_year", "1972" ], [ "THE MAN", "release_year", "2005" ], [ "THE NOTORIOUS BETTIE PAGE", "has_tags", "1950S" ], [ "THE NOTORIOUS BETTIE PAGE", "release_year", "2005" ], [ "THE TREE OF LIFE", "has_tags", "1950S" ], [ "THE TREE OF LIFE", "has_tags", "LOVE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37224, 1990 30985, ADVENTURELAND 8841, AIR AMERICA 23942, ALL FOR THE WINNER 39869, ALMOST AN ANGEL 35673, ANOTHER 48 HRS. 38136, ARACHNOPHOBIA 35141, BASKET CASE 2 7380, BETSY'S WEDDING 18793, BILL HADER 16277, BIRD ON A WIRE 21490, BOOK OF LOVE 37451, CADILLAC MAN 26811, CLEAR HISTORY 30463, COMEDY 23734, COUPE DE VILLE 22142, CRAZY PEOPLE 8346, CRY-BABY 16536, CYRANO DE BERGERAC 777, DEATH IN BRUNSWICK 11380, DOWNTOWN 36212, DRAMA 31615, ERNEST GOES TO JAIL 12404, FAR OUT MAN 36067, FLASHBACK 600, FRANKENHOOKER 27618, FUNNY ABOUT LOVE 157, GHOST DAD 26909, GREEN CARD 28236, GREG MOTTOLA 38964, HEART CONDITION 30886, HOME ALONE 17037, HOUSE PARTY 31236, I BOUGHT A VAMPIRE MOTORCYCLE 38459, I LOVE YOU TO DEATH 30468, I'M ALL RIGHT JACK 7361, JOE VERSUS THE VOLCANO 4046, KINDERGARTEN COP 19450, LOOK WHO'S TALKING TOO 35654, LOOSE CANNONS 26370, MADHOUSE 15746, MEN AT WORK 19498, MERMAIDS 5211, MR. DESTINY 18524, MY BLUE HEAVEN 25997, NUNS ON THE RUN 4387, OPPORTUNITY KNOCKS 30091, PAUL 1804, POSTCARDS FROM THE EDGE 17605, PRETTY WOMAN 25436, PROBLEM CHILD 27014, PUMP UP THE VOLUME 24486, QUICK CHANGE 11728, REPOSSESSED 7913, SETH ROGEN 30672, SHORT TIME 33684, SIBLING RIVALRY 15127, SKI PATROL 26957, SPACED INVADERS 35875, SUPERBAD 23378, TAKING CARE OF BUSINESS 39976, TEENAGE MUTANT NINJA TURTLES 13521, THE ADVENTURES OF FORD FAIRLANE 20873, THE BONFIRE OF THE VANITIES 15307, THE DAYTRIPPERS 31555, THE FRESHMAN 2782, THE LONG WALK HOME 17833, THE SHRIMP ON THE BARBIE 22406, THE SPIRIT OF '76 11987, TRUST 31732, URANUS 3620, WELCOME HOME, ROXY CARMICHAEL 33070, WHERE THE HEART IS 32503, WHY ME? src, edge_attr, dst 30985, directed_by, 28236 30985, has_genre, 30463 30985, has_genre, 36212 30985, has_tags, 18793 30985, has_tags, 28236 30985, written_by, 28236 8841, has_genre, 30463 8841, release_year, 37224 23942, has_genre, 30463 23942, release_year, 37224 39869, has_genre, 30463 39869, release_year, 37224 35673, has_genre, 30463 35673, has_tags, 30463 35673, release_year, 37224 38136, has_genre, 30463 38136, has_tags, 30463 38136, release_year, 37224 35141, has_genre, 30463 35141, release_year, 37224 7380, has_genre, 30463 7380, release_year, 37224 16277, has_genre, 30463 16277, has_tags, 30463 16277, release_year, 37224 21490, has_genre, 30463 21490, release_year, 37224 37451, has_genre, 30463 37451, release_year, 37224 26811, directed_by, 28236 26811, has_genre, 30463 26811, has_tags, 18793 26811, has_tags, 28236 26811, starred_actors, 18793 23734, has_genre, 30463 23734, release_year, 37224 22142, has_genre, 30463 22142, release_year, 37224 8346, has_genre, 30463 8346, release_year, 37224 16536, has_genre, 30463 16536, release_year, 37224 777, has_genre, 30463 777, release_year, 37224 11380, has_genre, 30463 11380, release_year, 37224 31615, has_genre, 30463 31615, release_year, 37224 12404, has_genre, 30463 12404, release_year, 37224 36067, has_genre, 30463 36067, release_year, 37224 600, has_genre, 30463 600, release_year, 37224 27618, has_genre, 30463 27618, release_year, 37224 157, has_genre, 30463 157, release_year, 37224 26909, has_genre, 30463 26909, release_year, 37224 38964, has_genre, 30463 38964, release_year, 37224 30886, has_genre, 30463 30886, has_tags, 30463 30886, release_year, 37224 17037, has_genre, 30463 17037, release_year, 37224 31236, has_genre, 30463 31236, release_year, 37224 38459, has_genre, 30463 38459, release_year, 37224 30468, has_genre, 30463 7361, has_genre, 30463 7361, release_year, 37224 4046, has_genre, 30463 4046, has_tags, 30463 4046, release_year, 37224 19450, has_genre, 30463 19450, release_year, 37224 35654, has_genre, 30463 35654, release_year, 37224 26370, has_genre, 30463 26370, release_year, 37224 15746, has_genre, 30463 15746, release_year, 37224 19498, has_genre, 30463 19498, has_tags, 30463 19498, release_year, 37224 5211, has_genre, 30463 5211, release_year, 37224 18524, has_genre, 30463 18524, release_year, 37224 25997, has_genre, 30463 25997, release_year, 37224 4387, has_genre, 30463 4387, release_year, 37224 30091, directed_by, 28236 30091, has_tags, 28236 30091, has_tags, 7913 1804, has_genre, 30463 1804, release_year, 37224 17605, has_genre, 30463 17605, has_tags, 30463 17605, release_year, 37224 25436, has_genre, 30463 25436, release_year, 37224 27014, has_genre, 30463 27014, release_year, 37224 24486, has_genre, 30463 24486, release_year, 37224 11728, has_genre, 30463 11728, release_year, 37224 30672, has_genre, 30463 30672, release_year, 37224 33684, has_genre, 30463 33684, release_year, 37224 15127, has_genre, 30463 15127, release_year, 37224 26957, has_genre, 30463 26957, release_year, 37224 35875, directed_by, 28236 35875, has_genre, 30463 35875, has_tags, 30463 35875, has_tags, 28236 35875, has_tags, 7913 35875, written_by, 7913 23378, has_genre, 30463 23378, release_year, 37224 39976, has_genre, 30463 39976, release_year, 37224 13521, has_genre, 30463 13521, has_tags, 30463 13521, release_year, 37224 20873, has_genre, 30463 20873, release_year, 37224 15307, directed_by, 28236 15307, has_genre, 36212 15307, has_tags, 28236 15307, written_by, 28236 31555, has_genre, 30463 31555, release_year, 37224 2782, release_year, 37224 17833, has_genre, 30463 17833, release_year, 37224 22406, has_genre, 30463 22406, release_year, 37224 11987, has_genre, 30463 11987, release_year, 37224 31732, has_genre, 30463 31732, release_year, 37224 3620, has_genre, 30463 3620, release_year, 37224 33070, has_genre, 30463 33070, release_year, 37224 32503, has_genre, 30463 32503, release_year, 37224 Question: In what context are GREG MOTTOLA, I'M ALL RIGHT JACK, and THE LONG WALK HOME connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GREG MOTTOLA", "I'M ALL RIGHT JACK", "THE LONG WALK HOME" ], "valid_edges": [ [ "ADVENTURELAND", "directed_by", "GREG MOTTOLA" ], [ "ADVENTURELAND", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "DRAMA" ], [ "ADVENTURELAND", "has_tags", "BILL HADER" ], [ "ADVENTURELAND", "has_tags", "GREG MOTTOLA" ], [ "ADVENTURELAND", "written_by", "GREG MOTTOLA" ], [ "AIR AMERICA", "has_genre", "COMEDY" ], [ "AIR AMERICA", "release_year", "1990" ], [ "ALL FOR THE WINNER", "has_genre", "COMEDY" ], [ "ALL FOR THE WINNER", "release_year", "1990" ], [ "ALMOST AN ANGEL", "has_genre", "COMEDY" ], [ "ALMOST AN ANGEL", "release_year", "1990" ], [ "ANOTHER 48 HRS.", "has_genre", "COMEDY" ], [ "ANOTHER 48 HRS.", "has_tags", "COMEDY" ], [ "ANOTHER 48 HRS.", "release_year", "1990" ], [ "ARACHNOPHOBIA", "has_genre", "COMEDY" ], [ "ARACHNOPHOBIA", "has_tags", "COMEDY" ], [ "ARACHNOPHOBIA", "release_year", "1990" ], [ "BASKET CASE 2", "has_genre", "COMEDY" ], [ "BASKET CASE 2", "release_year", "1990" ], [ "BETSY'S WEDDING", "has_genre", "COMEDY" ], [ "BETSY'S WEDDING", "release_year", "1990" ], [ "BIRD ON A WIRE", "has_genre", "COMEDY" ], [ "BIRD ON A WIRE", "has_tags", "COMEDY" ], [ "BIRD ON A WIRE", "release_year", "1990" ], [ "BOOK OF LOVE", "has_genre", "COMEDY" ], [ "BOOK OF LOVE", "release_year", "1990" ], [ "CADILLAC MAN", "has_genre", "COMEDY" ], [ "CADILLAC MAN", "release_year", "1990" ], [ "CLEAR HISTORY", "directed_by", "GREG MOTTOLA" ], [ "CLEAR HISTORY", "has_genre", "COMEDY" ], [ "CLEAR HISTORY", "has_tags", "BILL HADER" ], [ "CLEAR HISTORY", "has_tags", "GREG MOTTOLA" ], [ "CLEAR HISTORY", "starred_actors", "BILL HADER" ], [ "COUPE DE VILLE", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "release_year", "1990" ], [ "CRAZY PEOPLE", "has_genre", "COMEDY" ], [ "CRAZY PEOPLE", "release_year", "1990" ], [ "CRY-BABY", "has_genre", "COMEDY" ], [ "CRY-BABY", "release_year", "1990" ], [ "CYRANO DE BERGERAC", "has_genre", "COMEDY" ], [ "CYRANO DE BERGERAC", "release_year", "1990" ], [ "DEATH IN BRUNSWICK", "has_genre", "COMEDY" ], [ "DEATH IN BRUNSWICK", "release_year", "1990" ], [ "DOWNTOWN", "has_genre", "COMEDY" ], [ "DOWNTOWN", "release_year", "1990" ], [ "ERNEST GOES TO JAIL", "has_genre", "COMEDY" ], [ "ERNEST GOES TO JAIL", "release_year", "1990" ], [ "FAR OUT MAN", "has_genre", "COMEDY" ], [ "FAR OUT MAN", "release_year", "1990" ], [ "FLASHBACK", "has_genre", "COMEDY" ], [ "FLASHBACK", "release_year", "1990" ], [ "FRANKENHOOKER", "has_genre", "COMEDY" ], [ "FRANKENHOOKER", "release_year", "1990" ], [ "FUNNY ABOUT LOVE", "has_genre", "COMEDY" ], [ "FUNNY ABOUT LOVE", "release_year", "1990" ], [ "GHOST DAD", "has_genre", "COMEDY" ], [ "GHOST DAD", "release_year", "1990" ], [ "GREEN CARD", "has_genre", "COMEDY" ], [ "GREEN CARD", "release_year", "1990" ], [ "HEART CONDITION", "has_genre", "COMEDY" ], [ "HEART CONDITION", "release_year", "1990" ], [ "HOME ALONE", "has_genre", "COMEDY" ], [ "HOME ALONE", "has_tags", "COMEDY" ], [ "HOME ALONE", "release_year", "1990" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "release_year", "1990" ], [ "I BOUGHT A VAMPIRE MOTORCYCLE", "has_genre", "COMEDY" ], [ "I BOUGHT A VAMPIRE MOTORCYCLE", "release_year", "1990" ], [ "I LOVE YOU TO DEATH", "has_genre", "COMEDY" ], [ "I LOVE YOU TO DEATH", "release_year", "1990" ], [ "I'M ALL RIGHT JACK", "has_genre", "COMEDY" ], [ "JOE VERSUS THE VOLCANO", "has_genre", "COMEDY" ], [ "JOE VERSUS THE VOLCANO", "release_year", "1990" ], [ "KINDERGARTEN COP", "has_genre", "COMEDY" ], [ "KINDERGARTEN COP", "has_tags", "COMEDY" ], [ "KINDERGARTEN COP", "release_year", "1990" ], [ "LOOK WHO'S TALKING TOO", "has_genre", "COMEDY" ], [ "LOOK WHO'S TALKING TOO", "release_year", "1990" ], [ "LOOSE CANNONS", "has_genre", "COMEDY" ], [ "LOOSE CANNONS", "release_year", "1990" ], [ "MADHOUSE", "has_genre", "COMEDY" ], [ "MADHOUSE", "release_year", "1990" ], [ "MEN AT WORK", "has_genre", "COMEDY" ], [ "MEN AT WORK", "release_year", "1990" ], [ "MERMAIDS", "has_genre", "COMEDY" ], [ "MERMAIDS", "has_tags", "COMEDY" ], [ "MERMAIDS", "release_year", "1990" ], [ "MR. DESTINY", "has_genre", "COMEDY" ], [ "MR. DESTINY", "release_year", "1990" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "release_year", "1990" ], [ "NUNS ON THE RUN", "has_genre", "COMEDY" ], [ "NUNS ON THE RUN", "release_year", "1990" ], [ "OPPORTUNITY KNOCKS", "has_genre", "COMEDY" ], [ "OPPORTUNITY KNOCKS", "release_year", "1990" ], [ "PAUL", "directed_by", "GREG MOTTOLA" ], [ "PAUL", "has_tags", "GREG MOTTOLA" ], [ "PAUL", "has_tags", "SETH ROGEN" ], [ "POSTCARDS FROM THE EDGE", "has_genre", "COMEDY" ], [ "POSTCARDS FROM THE EDGE", "release_year", "1990" ], [ "PRETTY WOMAN", "has_genre", "COMEDY" ], [ "PRETTY WOMAN", "has_tags", "COMEDY" ], [ "PRETTY WOMAN", "release_year", "1990" ], [ "PROBLEM CHILD", "has_genre", "COMEDY" ], [ "PROBLEM CHILD", "release_year", "1990" ], [ "PUMP UP THE VOLUME", "has_genre", "COMEDY" ], [ "PUMP UP THE VOLUME", "release_year", "1990" ], [ "QUICK CHANGE", "has_genre", "COMEDY" ], [ "QUICK CHANGE", "release_year", "1990" ], [ "REPOSSESSED", "has_genre", "COMEDY" ], [ "REPOSSESSED", "release_year", "1990" ], [ "SHORT TIME", "has_genre", "COMEDY" ], [ "SHORT TIME", "release_year", "1990" ], [ "SIBLING RIVALRY", "has_genre", "COMEDY" ], [ "SIBLING RIVALRY", "release_year", "1990" ], [ "SKI PATROL", "has_genre", "COMEDY" ], [ "SKI PATROL", "release_year", "1990" ], [ "SPACED INVADERS", "has_genre", "COMEDY" ], [ "SPACED INVADERS", "release_year", "1990" ], [ "SUPERBAD", "directed_by", "GREG MOTTOLA" ], [ "SUPERBAD", "has_genre", "COMEDY" ], [ "SUPERBAD", "has_tags", "COMEDY" ], [ "SUPERBAD", "has_tags", "GREG MOTTOLA" ], [ "SUPERBAD", "has_tags", "SETH ROGEN" ], [ "SUPERBAD", "written_by", "SETH ROGEN" ], [ "TAKING CARE OF BUSINESS", "has_genre", "COMEDY" ], [ "TAKING CARE OF BUSINESS", "release_year", "1990" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "COMEDY" ], [ "TEENAGE MUTANT NINJA TURTLES", "release_year", "1990" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "release_year", "1990" ], [ "THE BONFIRE OF THE VANITIES", "has_genre", "COMEDY" ], [ "THE BONFIRE OF THE VANITIES", "release_year", "1990" ], [ "THE DAYTRIPPERS", "directed_by", "GREG MOTTOLA" ], [ "THE DAYTRIPPERS", "has_genre", "DRAMA" ], [ "THE DAYTRIPPERS", "has_tags", "GREG MOTTOLA" ], [ "THE DAYTRIPPERS", "written_by", "GREG MOTTOLA" ], [ "THE FRESHMAN", "has_genre", "COMEDY" ], [ "THE FRESHMAN", "release_year", "1990" ], [ "THE LONG WALK HOME", "release_year", "1990" ], [ "THE SHRIMP ON THE BARBIE", "has_genre", "COMEDY" ], [ "THE SHRIMP ON THE BARBIE", "release_year", "1990" ], [ "THE SPIRIT OF '76", "has_genre", "COMEDY" ], [ "THE SPIRIT OF '76", "release_year", "1990" ], [ "TRUST", "has_genre", "COMEDY" ], [ "TRUST", "release_year", "1990" ], [ "URANUS", "has_genre", "COMEDY" ], [ "URANUS", "release_year", "1990" ], [ "WELCOME HOME, ROXY CARMICHAEL", "has_genre", "COMEDY" ], [ "WELCOME HOME, ROXY CARMICHAEL", "release_year", "1990" ], [ "WHERE THE HEART IS", "has_genre", "COMEDY" ], [ "WHERE THE HEART IS", "release_year", "1990" ], [ "WHY ME?", "has_genre", "COMEDY" ], [ "WHY ME?", "release_year", "1990" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 772, ALAN RUDOLPH 5905, BUENA VISTA SOCIAL CLUB 207, CHOOSE ME 17958, FLASHPOINT 29274, JON CRYER 10015, KRIS KRISTOFFERSON 39689, LATIN AMERICA 14351, MUSICIANS 18680, NO SMALL AFFAIR 36572, RIP TORN 11725, SONGWRITER 30297, THE WAR ON DEMOCRACY src, edge_attr, dst 5905, has_tags, 39689 5905, has_tags, 14351 207, directed_by, 772 207, release_year, 24525 207, written_by, 772 17958, release_year, 24525 17958, starred_actors, 10015 17958, starred_actors, 36572 18680, release_year, 24525 18680, starred_actors, 29274 11725, directed_by, 772 11725, has_tags, 14351 11725, release_year, 24525 11725, starred_actors, 10015 11725, starred_actors, 36572 30297, has_tags, 39689 Question: In what context are JON CRYER, SONGWRITER, and THE WAR ON DEMOCRACY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JON CRYER", "SONGWRITER", "THE WAR ON DEMOCRACY" ], "valid_edges": [ [ "BUENA VISTA SOCIAL CLUB", "has_tags", "LATIN AMERICA" ], [ "BUENA VISTA SOCIAL CLUB", "has_tags", "MUSICIANS" ], [ "CHOOSE ME", "directed_by", "ALAN RUDOLPH" ], [ "CHOOSE ME", "release_year", "1984" ], [ "CHOOSE ME", "written_by", "ALAN RUDOLPH" ], [ "FLASHPOINT", "release_year", "1984" ], [ "FLASHPOINT", "starred_actors", "KRIS KRISTOFFERSON" ], [ "FLASHPOINT", "starred_actors", "RIP TORN" ], [ "NO SMALL AFFAIR", "release_year", "1984" ], [ "NO SMALL AFFAIR", "starred_actors", "JON CRYER" ], [ "SONGWRITER", "directed_by", "ALAN RUDOLPH" ], [ "SONGWRITER", "has_tags", "MUSICIANS" ], [ "SONGWRITER", "release_year", "1984" ], [ "SONGWRITER", "starred_actors", "KRIS KRISTOFFERSON" ], [ "SONGWRITER", "starred_actors", "RIP TORN" ], [ "THE WAR ON DEMOCRACY", "has_tags", "LATIN AMERICA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 36212, DRAMA 16120, FRANK BUTLER 15642, GOLDEN EARRINGS 23263, RAY MILLAND 6572, THE EARTH IS A SINFUL SONG 1368, THE MILKY WAY 39538, THE THING WITH TWO HEADS 7476, WES BISHOP src, edge_attr, dst 7977, has_genre, 36212 15642, has_tags, 23263 15642, starred_actors, 23263 15642, written_by, 16120 6572, has_genre, 36212 1368, release_year, 7977 1368, written_by, 16120 39538, has_tags, 23263 39538, starred_actors, 23263 39538, written_by, 7476 Question: In what context are FRANK BUTLER, THE EARTH IS A SINFUL SONG, and WES BISHOP connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FRANK BUTLER", "THE EARTH IS A SINFUL SONG", "WES BISHOP" ], "valid_edges": [ [ "1969", "has_genre", "DRAMA" ], [ "GOLDEN EARRINGS", "has_tags", "RAY MILLAND" ], [ "GOLDEN EARRINGS", "starred_actors", "RAY MILLAND" ], [ "GOLDEN EARRINGS", "written_by", "FRANK BUTLER" ], [ "THE EARTH IS A SINFUL SONG", "has_genre", "DRAMA" ], [ "THE MILKY WAY", "release_year", "1969" ], [ "THE MILKY WAY", "written_by", "FRANK BUTLER" ], [ "THE THING WITH TWO HEADS", "has_tags", "RAY MILLAND" ], [ "THE THING WITH TWO HEADS", "starred_actors", "RAY MILLAND" ], [ "THE THING WITH TWO HEADS", "written_by", "WES BISHOP" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9855, AMSTERDAMNED 36212, DRAMA 31008, DUTCH 5870, HORROR 33981, PARANORMAL ACTIVITY 3 36186, PETER FAIMAN 5964, SHIRLEY DOUGLAS 13703, THE LAW OF ENCLOSURES src, edge_attr, dst 9855, has_genre, 5870 9855, in_language, 31008 31008, directed_by, 36186 31008, has_genre, 36212 33981, has_genre, 5870 33981, has_tags, 5870 13703, has_genre, 36212 13703, starred_actors, 5964 Question: For what reason are PARANORMAL ACTIVITY 3, PETER FAIMAN, and SHIRLEY DOUGLAS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "PARANORMAL ACTIVITY 3", "PETER FAIMAN", "SHIRLEY DOUGLAS" ], "valid_edges": [ [ "AMSTERDAMNED", "has_genre", "HORROR" ], [ "AMSTERDAMNED", "in_language", "DUTCH" ], [ "DUTCH", "directed_by", "PETER FAIMAN" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "PARANORMAL ACTIVITY 3", "has_genre", "HORROR" ], [ "PARANORMAL ACTIVITY 3", "has_tags", "HORROR" ], [ "THE LAW OF ENCLOSURES", "has_genre", "DRAMA" ], [ "THE LAW OF ENCLOSURES", "starred_actors", "SHIRLEY DOUGLAS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 17315, 2007 36876, ATTACK 11473, CAPTAIN NEWMAN, M.D. 3567, DAYS OF GLORY 34494, EDDIE ALBERT 11021, EYE IN THE SKY 14180, FORCE 10 FROM NAVARONE 8287, GREGORY PECK 19463, HEDD WYN 676, KATE TSUI 33297, OPERATION PETTICOAT 1916, ORDERS TO KILL 6064, PAUL TURNER 23515, PORK CHOP HILL 27043, PT 109 31405, THE CARDINAL 6424, THE GREAT ESCAPE 23037, THE MAN IN THE GRAY FLANNEL SUIT 3373, THE PURPLE PLAIN 2813, THE SEA WOLVES 16761, TONY CURTIS 38352, TWELVE O'CLOCK HIGH 22214, WAR src, edge_attr, dst 36876, has_genre, 22214 36876, starred_actors, 34494 11473, has_genre, 22214 11473, release_year, 13504 11473, starred_actors, 34494 11473, starred_actors, 8287 11473, starred_actors, 16761 3567, has_genre, 22214 3567, has_tags, 8287 3567, has_tags, 22214 3567, starred_actors, 8287 11021, release_year, 17315 11021, starred_actors, 676 14180, has_genre, 22214 14180, has_tags, 8287 19463, directed_by, 6064 19463, has_genre, 22214 33297, has_genre, 22214 33297, has_tags, 16761 33297, starred_actors, 16761 1916, has_genre, 22214 1916, starred_actors, 34494 23515, has_genre, 22214 23515, starred_actors, 8287 27043, has_genre, 22214 27043, release_year, 13504 31405, has_genre, 22214 31405, release_year, 13504 6424, has_tags, 22214 6424, release_year, 13504 23037, has_genre, 22214 23037, starred_actors, 8287 3373, has_genre, 22214 3373, starred_actors, 8287 2813, has_genre, 22214 2813, starred_actors, 8287 38352, has_genre, 22214 38352, has_tags, 8287 38352, starred_actors, 8287 22214, release_year, 17315 Question: How are CAPTAIN NEWMAN, M.D., KATE TSUI, and PAUL TURNER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CAPTAIN NEWMAN, M.D.", "KATE TSUI", "PAUL TURNER" ], "valid_edges": [ [ "ATTACK", "has_genre", "WAR" ], [ "ATTACK", "starred_actors", "EDDIE ALBERT" ], [ "CAPTAIN NEWMAN, M.D.", "has_genre", "WAR" ], [ "CAPTAIN NEWMAN, M.D.", "release_year", "1963" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "EDDIE ALBERT" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "GREGORY PECK" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "TONY CURTIS" ], [ "DAYS OF GLORY", "has_genre", "WAR" ], [ "DAYS OF GLORY", "has_tags", "GREGORY PECK" ], [ "DAYS OF GLORY", "has_tags", "WAR" ], [ "DAYS OF GLORY", "starred_actors", "GREGORY PECK" ], [ "EYE IN THE SKY", "release_year", "2007" ], [ "EYE IN THE SKY", "starred_actors", "KATE TSUI" ], [ "FORCE 10 FROM NAVARONE", "has_genre", "WAR" ], [ "FORCE 10 FROM NAVARONE", "has_tags", "GREGORY PECK" ], [ "HEDD WYN", "directed_by", "PAUL TURNER" ], [ "HEDD WYN", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_tags", "TONY CURTIS" ], [ "OPERATION PETTICOAT", "starred_actors", "TONY CURTIS" ], [ "ORDERS TO KILL", "has_genre", "WAR" ], [ "ORDERS TO KILL", "starred_actors", "EDDIE ALBERT" ], [ "PORK CHOP HILL", "has_genre", "WAR" ], [ "PORK CHOP HILL", "starred_actors", "GREGORY PECK" ], [ "PT 109", "has_genre", "WAR" ], [ "PT 109", "release_year", "1963" ], [ "THE CARDINAL", "has_genre", "WAR" ], [ "THE CARDINAL", "release_year", "1963" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "release_year", "1963" ], [ "THE MAN IN THE GRAY FLANNEL SUIT", "has_genre", "WAR" ], [ "THE MAN IN THE GRAY FLANNEL SUIT", "starred_actors", "GREGORY PECK" ], [ "THE PURPLE PLAIN", "has_genre", "WAR" ], [ "THE PURPLE PLAIN", "starred_actors", "GREGORY PECK" ], [ "THE SEA WOLVES", "has_genre", "WAR" ], [ "THE SEA WOLVES", "starred_actors", "GREGORY PECK" ], [ "TWELVE O'CLOCK HIGH", "has_genre", "WAR" ], [ "TWELVE O'CLOCK HIGH", "has_tags", "GREGORY PECK" ], [ "TWELVE O'CLOCK HIGH", "starred_actors", "GREGORY PECK" ], [ "WAR", "release_year", "2007" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 34060, CREATION 13280, DENNIS THE MENACE 36212, DRAMA 30639, HANK KETCHAM 38634, JON AMIEL 5873, SOMMERSBY 30805, THE NEW GIRLFRIEND src, edge_attr, dst 34060, directed_by, 38634 34060, has_genre, 36212 34060, has_tags, 38634 34060, written_by, 38634 13280, release_year, 24438 13280, written_by, 30639 5873, directed_by, 38634 5873, has_genre, 36212 5873, release_year, 24438 30805, has_genre, 36212 Question: In what context are HANK KETCHAM, JON AMIEL, and THE NEW GIRLFRIEND connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HANK KETCHAM", "JON AMIEL", "THE NEW GIRLFRIEND" ], "valid_edges": [ [ "CREATION", "directed_by", "JON AMIEL" ], [ "CREATION", "has_genre", "DRAMA" ], [ "CREATION", "has_tags", "JON AMIEL" ], [ "CREATION", "written_by", "JON AMIEL" ], [ "DENNIS THE MENACE", "release_year", "1993" ], [ "DENNIS THE MENACE", "written_by", "HANK KETCHAM" ], [ "SOMMERSBY", "directed_by", "JON AMIEL" ], [ "SOMMERSBY", "has_genre", "DRAMA" ], [ "SOMMERSBY", "release_year", "1993" ], [ "THE NEW GIRLFRIEND", "has_genre", "DRAMA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 31362, CLARK GABLE 28538, DANCING LADY 15791, DINNER AT EIGHT 12841, DOCUMENTARY 20824, FLYING DOWN TO RIO 30016, H.W. HANEMANN 16644, JOHN BARRYMORE 23106, LAND WITHOUT BREAD 22149, LIONEL BARRYMORE 31195, LOOKING FORWARD 20443, NIGHT FLIGHT 29373, STEAM OF LIFE 29621, THE STRANGER'S RETURN src, edge_attr, dst 28538, release_year, 15506 28538, starred_actors, 31362 15791, release_year, 15506 15791, starred_actors, 16644 20824, release_year, 15506 20824, written_by, 30016 23106, has_genre, 12841 23106, release_year, 15506 31195, release_year, 15506 31195, starred_actors, 22149 20443, release_year, 15506 20443, starred_actors, 31362 20443, starred_actors, 16644 20443, starred_actors, 22149 29373, has_genre, 12841 29621, release_year, 15506 29621, starred_actors, 22149 Question: How are H.W. HANEMANN, NIGHT FLIGHT, and STEAM OF LIFE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "H.W. HANEMANN", "NIGHT FLIGHT", "STEAM OF LIFE" ], "valid_edges": [ [ "DANCING LADY", "release_year", "1933" ], [ "DANCING LADY", "starred_actors", "CLARK GABLE" ], [ "DINNER AT EIGHT", "release_year", "1933" ], [ "DINNER AT EIGHT", "starred_actors", "JOHN BARRYMORE" ], [ "FLYING DOWN TO RIO", "release_year", "1933" ], [ "FLYING DOWN TO RIO", "written_by", "H.W. HANEMANN" ], [ "LAND WITHOUT BREAD", "has_genre", "DOCUMENTARY" ], [ "LAND WITHOUT BREAD", "release_year", "1933" ], [ "LOOKING FORWARD", "release_year", "1933" ], [ "LOOKING FORWARD", "starred_actors", "LIONEL BARRYMORE" ], [ "NIGHT FLIGHT", "release_year", "1933" ], [ "NIGHT FLIGHT", "starred_actors", "CLARK GABLE" ], [ "NIGHT FLIGHT", "starred_actors", "JOHN BARRYMORE" ], [ "NIGHT FLIGHT", "starred_actors", "LIONEL BARRYMORE" ], [ "STEAM OF LIFE", "has_genre", "DOCUMENTARY" ], [ "THE STRANGER'S RETURN", "release_year", "1933" ], [ "THE STRANGER'S RETURN", "starred_actors", "LIONEL BARRYMORE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 19407, 8½ 24626, A CHILD IS WAITING 39646, ALL THE WAY HOME 34556, AMERICA AMERICA 13570, BILLY LIAR 19510, CLEOPATRA 36212, DRAMA 20659, HIGH AND LOW 39069, LARS AND THE REAL GIRL 5885, LOVE WITH THE PROPER STRANGER 1349, NANCY OLIVER 12572, SOLDIER IN THE RAIN 35252, STOP TRAIN 349 31405, THE CARDINAL 39534, THE CARETAKERS 2893, THE CRAWLING HAND 28928, THE FIRE WITHIN 12999, THE ORGANIZER 32147, THE SERVANT 23091, THE V.I.P.S 22999, TOYS IN THE ATTIC 27794, WATER FOR ELEPHANTS 35124, YOUNG APHRODITES src, edge_attr, dst 19407, has_genre, 36212 19407, release_year, 13504 24626, has_genre, 36212 24626, release_year, 13504 39646, has_genre, 36212 39646, release_year, 13504 34556, has_genre, 36212 34556, release_year, 13504 13570, has_genre, 36212 13570, release_year, 13504 19510, has_genre, 36212 19510, release_year, 13504 20659, has_genre, 36212 20659, release_year, 13504 39069, has_genre, 36212 39069, written_by, 1349 5885, has_genre, 36212 5885, release_year, 13504 12572, has_genre, 36212 12572, release_year, 13504 35252, has_genre, 36212 35252, release_year, 13504 31405, has_genre, 36212 31405, release_year, 13504 39534, has_genre, 36212 39534, release_year, 13504 2893, release_year, 13504 28928, has_genre, 36212 28928, release_year, 13504 12999, has_genre, 36212 12999, release_year, 13504 32147, has_genre, 36212 32147, release_year, 13504 23091, has_genre, 36212 23091, release_year, 13504 22999, has_genre, 36212 22999, release_year, 13504 27794, has_genre, 36212 35124, has_genre, 36212 35124, release_year, 13504 Question: For what reason are NANCY OLIVER, THE CRAWLING HAND, and WATER FOR ELEPHANTS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "NANCY OLIVER", "THE CRAWLING HAND", "WATER FOR ELEPHANTS" ], "valid_edges": [ [ "8½", "has_genre", "DRAMA" ], [ "8½", "release_year", "1963" ], [ "A CHILD IS WAITING", "has_genre", "DRAMA" ], [ "A CHILD IS WAITING", "release_year", "1963" ], [ "ALL THE WAY HOME", "has_genre", "DRAMA" ], [ "ALL THE WAY HOME", "release_year", "1963" ], [ "AMERICA AMERICA", "has_genre", "DRAMA" ], [ "AMERICA AMERICA", "release_year", "1963" ], [ "BILLY LIAR", "has_genre", "DRAMA" ], [ "BILLY LIAR", "release_year", "1963" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "1963" ], [ "HIGH AND LOW", "has_genre", "DRAMA" ], [ "HIGH AND LOW", "release_year", "1963" ], [ "LARS AND THE REAL GIRL", "has_genre", "DRAMA" ], [ "LARS AND THE REAL GIRL", "written_by", "NANCY OLIVER" ], [ "LOVE WITH THE PROPER STRANGER", "has_genre", "DRAMA" ], [ "LOVE WITH THE PROPER STRANGER", "release_year", "1963" ], [ "SOLDIER IN THE RAIN", "has_genre", "DRAMA" ], [ "SOLDIER IN THE RAIN", "release_year", "1963" ], [ "STOP TRAIN 349", "has_genre", "DRAMA" ], [ "STOP TRAIN 349", "release_year", "1963" ], [ "THE CARDINAL", "has_genre", "DRAMA" ], [ "THE CARDINAL", "release_year", "1963" ], [ "THE CARETAKERS", "has_genre", "DRAMA" ], [ "THE CARETAKERS", "release_year", "1963" ], [ "THE CRAWLING HAND", "release_year", "1963" ], [ "THE FIRE WITHIN", "has_genre", "DRAMA" ], [ "THE FIRE WITHIN", "release_year", "1963" ], [ "THE ORGANIZER", "has_genre", "DRAMA" ], [ "THE ORGANIZER", "release_year", "1963" ], [ "THE SERVANT", "has_genre", "DRAMA" ], [ "THE SERVANT", "release_year", "1963" ], [ "THE V.I.P.S", "has_genre", "DRAMA" ], [ "THE V.I.P.S", "release_year", "1963" ], [ "TOYS IN THE ATTIC", "has_genre", "DRAMA" ], [ "TOYS IN THE ATTIC", "release_year", "1963" ], [ "WATER FOR ELEPHANTS", "has_genre", "DRAMA" ], [ "YOUNG APHRODITES", "has_genre", "DRAMA" ], [ "YOUNG APHRODITES", "release_year", "1963" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15374, 2005 35798, 2010 28189, A LITTLE TRIP TO HEAVEN 29638, ALICE IN WONDERLAND 14880, AND SOON THE DARKNESS 28274, ASSASSINATION OF A HIGH SCHOOL PRESIDENT 37687, BALTASAR KORMÁKUR 30335, BE WITH ME 24260, CEREMONY 5840, CERTIFIED COPY 6521, DAYDREAM NATION 16522, DOMINO 31783, ENGLISH 35256, GAME OF DEATH 24815, GOING THE DISTANCE 37827, HIGH SCHOOL 15066, INHALE 37419, IT'S A WONDERFUL AFTERLIFE 5830, LEMMY 29987, LET ME IN 37130, LOOK BOTH WAYS 13531, MATCH POINT 36301, NEDS 24218, NEVERWAS 21568, ON A CLEAR DAY 32901, ON TOUR 26227, PETER MULLAN 13832, REECE THOMPSON 34806, ROOM IN ROME 25509, THE DEBT 8022, THE NEW WORLD 23343, THE WOLFMAN 24521, THESE GIRLS 6279, YOU WILL MEET A TALL DARK STRANGER src, edge_attr, dst 28189, directed_by, 37687 28189, release_year, 15374 28189, written_by, 37687 29638, in_language, 31783 29638, release_year, 35798 14880, in_language, 31783 14880, release_year, 35798 28274, has_tags, 37827 28274, starred_actors, 13832 30335, in_language, 31783 30335, release_year, 15374 24260, release_year, 35798 24260, starred_actors, 13832 5840, in_language, 31783 5840, release_year, 35798 6521, release_year, 35798 6521, starred_actors, 13832 16522, in_language, 31783 16522, release_year, 15374 35256, in_language, 31783 35256, release_year, 35798 24815, in_language, 31783 24815, release_year, 35798 37827, release_year, 35798 15066, directed_by, 37687 15066, release_year, 35798 37419, in_language, 31783 37419, release_year, 35798 5830, in_language, 31783 5830, release_year, 35798 29987, in_language, 31783 29987, release_year, 35798 37130, in_language, 31783 37130, release_year, 15374 13531, in_language, 31783 13531, release_year, 15374 36301, directed_by, 26227 36301, in_language, 31783 36301, release_year, 35798 36301, written_by, 26227 24218, in_language, 31783 24218, release_year, 15374 21568, in_language, 31783 21568, release_year, 15374 21568, starred_actors, 26227 32901, in_language, 31783 32901, release_year, 35798 34806, in_language, 31783 34806, release_year, 35798 25509, in_language, 31783 25509, release_year, 35798 8022, in_language, 31783 8022, release_year, 15374 23343, in_language, 31783 23343, release_year, 35798 24521, in_language, 31783 24521, release_year, 15374 6279, in_language, 31783 6279, release_year, 35798 Question: How are INHALE, ON A CLEAR DAY, and REECE THOMPSON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "INHALE", "ON A CLEAR DAY", "REECE THOMPSON" ], "valid_edges": [ [ "A LITTLE TRIP TO HEAVEN", "directed_by", "BALTASAR KORMÁKUR" ], [ "A LITTLE TRIP TO HEAVEN", "release_year", "2005" ], [ "A LITTLE TRIP TO HEAVEN", "written_by", "BALTASAR KORMÁKUR" ], [ "ALICE IN WONDERLAND", "in_language", "ENGLISH" ], [ "ALICE IN WONDERLAND", "release_year", "2010" ], [ "AND SOON THE DARKNESS", "in_language", "ENGLISH" ], [ "AND SOON THE DARKNESS", "release_year", "2010" ], [ "ASSASSINATION OF A HIGH SCHOOL PRESIDENT", "has_tags", "HIGH SCHOOL" ], [ "ASSASSINATION OF A HIGH SCHOOL PRESIDENT", "starred_actors", "REECE THOMPSON" ], [ "BE WITH ME", "in_language", "ENGLISH" ], [ "BE WITH ME", "release_year", "2005" ], [ "CEREMONY", "release_year", "2010" ], [ "CEREMONY", "starred_actors", "REECE THOMPSON" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "release_year", "2010" ], [ "DAYDREAM NATION", "release_year", "2010" ], [ "DAYDREAM NATION", "starred_actors", "REECE THOMPSON" ], [ "DOMINO", "in_language", "ENGLISH" ], [ "DOMINO", "release_year", "2005" ], [ "GAME OF DEATH", "in_language", "ENGLISH" ], [ "GAME OF DEATH", "release_year", "2010" ], [ "GOING THE DISTANCE", "in_language", "ENGLISH" ], [ "GOING THE DISTANCE", "release_year", "2010" ], [ "HIGH SCHOOL", "release_year", "2010" ], [ "INHALE", "directed_by", "BALTASAR KORMÁKUR" ], [ "INHALE", "release_year", "2010" ], [ "IT'S A WONDERFUL AFTERLIFE", "in_language", "ENGLISH" ], [ "IT'S A WONDERFUL AFTERLIFE", "release_year", "2010" ], [ "LEMMY", "in_language", "ENGLISH" ], [ "LEMMY", "release_year", "2010" ], [ "LET ME IN", "in_language", "ENGLISH" ], [ "LET ME IN", "release_year", "2010" ], [ "LOOK BOTH WAYS", "in_language", "ENGLISH" ], [ "LOOK BOTH WAYS", "release_year", "2005" ], [ "MATCH POINT", "in_language", "ENGLISH" ], [ "MATCH POINT", "release_year", "2005" ], [ "NEDS", "directed_by", "PETER MULLAN" ], [ "NEDS", "in_language", "ENGLISH" ], [ "NEDS", "release_year", "2010" ], [ "NEDS", "written_by", "PETER MULLAN" ], [ "NEVERWAS", "in_language", "ENGLISH" ], [ "NEVERWAS", "release_year", "2005" ], [ "ON A CLEAR DAY", "in_language", "ENGLISH" ], [ "ON A CLEAR DAY", "release_year", "2005" ], [ "ON A CLEAR DAY", "starred_actors", "PETER MULLAN" ], [ "ON TOUR", "in_language", "ENGLISH" ], [ "ON TOUR", "release_year", "2010" ], [ "ROOM IN ROME", "in_language", "ENGLISH" ], [ "ROOM IN ROME", "release_year", "2010" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2010" ], [ "THE NEW WORLD", "in_language", "ENGLISH" ], [ "THE NEW WORLD", "release_year", "2005" ], [ "THE WOLFMAN", "in_language", "ENGLISH" ], [ "THE WOLFMAN", "release_year", "2010" ], [ "THESE GIRLS", "in_language", "ENGLISH" ], [ "THESE GIRLS", "release_year", "2005" ], [ "YOU WILL MEET A TALL DARK STRANGER", "in_language", "ENGLISH" ], [ "YOU WILL MEET A TALL DARK STRANGER", "release_year", "2010" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 27261, 2009 29424, 2011 36438, COMMAND PERFORMANCE 38780, DETENTION 36402, DIRECT CONTACT 31470, DOLPH LUNDGREN 24563, FULL BODY MASSAGE 21083, NOTHING PERSONAL 5538, QUEEN TO PLAY 7240, THE GIRL WITH THE DRAGON TATTOO 15562, THE ROAD src, edge_attr, dst 36438, directed_by, 31470 36438, release_year, 27261 36438, starred_actors, 31470 36438, written_by, 31470 38780, release_year, 29424 38780, starred_actors, 31470 36402, release_year, 27261 36402, starred_actors, 31470 24563, release_year, 3702 21083, release_year, 3702 21083, release_year, 27261 5538, release_year, 27261 7240, release_year, 27261 7240, release_year, 29424 15562, release_year, 27261 15562, release_year, 29424 Question: In what context are DETENTION, FULL BODY MASSAGE, and QUEEN TO PLAY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DETENTION", "FULL BODY MASSAGE", "QUEEN TO PLAY" ], "valid_edges": [ [ "COMMAND PERFORMANCE", "directed_by", "DOLPH LUNDGREN" ], [ "COMMAND PERFORMANCE", "release_year", "2009" ], [ "COMMAND PERFORMANCE", "starred_actors", "DOLPH LUNDGREN" ], [ "COMMAND PERFORMANCE", "written_by", "DOLPH LUNDGREN" ], [ "DETENTION", "release_year", "2011" ], [ "DETENTION", "starred_actors", "DOLPH LUNDGREN" ], [ "DIRECT CONTACT", "release_year", "2009" ], [ "DIRECT CONTACT", "starred_actors", "DOLPH LUNDGREN" ], [ "FULL BODY MASSAGE", "release_year", "1995" ], [ "NOTHING PERSONAL", "release_year", "1995" ], [ "NOTHING PERSONAL", "release_year", "2009" ], [ "QUEEN TO PLAY", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2011" ], [ "THE ROAD", "release_year", "2009" ], [ "THE ROAD", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 3702, 1995 18899, A BUCKET OF BLOOD 30407, ALIEN 9493, ALLEN PAYNE 10045, BD-R 19826, BLACK DEATH 26014, BLOOD OF THE VAMPIRE 32620, BUBBA HO-TEP 13138, CANNIBALISM 37126, CASTLE FREAK 37912, CAT PEOPLE 38158, DAVID HILLENBRAND 4381, DEAD OF NIGHT 27143, DEMENTIA 13 8381, DETOUR 23807, DOCTOR X 3154, DONOVAN'S BRAIN 34827, DR. JEKYLL AND MR. HYDE 36920, DRACULA HAS RISEN FROM THE GRAVE 37707, DRACULA'S DAUGHTER 24825, EVOLVER 29503, EYE OF THE DEVIL 24540, EYES WITHOUT A FACE 4653, FAY WRAY 32144, FRANKENSTEIN MUST BE DESTROYED 5291, FREAKS 38609, GALAXY OF TERROR 12378, HANDS OF THE RIPPER 13990, HIDEAWAY 39972, HOLLOW MAN 5870, HORROR 22421, HORROR EXPRESS 10955, HOUSE OF USHER 9686, HOUSE OF WAX 33663, ICE CREAM MAN 33269, ISLAND OF LOST SOULS 35018, KING COBRA 30645, LIONEL ATWILL 33627, LORD OF ILLUSIONS 40127, MACABRE 17728, MAD LOVE 26370, MADHOUSE 25643, MARK OF THE VAMPIRE 3129, MAXIMUM OVERDRIVE 13889, MICHAEL CURTIZ 18744, MURDERS IN THE RUE MORGUE 16462, MYSTERY OF THE WAX MUSEUM 17189, NIGHT OF THE DEMONS 9330, NIGHT OF THE LEPUS 32988, NIGHT OF THE LIVING DEAD 32891, NOSFERATU 19017, PEEPING TOM 16004, PLANET TERROR 13060, RAVENOUS 5897, REPULSION 7531, SPECIES 8436, SPIRITS OF THE DEAD 32367, STAGE FRIGHT 39265, STORAGE 24 34349, SVENGALI 4938, TALES FROM THE HOOD 14072, THE ABOMINABLE DR. PHIBES 12781, THE ALLIGATOR PEOPLE 13151, THE BAD SEED 17361, THE BRAIN THAT WOULDN'T DIE 25829, THE CABINET OF DR. CALIGARI 31239, THE CAT AND THE CANARY 38676, THE CREEPING FLESH 24990, THE CURSE OF FRANKENSTEIN 38265, THE DEVIL-DOLL 32732, THE DOCTOR AND THE DEVILS 23327, THE FEARLESS VAMPIRE KILLERS 28048, THE GHOST BREAKERS 10613, THE GHOST OF FRANKENSTEIN 14113, THE GHOUL 14382, THE GORGON 25175, THE HAUNTED PALACE 11787, THE HAUNTING 31283, THE HOUND OF THE BASKERVILLES 22212, THE HOUSE THAT DRIPPED BLOOD 32595, THE HOWLING 15198, THE HUNCHBACK OF NOTRE DAME 29358, THE HUNGER 27780, THE INNOCENTS 34005, THE INVISIBLE MAN 8623, THE LEGEND OF HELL HOUSE 33794, THE LITTLE SHOP OF HORRORS 29109, THE LODGER 26566, THE MANGLER 11243, THE MASQUE OF THE RED DEATH 12785, THE MONSTER WALKS 26820, THE MUMMY 27182, THE NATURE OF THE BEAST 9420, THE OLD DARK HOUSE 8727, THE PICTURE OF DORIAN GRAY 1565, THE PLAGUE OF THE ZOMBIES 22294, THE PROPHECY 18162, THE RAVEN 10186, THE REVENGE OF FRANKENSTEIN 1143, THE SEVENTH VICTIM 23847, THE STEPFORD WIVES 23260, THE SWARM 33991, THE TERROR 19823, THE UNKNOWN 39200, THE VAMPIRE BAT 13780, THE WALKING DEAD 22751, THE WICKER MAN 6833, THE WITCHES 3594, THEATRE OF BLOOD 14444, THEM! 1596, TORTURE GARDEN 29370, TROG 31252, V/H/S 11907, VAMPIRE IN BROOKLYN 38370, VAMPYR 36374, VILLAGE OF THE DAMNED 28352, WHITE ZOMBIE 6037, WITCHFINDER GENERAL src, edge_attr, dst 18899, has_genre, 5870 18899, has_tags, 10045 18899, release_year, 3702 30407, has_genre, 5870 30407, has_tags, 5870 19826, has_genre, 5870 19826, has_tags, 10045 26014, has_genre, 5870 26014, has_tags, 10045 32620, has_tags, 10045 32620, has_tags, 5870 37126, has_genre, 5870 37126, release_year, 3702 37912, has_genre, 5870 37912, has_tags, 10045 4381, has_genre, 5870 4381, has_tags, 10045 27143, has_genre, 5870 27143, has_tags, 10045 8381, has_genre, 5870 8381, has_tags, 10045 23807, directed_by, 13889 23807, has_genre, 5870 23807, has_tags, 10045 23807, has_tags, 13138 23807, has_tags, 4653 23807, release_year, 1892 23807, starred_actors, 4653 23807, starred_actors, 30645 3154, has_genre, 5870 3154, has_tags, 10045 34827, has_genre, 5870 34827, has_tags, 10045 36920, has_genre, 5870 36920, has_tags, 10045 37707, has_genre, 5870 37707, has_tags, 10045 24825, has_genre, 5870 24825, release_year, 3702 29503, has_genre, 5870 29503, has_tags, 10045 24540, has_genre, 5870 24540, has_tags, 10045 32144, has_genre, 5870 32144, has_tags, 10045 5291, has_genre, 5870 5291, release_year, 1892 38609, has_genre, 5870 38609, has_tags, 10045 12378, has_genre, 5870 12378, has_tags, 10045 13990, has_genre, 5870 13990, release_year, 3702 39972, has_tags, 10045 39972, has_tags, 5870 22421, has_genre, 5870 22421, has_tags, 10045 10955, has_genre, 5870 10955, has_tags, 10045 10955, has_tags, 5870 9686, has_genre, 5870 9686, has_tags, 10045 33663, has_genre, 5870 33663, release_year, 3702 33269, has_genre, 5870 33269, release_year, 1892 35018, directed_by, 38158 35018, has_genre, 5870 35018, written_by, 38158 33627, has_genre, 5870 33627, release_year, 3702 40127, has_genre, 5870 40127, has_tags, 10045 17728, has_genre, 5870 17728, has_tags, 10045 17728, release_year, 3702 26370, has_genre, 5870 26370, has_tags, 10045 25643, has_genre, 5870 25643, has_tags, 10045 25643, starred_actors, 30645 3129, has_genre, 5870 3129, has_tags, 10045 18744, has_genre, 5870 18744, release_year, 1892 16462, directed_by, 13889 16462, has_genre, 5870 16462, has_tags, 10045 16462, has_tags, 4653 16462, has_tags, 13889 16462, starred_actors, 4653 16462, starred_actors, 30645 17189, has_genre, 5870 17189, has_tags, 10045 9330, has_genre, 5870 9330, has_tags, 10045 32988, has_genre, 5870 32988, has_tags, 10045 32988, has_tags, 5870 32891, has_genre, 5870 32891, has_tags, 10045 19017, has_genre, 5870 19017, has_tags, 10045 16004, has_genre, 5870 16004, has_tags, 10045 16004, has_tags, 5870 13060, has_genre, 5870 13060, has_tags, 13138 5897, has_genre, 5870 5897, has_tags, 10045 7531, has_genre, 5870 7531, has_tags, 30407 7531, release_year, 3702 8436, has_genre, 5870 8436, has_tags, 10045 32367, has_genre, 5870 32367, has_tags, 10045 39265, has_genre, 5870 39265, has_tags, 10045 34349, has_genre, 5870 34349, has_tags, 10045 4938, has_genre, 5870 4938, release_year, 3702 14072, has_genre, 5870 14072, has_tags, 10045 14072, has_tags, 5870 12781, has_genre, 5870 12781, has_tags, 10045 13151, has_genre, 5870 13151, has_tags, 10045 17361, has_genre, 5870 17361, has_tags, 10045 25829, has_genre, 5870 25829, has_tags, 10045 31239, has_genre, 5870 31239, has_tags, 10045 38676, has_genre, 5870 38676, has_tags, 10045 24990, has_genre, 5870 24990, has_tags, 10045 24990, has_tags, 5870 38265, has_genre, 5870 38265, has_tags, 10045 32732, has_genre, 5870 32732, has_tags, 10045 23327, has_genre, 5870 23327, has_tags, 10045 28048, has_genre, 5870 28048, has_tags, 10045 10613, has_genre, 5870 10613, starred_actors, 30645 14113, has_genre, 5870 14113, has_tags, 10045 14382, has_genre, 5870 14382, has_tags, 10045 25175, has_genre, 5870 25175, has_tags, 10045 11787, has_genre, 5870 11787, has_tags, 10045 11787, has_tags, 5870 31283, has_genre, 5870 31283, has_tags, 10045 22212, has_genre, 5870 22212, has_tags, 10045 32595, has_genre, 5870 32595, has_tags, 10045 15198, has_genre, 5870 15198, has_tags, 10045 29358, has_genre, 5870 29358, has_tags, 10045 27780, has_genre, 5870 27780, has_tags, 10045 34005, has_genre, 5870 34005, has_tags, 10045 8623, has_genre, 5870 8623, has_tags, 10045 33794, has_genre, 5870 33794, has_tags, 10045 29109, has_genre, 5870 29109, has_tags, 10045 26566, has_genre, 5870 26566, has_tags, 5870 26566, release_year, 3702 11243, has_genre, 5870 11243, has_tags, 10045 12785, has_genre, 5870 12785, release_year, 1892 26820, has_genre, 5870 26820, has_tags, 10045 26820, has_tags, 5870 26820, release_year, 1892 27182, has_genre, 5870 27182, release_year, 3702 9420, has_genre, 5870 9420, release_year, 1892 8727, has_genre, 5870 8727, has_tags, 10045 1565, has_genre, 5870 1565, has_tags, 10045 22294, has_genre, 5870 22294, release_year, 3702 18162, has_genre, 5870 18162, has_tags, 10045 18162, has_tags, 5870 10186, has_genre, 5870 10186, has_tags, 10045 1143, has_genre, 5870 1143, has_tags, 10045 23847, has_genre, 5870 23847, has_tags, 10045 23260, has_genre, 5870 23260, has_tags, 10045 33991, has_genre, 5870 33991, has_tags, 10045 19823, has_genre, 5870 19823, has_tags, 10045 39200, has_genre, 5870 39200, has_tags, 4653 39200, starred_actors, 4653 39200, starred_actors, 30645 13780, directed_by, 13889 13780, has_genre, 5870 13780, release_year, 3702 13780, starred_actors, 9493 22751, has_genre, 5870 22751, has_tags, 10045 6833, has_genre, 5870 6833, has_tags, 10045 3594, has_genre, 5870 3594, has_tags, 10045 14444, has_genre, 5870 14444, has_tags, 10045 14444, has_tags, 5870 1596, has_genre, 5870 1596, has_tags, 10045 29370, has_genre, 5870 29370, has_tags, 10045 31252, has_genre, 5870 31252, has_tags, 10045 31252, has_tags, 5870 11907, has_genre, 5870 11907, release_year, 3702 11907, starred_actors, 9493 38370, has_genre, 5870 38370, release_year, 1892 36374, has_genre, 5870 36374, has_tags, 10045 36374, release_year, 3702 28352, has_genre, 5870 28352, has_tags, 10045 28352, release_year, 1892 6037, has_genre, 5870 6037, has_tags, 10045 Question: For what reason are 1995, DAVID HILLENBRAND, and DOCTOR X associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1995", "DAVID HILLENBRAND", "DOCTOR X" ], "valid_edges": [ [ "A BUCKET OF BLOOD", "has_genre", "HORROR" ], [ "A BUCKET OF BLOOD", "has_tags", "BD-R" ], [ "A BUCKET OF BLOOD", "release_year", "1995" ], [ "ALIEN", "has_genre", "HORROR" ], [ "ALIEN", "has_tags", "HORROR" ], [ "BLACK DEATH", "has_genre", "HORROR" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLOOD OF THE VAMPIRE", "has_genre", "HORROR" ], [ "BLOOD OF THE VAMPIRE", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "HORROR" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "release_year", "1995" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "has_tags", "BD-R" ], [ "DEAD OF NIGHT", "has_genre", "HORROR" ], [ "DEAD OF NIGHT", "has_tags", "BD-R" ], [ "DEMENTIA 13", "has_genre", "HORROR" ], [ "DEMENTIA 13", "has_tags", "BD-R" ], [ "DETOUR", "has_genre", "HORROR" ], [ "DETOUR", "has_tags", "BD-R" ], [ "DOCTOR X", "directed_by", "MICHAEL CURTIZ" ], [ "DOCTOR X", "has_genre", "HORROR" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DOCTOR X", "has_tags", "CANNIBALISM" ], [ "DOCTOR X", "has_tags", "FAY WRAY" ], [ "DOCTOR X", "release_year", "1932" ], [ "DOCTOR X", "starred_actors", "FAY WRAY" ], [ "DOCTOR X", "starred_actors", "LIONEL ATWILL" ], [ "DONOVAN'S BRAIN", "has_genre", "HORROR" ], [ "DONOVAN'S BRAIN", "has_tags", "BD-R" ], [ "DR. JEKYLL AND MR. HYDE", "has_genre", "HORROR" ], [ "DR. JEKYLL AND MR. HYDE", "has_tags", "BD-R" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_genre", "HORROR" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_tags", "BD-R" ], [ "DRACULA'S DAUGHTER", "has_genre", "HORROR" ], [ "DRACULA'S DAUGHTER", "has_tags", "BD-R" ], [ "EVOLVER", "has_genre", "HORROR" ], [ "EVOLVER", "release_year", "1995" ], [ "EYE OF THE DEVIL", "has_genre", "HORROR" ], [ "EYE OF THE DEVIL", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_genre", "HORROR" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_genre", "HORROR" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_tags", "BD-R" ], [ "FREAKS", "has_genre", "HORROR" ], [ "FREAKS", "release_year", "1932" ], [ "GALAXY OF TERROR", "has_genre", "HORROR" ], [ "GALAXY OF TERROR", "has_tags", "BD-R" ], [ "HANDS OF THE RIPPER", "has_genre", "HORROR" ], [ "HANDS OF THE RIPPER", "has_tags", "BD-R" ], [ "HIDEAWAY", "has_genre", "HORROR" ], [ "HIDEAWAY", "release_year", "1995" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "HORROR" ], [ "HORROR EXPRESS", "has_genre", "HORROR" ], [ "HORROR EXPRESS", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF WAX", "has_genre", "HORROR" ], [ "HOUSE OF WAX", "has_tags", "BD-R" ], [ "ICE CREAM MAN", "has_genre", "HORROR" ], [ "ICE CREAM MAN", "release_year", "1995" ], [ "ISLAND OF LOST SOULS", "has_genre", "HORROR" ], [ "ISLAND OF LOST SOULS", "release_year", "1932" ], [ "KING COBRA", "directed_by", "DAVID HILLENBRAND" ], [ "KING COBRA", "has_genre", "HORROR" ], [ "KING COBRA", "written_by", "DAVID HILLENBRAND" ], [ "LORD OF ILLUSIONS", "has_genre", "HORROR" ], [ "LORD OF ILLUSIONS", "release_year", "1995" ], [ "MACABRE", "has_genre", "HORROR" ], [ "MACABRE", "has_tags", "BD-R" ], [ "MAD LOVE", "has_genre", "HORROR" ], [ "MAD LOVE", "has_tags", "BD-R" ], [ "MAD LOVE", "release_year", "1995" ], [ "MADHOUSE", "has_genre", "HORROR" ], [ "MADHOUSE", "has_tags", "BD-R" ], [ "MARK OF THE VAMPIRE", "has_genre", "HORROR" ], [ "MARK OF THE VAMPIRE", "has_tags", "BD-R" ], [ "MARK OF THE VAMPIRE", "starred_actors", "LIONEL ATWILL" ], [ "MAXIMUM OVERDRIVE", "has_genre", "HORROR" ], [ "MAXIMUM OVERDRIVE", "has_tags", "BD-R" ], [ "MURDERS IN THE RUE MORGUE", "has_genre", "HORROR" ], [ "MURDERS IN THE RUE MORGUE", "release_year", "1932" ], [ "MYSTERY OF THE WAX MUSEUM", "directed_by", "MICHAEL CURTIZ" ], [ "MYSTERY OF THE WAX MUSEUM", "has_genre", "HORROR" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "BD-R" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "FAY WRAY" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "MICHAEL CURTIZ" ], [ "MYSTERY OF THE WAX MUSEUM", "starred_actors", "FAY WRAY" ], [ "MYSTERY OF THE WAX MUSEUM", "starred_actors", "LIONEL ATWILL" ], [ "NIGHT OF THE DEMONS", "has_genre", "HORROR" ], [ "NIGHT OF THE DEMONS", "has_tags", "BD-R" ], [ "NIGHT OF THE LEPUS", "has_genre", "HORROR" ], [ "NIGHT OF THE LEPUS", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "NOSFERATU", "has_genre", "HORROR" ], [ "NOSFERATU", "has_tags", "BD-R" ], [ "PEEPING TOM", "has_genre", "HORROR" ], [ "PEEPING TOM", "has_tags", "BD-R" ], [ "PLANET TERROR", "has_genre", "HORROR" ], [ "PLANET TERROR", "has_tags", "BD-R" ], [ "PLANET TERROR", "has_tags", "HORROR" ], [ "RAVENOUS", "has_genre", "HORROR" ], [ "RAVENOUS", "has_tags", "CANNIBALISM" ], [ "REPULSION", "has_genre", "HORROR" ], [ "REPULSION", "has_tags", "BD-R" ], [ "SPECIES", "has_genre", "HORROR" ], [ "SPECIES", "has_tags", "ALIEN" ], [ "SPECIES", "release_year", "1995" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "STAGE FRIGHT", "has_genre", "HORROR" ], [ "STAGE FRIGHT", "has_tags", "BD-R" ], [ "STORAGE 24", "has_genre", "HORROR" ], [ "STORAGE 24", "has_tags", "BD-R" ], [ "SVENGALI", "has_genre", "HORROR" ], [ "SVENGALI", "has_tags", "BD-R" ], [ "TALES FROM THE HOOD", "has_genre", "HORROR" ], [ "TALES FROM THE HOOD", "release_year", "1995" ], [ "THE ABOMINABLE DR. PHIBES", "has_genre", "HORROR" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "BD-R" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_genre", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_tags", "BD-R" ], [ "THE BAD SEED", "has_genre", "HORROR" ], [ "THE BAD SEED", "has_tags", "BD-R" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_tags", "BD-R" ], [ "THE CABINET OF DR. CALIGARI", "has_genre", "HORROR" ], [ "THE CABINET OF DR. CALIGARI", "has_tags", "BD-R" ], [ "THE CAT AND THE CANARY", "has_genre", "HORROR" ], [ "THE CAT AND THE CANARY", "has_tags", "BD-R" ], [ "THE CREEPING FLESH", "has_genre", "HORROR" ], [ "THE CREEPING FLESH", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "HORROR" ], [ "THE DEVIL-DOLL", "has_genre", "HORROR" ], [ "THE DEVIL-DOLL", "has_tags", "BD-R" ], [ "THE DOCTOR AND THE DEVILS", "has_genre", "HORROR" ], [ "THE DOCTOR AND THE DEVILS", "has_tags", "BD-R" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_genre", "HORROR" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_tags", "BD-R" ], [ "THE GHOST BREAKERS", "has_genre", "HORROR" ], [ "THE GHOST BREAKERS", "has_tags", "BD-R" ], [ "THE GHOST OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE GHOST OF FRANKENSTEIN", "starred_actors", "LIONEL ATWILL" ], [ "THE GHOUL", "has_genre", "HORROR" ], [ "THE GHOUL", "has_tags", "BD-R" ], [ "THE GORGON", "has_genre", "HORROR" ], [ "THE GORGON", "has_tags", "BD-R" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_genre", "HORROR" ], [ "THE HAUNTING", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_tags", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_genre", "HORROR" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_tags", "BD-R" ], [ "THE HOWLING", "has_genre", "HORROR" ], [ "THE HOWLING", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "HORROR" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNGER", "has_genre", "HORROR" ], [ "THE HUNGER", "has_tags", "BD-R" ], [ "THE INNOCENTS", "has_genre", "HORROR" ], [ "THE INNOCENTS", "has_tags", "BD-R" ], [ "THE INVISIBLE MAN", "has_genre", "HORROR" ], [ "THE INVISIBLE MAN", "has_tags", "BD-R" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "BD-R" ], [ "THE LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "THE LITTLE SHOP OF HORRORS", "has_tags", "BD-R" ], [ "THE LODGER", "has_genre", "HORROR" ], [ "THE LODGER", "has_tags", "BD-R" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "release_year", "1995" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "BD-R" ], [ "THE MONSTER WALKS", "has_genre", "HORROR" ], [ "THE MONSTER WALKS", "release_year", "1932" ], [ "THE MUMMY", "has_genre", "HORROR" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE MUMMY", "has_tags", "HORROR" ], [ "THE MUMMY", "release_year", "1932" ], [ "THE NATURE OF THE BEAST", "has_genre", "HORROR" ], [ "THE NATURE OF THE BEAST", "release_year", "1995" ], [ "THE OLD DARK HOUSE", "has_genre", "HORROR" ], [ "THE OLD DARK HOUSE", "release_year", "1932" ], [ "THE PICTURE OF DORIAN GRAY", "has_genre", "HORROR" ], [ "THE PICTURE OF DORIAN GRAY", "has_tags", "BD-R" ], [ "THE PLAGUE OF THE ZOMBIES", "has_genre", "HORROR" ], [ "THE PLAGUE OF THE ZOMBIES", "has_tags", "BD-R" ], [ "THE PROPHECY", "has_genre", "HORROR" ], [ "THE PROPHECY", "release_year", "1995" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "BD-R" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE SEVENTH VICTIM", "has_genre", "HORROR" ], [ "THE SEVENTH VICTIM", "has_tags", "BD-R" ], [ "THE STEPFORD WIVES", "has_genre", "HORROR" ], [ "THE STEPFORD WIVES", "has_tags", "BD-R" ], [ "THE SWARM", "has_genre", "HORROR" ], [ "THE SWARM", "has_tags", "BD-R" ], [ "THE TERROR", "has_genre", "HORROR" ], [ "THE TERROR", "has_tags", "BD-R" ], [ "THE UNKNOWN", "has_genre", "HORROR" ], [ "THE UNKNOWN", "has_tags", "BD-R" ], [ "THE VAMPIRE BAT", "has_genre", "HORROR" ], [ "THE VAMPIRE BAT", "has_tags", "FAY WRAY" ], [ "THE VAMPIRE BAT", "starred_actors", "FAY WRAY" ], [ "THE VAMPIRE BAT", "starred_actors", "LIONEL ATWILL" ], [ "THE WALKING DEAD", "directed_by", "MICHAEL CURTIZ" ], [ "THE WALKING DEAD", "has_genre", "HORROR" ], [ "THE WALKING DEAD", "release_year", "1995" ], [ "THE WALKING DEAD", "starred_actors", "ALLEN PAYNE" ], [ "THE WICKER MAN", "has_genre", "HORROR" ], [ "THE WICKER MAN", "has_tags", "BD-R" ], [ "THE WITCHES", "has_genre", "HORROR" ], [ "THE WITCHES", "has_tags", "BD-R" ], [ "THEATRE OF BLOOD", "has_genre", "HORROR" ], [ "THEATRE OF BLOOD", "has_tags", "BD-R" ], [ "THEM!", "has_genre", "HORROR" ], [ "THEM!", "has_tags", "BD-R" ], [ "THEM!", "has_tags", "HORROR" ], [ "TORTURE GARDEN", "has_genre", "HORROR" ], [ "TORTURE GARDEN", "has_tags", "BD-R" ], [ "TROG", "has_genre", "HORROR" ], [ "TROG", "has_tags", "BD-R" ], [ "V/H/S", "has_genre", "HORROR" ], [ "V/H/S", "has_tags", "BD-R" ], [ "V/H/S", "has_tags", "HORROR" ], [ "VAMPIRE IN BROOKLYN", "has_genre", "HORROR" ], [ "VAMPIRE IN BROOKLYN", "release_year", "1995" ], [ "VAMPIRE IN BROOKLYN", "starred_actors", "ALLEN PAYNE" ], [ "VAMPYR", "has_genre", "HORROR" ], [ "VAMPYR", "release_year", "1932" ], [ "VILLAGE OF THE DAMNED", "has_genre", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_tags", "BD-R" ], [ "VILLAGE OF THE DAMNED", "release_year", "1995" ], [ "WHITE ZOMBIE", "has_genre", "HORROR" ], [ "WHITE ZOMBIE", "has_tags", "BD-R" ], [ "WHITE ZOMBIE", "release_year", "1932" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36646, HE GOT GAME 6315, RAY ALLEN 32404, SPORT 3049, SPORTS 32526, THE BLIND SIDE 35135, THE LAST AMERICAN HERO 32080, TIM MCGRAW 2955, TOM WOLFE src, edge_attr, dst 36646, has_genre, 32404 36646, has_tags, 3049 36646, starred_actors, 6315 32526, has_genre, 32404 32526, has_tags, 3049 32526, has_tags, 32080 32526, starred_actors, 32080 35135, has_genre, 32404 35135, written_by, 2955 Question: In what context are RAY ALLEN, TIM MCGRAW, and TOM WOLFE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "RAY ALLEN", "TIM MCGRAW", "TOM WOLFE" ], "valid_edges": [ [ "HE GOT GAME", "has_genre", "SPORT" ], [ "HE GOT GAME", "has_tags", "SPORTS" ], [ "HE GOT GAME", "starred_actors", "RAY ALLEN" ], [ "THE BLIND SIDE", "has_genre", "SPORT" ], [ "THE BLIND SIDE", "has_tags", "SPORTS" ], [ "THE BLIND SIDE", "has_tags", "TIM MCGRAW" ], [ "THE BLIND SIDE", "starred_actors", "TIM MCGRAW" ], [ "THE LAST AMERICAN HERO", "has_genre", "SPORT" ], [ "THE LAST AMERICAN HERO", "written_by", "TOM WOLFE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 23696, ETERNAL SUNSHINE OF THE SPOTLESS MIND 9621, HAWAII, OSLO 12112, LINDSAY LOHAN 19791, MEAN GIRLS 38298, NONLINEAR 31625, TROND ESPEN SEIM src, edge_attr, dst 10272, has_tags, 12112 10272, release_year, 37484 10272, starred_actors, 12112 23696, has_tags, 38298 23696, release_year, 37484 9621, release_year, 37484 9621, starred_actors, 31625 19791, has_tags, 12112 19791, release_year, 37484 19791, starred_actors, 12112 Question: For what reason are LINDSAY LOHAN, NONLINEAR, and TROND ESPEN SEIM associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LINDSAY LOHAN", "NONLINEAR", "TROND ESPEN SEIM" ], "valid_edges": [ [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "LINDSAY LOHAN" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "starred_actors", "LINDSAY LOHAN" ], [ "ETERNAL SUNSHINE OF THE SPOTLESS MIND", "has_tags", "NONLINEAR" ], [ "ETERNAL SUNSHINE OF THE SPOTLESS MIND", "release_year", "2004" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWAII, OSLO", "starred_actors", "TROND ESPEN SEIM" ], [ "MEAN GIRLS", "has_tags", "LINDSAY LOHAN" ], [ "MEAN GIRLS", "release_year", "2004" ], [ "MEAN GIRLS", "starred_actors", "LINDSAY LOHAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 40094, 1930S 6776, 2000 20719, A TIME FOR DRUNKEN HORSES 21413, AMARCORD 32815, BLACKBOARDS 9778, GLADIATOR 16200, ITALIAN 17279, KIPPUR 13725, KURDISH 37499, PARAGRAPH 175 8504, PRIMO LEVI 6759, RULES OF ENGAGEMENT 12691, THE PATRIOT 37529, THE TRUCE 3934, TIGERLAND 23247, TRIAGE 29947, TURTLES CAN FLY 37253, U-571 22214, WAR src, edge_attr, dst 20719, has_genre, 22214 20719, in_language, 13725 20719, release_year, 6776 21413, has_tags, 40094 21413, in_language, 16200 32815, has_genre, 22214 32815, in_language, 13725 32815, release_year, 6776 9778, has_tags, 22214 9778, release_year, 6776 17279, has_genre, 22214 17279, release_year, 6776 37499, has_genre, 22214 37499, release_year, 6776 6759, has_genre, 22214 6759, release_year, 6776 12691, has_tags, 22214 12691, release_year, 6776 37529, has_genre, 22214 37529, in_language, 16200 37529, written_by, 8504 3934, has_genre, 22214 3934, release_year, 6776 23247, has_genre, 22214 23247, in_language, 13725 29947, has_genre, 22214 29947, in_language, 13725 37253, has_genre, 22214 37253, has_tags, 22214 37253, release_year, 6776 Question: For what reason are 1930S, BLACKBOARDS, and PRIMO LEVI associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1930S", "BLACKBOARDS", "PRIMO LEVI" ], "valid_edges": [ [ "A TIME FOR DRUNKEN HORSES", "has_genre", "WAR" ], [ "A TIME FOR DRUNKEN HORSES", "in_language", "KURDISH" ], [ "A TIME FOR DRUNKEN HORSES", "release_year", "2000" ], [ "AMARCORD", "has_tags", "1930S" ], [ "AMARCORD", "in_language", "ITALIAN" ], [ "BLACKBOARDS", "has_genre", "WAR" ], [ "BLACKBOARDS", "in_language", "KURDISH" ], [ "BLACKBOARDS", "release_year", "2000" ], [ "GLADIATOR", "has_tags", "WAR" ], [ "GLADIATOR", "release_year", "2000" ], [ "KIPPUR", "has_genre", "WAR" ], [ "KIPPUR", "release_year", "2000" ], [ "PARAGRAPH 175", "has_genre", "WAR" ], [ "PARAGRAPH 175", "release_year", "2000" ], [ "RULES OF ENGAGEMENT", "has_genre", "WAR" ], [ "RULES OF ENGAGEMENT", "release_year", "2000" ], [ "THE PATRIOT", "has_tags", "WAR" ], [ "THE PATRIOT", "release_year", "2000" ], [ "THE TRUCE", "has_genre", "WAR" ], [ "THE TRUCE", "in_language", "ITALIAN" ], [ "THE TRUCE", "written_by", "PRIMO LEVI" ], [ "TIGERLAND", "has_genre", "WAR" ], [ "TIGERLAND", "release_year", "2000" ], [ "TRIAGE", "has_genre", "WAR" ], [ "TRIAGE", "in_language", "KURDISH" ], [ "TURTLES CAN FLY", "has_genre", "WAR" ], [ "TURTLES CAN FLY", "in_language", "KURDISH" ], [ "U-571", "has_genre", "WAR" ], [ "U-571", "has_tags", "WAR" ], [ "U-571", "release_year", "2000" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10757, EDDIE 33902, FOOL FOR LOVE 18907, IMAGES 33184, RANDY QUAID 29049, ROBERT ALTMAN 35362, THE MAGICAL LEGEND OF THE LEPRECHAUNS 37332, WHOOPI GOLDBERG src, edge_attr, dst 10757, starred_actors, 37332 33902, directed_by, 29049 33902, starred_actors, 33184 18907, directed_by, 29049 18907, has_tags, 29049 18907, written_by, 29049 35362, starred_actors, 33184 35362, starred_actors, 37332 Question: In what context are EDDIE, FOOL FOR LOVE, and IMAGES connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EDDIE", "FOOL FOR LOVE", "IMAGES" ], "valid_edges": [ [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "FOOL FOR LOVE", "directed_by", "ROBERT ALTMAN" ], [ "FOOL FOR LOVE", "starred_actors", "RANDY QUAID" ], [ "IMAGES", "directed_by", "ROBERT ALTMAN" ], [ "IMAGES", "has_tags", "ROBERT ALTMAN" ], [ "IMAGES", "written_by", "ROBERT ALTMAN" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "RANDY QUAID" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "WHOOPI GOLDBERG" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 3417, COPPOLA 14724, CRIME 36645, JON COHEN 3487, MINORITY REPORT 10956, REAL WOMEN HAVE CURVES 35551, THE GODFATHER src, edge_attr, dst 3487, has_tags, 14724 3487, release_year, 35935 3487, written_by, 36645 10956, release_year, 35935 35551, has_genre, 14724 35551, has_tags, 3417 35551, has_tags, 14724 Question: How are COPPOLA, JON COHEN, and REAL WOMEN HAVE CURVES related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "COPPOLA", "JON COHEN", "REAL WOMEN HAVE CURVES" ], "valid_edges": [ [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "MINORITY REPORT", "written_by", "JON COHEN" ], [ "REAL WOMEN HAVE CURVES", "release_year", "2002" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "COPPOLA" ], [ "THE GODFATHER", "has_tags", "CRIME" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 6718, A FAREWELL TO ARMS 34734, BATTLE OF THE BULGE 34812, BECKY SHARP 40074, BLACK BOOK 867, BREAKING AND ENTERING 11929, CASABLANCA 25285, COME AND SEE 30463, COMEDY 10293, CONSPIRACY 30624, DANCES WITH WOLVES 24410, DEMONLOVER 30123, DORIAN GRAY 36212, DRAMA 31008, DUTCH 31783, ENGLISH 8294, FIVE FINGERS 1273, FLYBOYS 13834, FLYING TIGERS 39145, FURY 15765, HAMSUN 24370, HOWARD TEICHMANN 15343, IN DARKNESS 30910, LONELYHEARTS 22260, MEMORY 28910, MICHAEL CRICHTON 38294, MRS. MINIVER 26892, NAZIS 25264, NOTES ON A SCANDAL 39852, PAN'S LABYRINTH 24369, QUINCEAÑERA 35586, SAHARA 11124, STALINGRAD 27210, THE BEST YEARS OF OUR LIVES 36692, THE CAINE MUTINY 19883, THE CHATTERLEY AFFAIR 25509, THE DEBT 36390, THE ENGLISH PATIENT 6424, THE GREAT ESCAPE 28107, THE LAST KISS 12614, THE PIANIST 28919, THE RETURN 21548, THE SUN 2783, THE WIND THAT SHAKES THE BARLEY 36313, THERE BE DRAGONS 24811, THRILLER 30585, TWISTER 22214, WAR 24155, WORLD WAR II 15904, YANKS 16849, ZERO DARK THIRTY src, edge_attr, dst 6718, has_genre, 22214 6718, in_language, 31783 34734, has_genre, 22214 34734, has_tags, 24155 34812, has_genre, 22214 34812, in_language, 31783 40074, has_genre, 24811 40074, has_genre, 22214 40074, has_tags, 26892 40074, has_tags, 24155 40074, in_language, 31008 40074, in_language, 31783 40074, release_year, 35845 867, in_language, 31783 867, release_year, 35845 11929, has_genre, 22214 11929, has_tags, 26892 11929, has_tags, 22214 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 30624, has_tags, 22214 30624, in_language, 31783 24410, has_genre, 24811 24410, in_language, 31783 30123, has_genre, 24811 30123, in_language, 31783 31008, has_genre, 30463 31008, has_genre, 36212 8294, has_genre, 24811 8294, release_year, 35845 1273, has_tags, 22214 1273, release_year, 35845 13834, has_genre, 22214 13834, has_tags, 24155 39145, has_genre, 22214 39145, has_tags, 22214 39145, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 15765, in_language, 31783 15343, has_genre, 22214 15343, has_tags, 22214 15343, has_tags, 24155 30910, has_genre, 36212 30910, written_by, 24370 22260, has_genre, 24811 22260, release_year, 35845 38294, has_genre, 22214 38294, has_tags, 24155 25264, has_genre, 24811 25264, release_year, 35845 39852, has_genre, 22214 39852, has_tags, 22214 39852, release_year, 35845 24369, in_language, 31783 24369, release_year, 35845 35586, has_genre, 22214 35586, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 27210, has_genre, 22214 27210, has_tags, 24155 36692, has_genre, 22214 36692, has_tags, 24155 19883, in_language, 31783 19883, release_year, 35845 25509, has_genre, 24811 25509, in_language, 31783 36390, has_genre, 22214 36390, has_tags, 22214 36390, in_language, 31783 6424, has_tags, 22214 6424, has_tags, 24155 28107, in_language, 31783 28107, release_year, 35845 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 28919, has_genre, 24811 28919, release_year, 35845 21548, has_tags, 22214 21548, has_tags, 24155 2783, has_genre, 22214 2783, in_language, 31783 2783, release_year, 35845 36313, has_genre, 22214 36313, in_language, 31783 30585, has_genre, 30463 30585, has_genre, 36212 30585, has_tags, 28910 30585, written_by, 28910 15904, has_genre, 22214 15904, has_tags, 24155 16849, has_genre, 24811 16849, has_tags, 22214 Question: In what context are BLACK BOOK, HOWARD TEICHMANN, and MICHAEL CRICHTON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BLACK BOOK", "HOWARD TEICHMANN", "MICHAEL CRICHTON" ], "valid_edges": [ [ "A FAREWELL TO ARMS", "has_genre", "WAR" ], [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "BATTLE OF THE BULGE", "has_genre", "WAR" ], [ "BATTLE OF THE BULGE", "has_tags", "WORLD WAR II" ], [ "BECKY SHARP", "has_genre", "WAR" ], [ "BECKY SHARP", "in_language", "ENGLISH" ], [ "BLACK BOOK", "has_genre", "THRILLER" ], [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "has_tags", "NAZIS" ], [ "BLACK BOOK", "has_tags", "WORLD WAR II" ], [ "BLACK BOOK", "in_language", "DUTCH" ], [ "BLACK BOOK", "in_language", "ENGLISH" ], [ "BLACK BOOK", "release_year", "2006" ], [ "BREAKING AND ENTERING", "in_language", "ENGLISH" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "CASABLANCA", "has_genre", "WAR" ], [ "CASABLANCA", "has_tags", "NAZIS" ], [ "CASABLANCA", "has_tags", "WAR" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "DANCES WITH WOLVES", "has_tags", "WAR" ], [ "DANCES WITH WOLVES", "in_language", "ENGLISH" ], [ "DEMONLOVER", "has_genre", "THRILLER" ], [ "DEMONLOVER", "in_language", "ENGLISH" ], [ "DORIAN GRAY", "has_genre", "THRILLER" ], [ "DORIAN GRAY", "in_language", "ENGLISH" ], [ "DUTCH", "has_genre", "COMEDY" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "FIVE FINGERS", "has_genre", "THRILLER" ], [ "FIVE FINGERS", "release_year", "2006" ], [ "FLYBOYS", "has_tags", "WAR" ], [ "FLYBOYS", "release_year", "2006" ], [ "FLYING TIGERS", "has_genre", "WAR" ], [ "FLYING TIGERS", "has_tags", "WORLD WAR II" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "in_language", "ENGLISH" ], [ "IN DARKNESS", "has_genre", "WAR" ], [ "IN DARKNESS", "has_tags", "WAR" ], [ "IN DARKNESS", "has_tags", "WORLD WAR II" ], [ "LONELYHEARTS", "has_genre", "DRAMA" ], [ "LONELYHEARTS", "written_by", "HOWARD TEICHMANN" ], [ "MEMORY", "has_genre", "THRILLER" ], [ "MEMORY", "release_year", "2006" ], [ "MRS. MINIVER", "has_genre", "WAR" ], [ "MRS. MINIVER", "has_tags", "WORLD WAR II" ], [ "NOTES ON A SCANDAL", "has_genre", "THRILLER" ], [ "NOTES ON A SCANDAL", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_genre", "WAR" ], [ "PAN'S LABYRINTH", "has_tags", "WAR" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "QUINCEAÑERA", "in_language", "ENGLISH" ], [ "QUINCEAÑERA", "release_year", "2006" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "THE BEST YEARS OF OUR LIVES", "has_genre", "WAR" ], [ "THE BEST YEARS OF OUR LIVES", "has_tags", "WORLD WAR II" ], [ "THE CAINE MUTINY", "has_genre", "WAR" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE CHATTERLEY AFFAIR", "in_language", "ENGLISH" ], [ "THE CHATTERLEY AFFAIR", "release_year", "2006" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE ENGLISH PATIENT", "has_genre", "WAR" ], [ "THE ENGLISH PATIENT", "has_tags", "WAR" ], [ "THE ENGLISH PATIENT", "in_language", "ENGLISH" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "has_tags", "WORLD WAR II" ], [ "THE LAST KISS", "in_language", "ENGLISH" ], [ "THE LAST KISS", "release_year", "2006" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "THE RETURN", "has_genre", "THRILLER" ], [ "THE RETURN", "release_year", "2006" ], [ "THE SUN", "has_tags", "WAR" ], [ "THE SUN", "has_tags", "WORLD WAR II" ], [ "THE WIND THAT SHAKES THE BARLEY", "has_genre", "WAR" ], [ "THE WIND THAT SHAKES THE BARLEY", "in_language", "ENGLISH" ], [ "THE WIND THAT SHAKES THE BARLEY", "release_year", "2006" ], [ "THERE BE DRAGONS", "has_genre", "WAR" ], [ "THERE BE DRAGONS", "in_language", "ENGLISH" ], [ "TWISTER", "has_genre", "COMEDY" ], [ "TWISTER", "has_genre", "DRAMA" ], [ "TWISTER", "has_tags", "MICHAEL CRICHTON" ], [ "TWISTER", "written_by", "MICHAEL CRICHTON" ], [ "YANKS", "has_genre", "WAR" ], [ "YANKS", "has_tags", "WORLD WAR II" ], [ "ZERO DARK THIRTY", "has_genre", "THRILLER" ], [ "ZERO DARK THIRTY", "has_tags", "WAR" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 9256, ANDREW CALDWELL 23702, BLOOMINGTON 16496, BLUE CHIPS 39848, BLUE LIKE JAZZ 24116, COLLEGE 38134, DANTE 01 36212, DRAMA 14023, GLORY ROAD 37982, GUMMO 14931, LIBERAL ARTS 4569, MARC CARO 9433, STOMP THE YARD 10213, THE GREAT DEBATERS 31401, THE RULES OF ATTRACTION src, edge_attr, dst 23702, has_genre, 36212 23702, has_tags, 24116 16496, has_genre, 36212 16496, has_tags, 24116 39848, has_genre, 36212 39848, has_tags, 24116 24116, has_genre, 36212 24116, release_year, 26762 24116, starred_actors, 9256 38134, directed_by, 4569 38134, release_year, 26762 38134, written_by, 4569 14023, has_genre, 36212 14023, has_tags, 24116 37982, has_genre, 36212 14931, has_genre, 36212 14931, has_tags, 24116 9433, has_genre, 36212 9433, has_tags, 24116 10213, has_genre, 36212 10213, has_tags, 24116 31401, has_genre, 36212 31401, has_tags, 24116 Question: How are ANDREW CALDWELL, GUMMO, and MARC CARO related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANDREW CALDWELL", "GUMMO", "MARC CARO" ], "valid_edges": [ [ "BLOOMINGTON", "has_genre", "DRAMA" ], [ "BLOOMINGTON", "has_tags", "COLLEGE" ], [ "BLUE CHIPS", "has_genre", "DRAMA" ], [ "BLUE CHIPS", "has_tags", "COLLEGE" ], [ "BLUE LIKE JAZZ", "has_genre", "DRAMA" ], [ "BLUE LIKE JAZZ", "has_tags", "COLLEGE" ], [ "COLLEGE", "has_genre", "DRAMA" ], [ "COLLEGE", "release_year", "2008" ], [ "COLLEGE", "starred_actors", "ANDREW CALDWELL" ], [ "DANTE 01", "directed_by", "MARC CARO" ], [ "DANTE 01", "release_year", "2008" ], [ "DANTE 01", "written_by", "MARC CARO" ], [ "GLORY ROAD", "has_genre", "DRAMA" ], [ "GLORY ROAD", "has_tags", "COLLEGE" ], [ "GUMMO", "has_genre", "DRAMA" ], [ "LIBERAL ARTS", "has_genre", "DRAMA" ], [ "LIBERAL ARTS", "has_tags", "COLLEGE" ], [ "STOMP THE YARD", "has_genre", "DRAMA" ], [ "STOMP THE YARD", "has_tags", "COLLEGE" ], [ "THE GREAT DEBATERS", "has_genre", "DRAMA" ], [ "THE GREAT DEBATERS", "has_tags", "COLLEGE" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "has_tags", "COLLEGE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 35724, ALTER EGOS 14883, DANNY MASTERSON 34031, RAGING PHOENIX 15926, SILENT NIGHT 36058, STEVEN C. MILLER src, edge_attr, dst 658, release_year, 27261 35724, release_year, 658 35724, starred_actors, 14883 34031, release_year, 27261 15926, directed_by, 36058 15926, release_year, 658 Question: For what reason are DANNY MASTERSON, RAGING PHOENIX, and STEVEN C. MILLER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DANNY MASTERSON", "RAGING PHOENIX", "STEVEN C. MILLER" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "ALTER EGOS", "release_year", "2012" ], [ "ALTER EGOS", "starred_actors", "DANNY MASTERSON" ], [ "RAGING PHOENIX", "release_year", "2009" ], [ "SILENT NIGHT", "directed_by", "STEVEN C. MILLER" ], [ "SILENT NIGHT", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 1006, 1996 35845, 2006 18243, A SCANNER DARKLY 23754, AFTER THE WEDDING 6938, ALPHA DOG 8229, APOCALYPTO 24301, ART SCHOOL CONFIDENTIAL 18820, ASK THE DUST 24366, BABEL 17883, BARRY LEVINSON 38865, BIG NIGHT 36593, BLACK CHRISTMAS 16664, BLOOD DIAMOND 10531, BOBBY 867, BREAKING AND ENTERING 16749, BROKEN ARROW 17899, BUG 33360, CANDY 22435, CHILDREN OF MEN 21625, CLERKS II 37750, CRANK 32049, CRASH 15115, CURSE OF THE GOLDEN FLOWER 932, DAVID HARE 3567, DAYS OF GLORY 21123, FARGO 13766, FAST FOOD NATION 13893, FIDO 18217, FIND ME GUILTY 10315, FLAGS OF OUR FATHERS 39988, FRIENDS WITH MONEY 7879, HALF NELSON 26170, HOLLYWOODLAND 17120, INFAMOUS 19637, INLAND EMPIRE 7264, INSIDE MAN 18934, LETTERS FROM IWO JIMA 11277, LITTLE CHILDREN 24376, LITTLE MISS SUNSHINE 19123, LONE STAR 33950, LUCKY NUMBER SLEVIN 38677, MIAMI VICE 39852, PAN'S LABYRINTH 3451, PAPRIKA 13081, R 37623, RAIN MAN 2169, RANSOM 18480, RENAISSANCE 5766, RUNNING WITH SCISSORS 17383, SHERRYBABY 26768, SLEEPERS 29018, SLING BLADE 26930, SLITHER 12333, SMOKIN' ACES 21171, STEPHEN DALDRY 37807, TELL NO ONE 37498, TENACIOUS D IN THE PICK OF DESTINY 11948, THE BLACK DAHLIA 31353, THE CONTRACT 1059, THE DA VINCI CODE 18997, THE DEPARTED 1723, THE FALL 4662, THE GOOD GERMAN 15862, THE GOOD SHEPHERD 31309, THE HOAX 11713, THE HOURS 2467, THE LAST KING OF SCOTLAND 14315, THE LIVES OF OTHERS 17393, THE NIGHT LISTENER 9058, THE READER 36327, THE ROCK 11383, THE SCIENCE OF SLEEP 27559, TRAINSPOTTING 25806, UNITED 93 36753, VENUS 35728, VOLVER 27612, WHAT JUST HAPPENED src, edge_attr, dst 29145, has_tags, 13081 29145, release_year, 35845 18243, has_tags, 13081 18243, release_year, 35845 23754, has_tags, 13081 23754, release_year, 35845 6938, has_tags, 13081 6938, release_year, 35845 8229, has_tags, 13081 8229, release_year, 35845 24301, has_tags, 13081 24301, release_year, 35845 18820, has_tags, 13081 18820, release_year, 35845 24366, has_tags, 13081 24366, release_year, 35845 38865, has_tags, 13081 38865, release_year, 1006 36593, has_tags, 13081 36593, release_year, 35845 16664, has_tags, 13081 16664, release_year, 35845 10531, has_tags, 13081 10531, release_year, 35845 867, has_tags, 13081 867, release_year, 35845 16749, has_tags, 13081 16749, release_year, 1006 17899, has_tags, 13081 17899, release_year, 35845 33360, has_tags, 13081 33360, release_year, 35845 22435, has_tags, 13081 22435, release_year, 35845 21625, has_tags, 13081 21625, release_year, 35845 37750, has_tags, 13081 37750, release_year, 35845 32049, has_tags, 13081 32049, release_year, 1006 15115, has_tags, 13081 15115, release_year, 35845 3567, has_tags, 13081 3567, release_year, 35845 21123, has_tags, 13081 21123, release_year, 1006 13766, has_tags, 13081 13766, release_year, 35845 13893, has_tags, 13081 13893, release_year, 35845 18217, has_tags, 13081 18217, release_year, 35845 10315, has_tags, 13081 10315, release_year, 35845 39988, has_tags, 13081 39988, release_year, 35845 7879, has_tags, 13081 7879, release_year, 35845 26170, has_tags, 13081 26170, release_year, 35845 17120, has_tags, 13081 17120, release_year, 35845 19637, has_tags, 13081 19637, release_year, 35845 7264, has_tags, 13081 7264, release_year, 35845 18934, has_tags, 13081 18934, release_year, 35845 11277, has_tags, 13081 11277, release_year, 35845 24376, has_tags, 13081 24376, release_year, 35845 19123, has_tags, 13081 19123, release_year, 1006 33950, has_tags, 13081 33950, release_year, 35845 38677, has_tags, 13081 38677, release_year, 35845 39852, has_tags, 13081 39852, release_year, 35845 3451, has_tags, 13081 3451, release_year, 35845 37623, directed_by, 17883 37623, has_tags, 17883 37623, has_tags, 13081 2169, has_tags, 13081 2169, release_year, 1006 18480, has_tags, 13081 18480, release_year, 35845 5766, has_tags, 13081 5766, release_year, 35845 17383, has_tags, 13081 17383, release_year, 35845 26768, directed_by, 17883 26768, has_tags, 17883 26768, has_tags, 13081 26768, release_year, 1006 26768, written_by, 17883 29018, has_tags, 13081 29018, release_year, 1006 26930, has_tags, 13081 26930, release_year, 35845 12333, has_tags, 13081 12333, release_year, 35845 37807, release_year, 35845 37498, has_tags, 13081 37498, release_year, 35845 11948, has_tags, 13081 11948, release_year, 35845 31353, has_tags, 13081 31353, release_year, 35845 1059, has_tags, 13081 1059, release_year, 35845 18997, has_tags, 13081 18997, release_year, 35845 1723, has_tags, 13081 1723, release_year, 35845 4662, has_tags, 13081 4662, release_year, 35845 15862, has_tags, 13081 15862, release_year, 35845 31309, has_tags, 13081 31309, release_year, 35845 11713, directed_by, 21171 11713, has_tags, 21171 11713, written_by, 932 2467, has_tags, 13081 2467, release_year, 35845 14315, has_tags, 13081 14315, release_year, 35845 17393, has_tags, 13081 17393, release_year, 35845 9058, directed_by, 21171 9058, has_tags, 13081 9058, has_tags, 21171 9058, written_by, 932 36327, has_tags, 13081 36327, release_year, 1006 11383, has_tags, 13081 11383, release_year, 35845 27559, has_tags, 13081 27559, release_year, 1006 25806, has_tags, 13081 25806, release_year, 35845 36753, has_tags, 13081 36753, release_year, 35845 35728, has_tags, 13081 35728, release_year, 35845 27612, directed_by, 17883 27612, has_tags, 17883 27612, has_tags, 13081 Question: How are DAVID HARE, SLEEPERS, and TELL NO ONE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAVID HARE", "SLEEPERS", "TELL NO ONE" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_tags", "R" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "A SCANNER DARKLY", "has_tags", "R" ], [ "A SCANNER DARKLY", "release_year", "2006" ], [ "AFTER THE WEDDING", "has_tags", "R" ], [ "AFTER THE WEDDING", "release_year", "2006" ], [ "ALPHA DOG", "has_tags", "R" ], [ "ALPHA DOG", "release_year", "2006" ], [ "APOCALYPTO", "has_tags", "R" ], [ "APOCALYPTO", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_tags", "R" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "ASK THE DUST", "has_tags", "R" ], [ "ASK THE DUST", "release_year", "2006" ], [ "BABEL", "has_tags", "R" ], [ "BABEL", "release_year", "2006" ], [ "BIG NIGHT", "has_tags", "R" ], [ "BIG NIGHT", "release_year", "1996" ], [ "BLACK CHRISTMAS", "has_tags", "R" ], [ "BLACK CHRISTMAS", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "R" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "BOBBY", "has_tags", "R" ], [ "BOBBY", "release_year", "2006" ], [ "BREAKING AND ENTERING", "has_tags", "R" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "BROKEN ARROW", "has_tags", "R" ], [ "BROKEN ARROW", "release_year", "1996" ], [ "BUG", "has_tags", "R" ], [ "BUG", "release_year", "2006" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "R" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "CLERKS II", "has_tags", "R" ], [ "CLERKS II", "release_year", "2006" ], [ "CRANK", "has_tags", "R" ], [ "CRANK", "release_year", "2006" ], [ "CRASH", "has_tags", "R" ], [ "CRASH", "release_year", "1996" ], [ "CURSE OF THE GOLDEN FLOWER", "has_tags", "R" ], [ "CURSE OF THE GOLDEN FLOWER", "release_year", "2006" ], [ "DAYS OF GLORY", "has_tags", "R" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "FARGO", "has_tags", "R" ], [ "FARGO", "release_year", "1996" ], [ "FAST FOOD NATION", "has_tags", "R" ], [ "FAST FOOD NATION", "release_year", "2006" ], [ "FIDO", "has_tags", "R" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_tags", "R" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FRIENDS WITH MONEY", "has_tags", "R" ], [ "FRIENDS WITH MONEY", "release_year", "2006" ], [ "HALF NELSON", "has_tags", "R" ], [ "HALF NELSON", "release_year", "2006" ], [ "HOLLYWOODLAND", "has_tags", "R" ], [ "HOLLYWOODLAND", "release_year", "2006" ], [ "INFAMOUS", "has_tags", "R" ], [ "INFAMOUS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "R" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "INSIDE MAN", "has_tags", "R" ], [ "INSIDE MAN", "release_year", "2006" ], [ "LETTERS FROM IWO JIMA", "has_tags", "R" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "LITTLE CHILDREN", "has_tags", "R" ], [ "LITTLE CHILDREN", "release_year", "2006" ], [ "LITTLE MISS SUNSHINE", "has_tags", "R" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LONE STAR", "has_tags", "R" ], [ "LONE STAR", "release_year", "1996" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "release_year", "2006" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MIAMI VICE", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_tags", "R" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PAPRIKA", "has_tags", "R" ], [ "PAPRIKA", "release_year", "2006" ], [ "RAIN MAN", "directed_by", "BARRY LEVINSON" ], [ "RAIN MAN", "has_tags", "BARRY LEVINSON" ], [ "RAIN MAN", "has_tags", "R" ], [ "RANSOM", "has_tags", "R" ], [ "RANSOM", "release_year", "1996" ], [ "RENAISSANCE", "has_tags", "R" ], [ "RENAISSANCE", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_tags", "R" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "SHERRYBABY", "has_tags", "R" ], [ "SHERRYBABY", "release_year", "2006" ], [ "SLEEPERS", "directed_by", "BARRY LEVINSON" ], [ "SLEEPERS", "has_tags", "BARRY LEVINSON" ], [ "SLEEPERS", "has_tags", "R" ], [ "SLEEPERS", "release_year", "1996" ], [ "SLEEPERS", "written_by", "BARRY LEVINSON" ], [ "SLING BLADE", "has_tags", "R" ], [ "SLING BLADE", "release_year", "1996" ], [ "SLITHER", "has_tags", "R" ], [ "SLITHER", "release_year", "2006" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "TELL NO ONE", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "R" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE BLACK DAHLIA", "release_year", "2006" ], [ "THE CONTRACT", "has_tags", "R" ], [ "THE CONTRACT", "release_year", "2006" ], [ "THE DA VINCI CODE", "has_tags", "R" ], [ "THE DA VINCI CODE", "release_year", "2006" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "release_year", "2006" ], [ "THE FALL", "has_tags", "R" ], [ "THE FALL", "release_year", "2006" ], [ "THE GOOD GERMAN", "has_tags", "R" ], [ "THE GOOD GERMAN", "release_year", "2006" ], [ "THE GOOD SHEPHERD", "has_tags", "R" ], [ "THE GOOD SHEPHERD", "release_year", "2006" ], [ "THE HOAX", "has_tags", "R" ], [ "THE HOAX", "release_year", "2006" ], [ "THE HOURS", "directed_by", "STEPHEN DALDRY" ], [ "THE HOURS", "has_tags", "STEPHEN DALDRY" ], [ "THE HOURS", "written_by", "DAVID HARE" ], [ "THE LAST KING OF SCOTLAND", "has_tags", "R" ], [ "THE LAST KING OF SCOTLAND", "release_year", "2006" ], [ "THE LIVES OF OTHERS", "has_tags", "R" ], [ "THE LIVES OF OTHERS", "release_year", "2006" ], [ "THE NIGHT LISTENER", "has_tags", "R" ], [ "THE NIGHT LISTENER", "release_year", "2006" ], [ "THE READER", "directed_by", "STEPHEN DALDRY" ], [ "THE READER", "has_tags", "R" ], [ "THE READER", "has_tags", "STEPHEN DALDRY" ], [ "THE READER", "written_by", "DAVID HARE" ], [ "THE ROCK", "has_tags", "R" ], [ "THE ROCK", "release_year", "1996" ], [ "THE SCIENCE OF SLEEP", "has_tags", "R" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "TRAINSPOTTING", "has_tags", "R" ], [ "TRAINSPOTTING", "release_year", "1996" ], [ "UNITED 93", "has_tags", "R" ], [ "UNITED 93", "release_year", "2006" ], [ "VENUS", "has_tags", "R" ], [ "VENUS", "release_year", "2006" ], [ "VOLVER", "has_tags", "R" ], [ "VOLVER", "release_year", "2006" ], [ "WHAT JUST HAPPENED", "directed_by", "BARRY LEVINSON" ], [ "WHAT JUST HAPPENED", "has_tags", "BARRY LEVINSON" ], [ "WHAT JUST HAPPENED", "has_tags", "R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 37484, 2004 812, BATMAN 27815, CLOWNHOUSE 18348, DHOOM 22693, HELLS ANGELS ON WHEELS 21488, JACK NICHOLSON 32051, THE PUNISHER src, edge_attr, dst 812, has_tags, 21488 812, release_year, 26633 812, starred_actors, 21488 27815, release_year, 26633 18348, release_year, 37484 22693, has_tags, 21488 22693, starred_actors, 21488 32051, release_year, 26633 32051, release_year, 37484 Question: In what context are CLOWNHOUSE, DHOOM, and HELLS ANGELS ON WHEELS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CLOWNHOUSE", "DHOOM", "HELLS ANGELS ON WHEELS" ], "valid_edges": [ [ "BATMAN", "has_tags", "JACK NICHOLSON" ], [ "BATMAN", "release_year", "1989" ], [ "BATMAN", "starred_actors", "JACK NICHOLSON" ], [ "CLOWNHOUSE", "release_year", "1989" ], [ "DHOOM", "release_year", "2004" ], [ "HELLS ANGELS ON WHEELS", "has_tags", "JACK NICHOLSON" ], [ "HELLS ANGELS ON WHEELS", "starred_actors", "JACK NICHOLSON" ], [ "THE PUNISHER", "release_year", "1989" ], [ "THE PUNISHER", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35187, 1948 26423, 1950 32617, GLORIA DEHAVEN 31193, PAT GARRISON 6498, RUSSEL CROUSE 5765, STATE OF THE UNION 29067, SUMMER HOLIDAY 37757, SUMMER STOCK 34691, THE FLYING SAUCER 37555, THE YELLOW CAB MAN src, edge_attr, dst 5765, release_year, 35187 5765, written_by, 6498 29067, release_year, 35187 29067, starred_actors, 32617 37757, release_year, 26423 37757, starred_actors, 32617 34691, release_year, 26423 34691, starred_actors, 31193 37555, release_year, 26423 37555, starred_actors, 32617 Question: How are GLORIA DEHAVEN, PAT GARRISON, and RUSSEL CROUSE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GLORIA DEHAVEN", "PAT GARRISON", "RUSSEL CROUSE" ], "valid_edges": [ [ "STATE OF THE UNION", "release_year", "1948" ], [ "STATE OF THE UNION", "written_by", "RUSSEL CROUSE" ], [ "SUMMER HOLIDAY", "release_year", "1948" ], [ "SUMMER HOLIDAY", "starred_actors", "GLORIA DEHAVEN" ], [ "SUMMER STOCK", "release_year", "1950" ], [ "SUMMER STOCK", "starred_actors", "GLORIA DEHAVEN" ], [ "THE FLYING SAUCER", "release_year", "1950" ], [ "THE FLYING SAUCER", "starred_actors", "PAT GARRISON" ], [ "THE YELLOW CAB MAN", "release_year", "1950" ], [ "THE YELLOW CAB MAN", "starred_actors", "GLORIA DEHAVEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 21497, A NIGHT IN HEAVEN 37540, DON JUAN DEMARCO 32719, EDWIGE FEUILLÈRE 6012, FRENCH 24485, HIGH ROAD TO CHINA 2625, JOYSTICKS 11142, LUCREZIA BORGIA 8379, ROMANCE src, edge_attr, dst 21497, has_genre, 8379 21497, release_year, 16055 37540, has_genre, 8379 37540, has_tags, 8379 24485, has_genre, 8379 24485, release_year, 16055 2625, release_year, 16055 11142, in_language, 6012 11142, starred_actors, 32719 8379, in_language, 6012 Question: In what context are DON JUAN DEMARCO, EDWIGE FEUILLÈRE, and JOYSTICKS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DON JUAN DEMARCO", "EDWIGE FEUILLÈRE", "JOYSTICKS" ], "valid_edges": [ [ "A NIGHT IN HEAVEN", "has_genre", "ROMANCE" ], [ "A NIGHT IN HEAVEN", "release_year", "1983" ], [ "DON JUAN DEMARCO", "has_genre", "ROMANCE" ], [ "DON JUAN DEMARCO", "has_tags", "ROMANCE" ], [ "HIGH ROAD TO CHINA", "has_genre", "ROMANCE" ], [ "HIGH ROAD TO CHINA", "release_year", "1983" ], [ "JOYSTICKS", "release_year", "1983" ], [ "LUCREZIA BORGIA", "in_language", "FRENCH" ], [ "LUCREZIA BORGIA", "starred_actors", "EDWIGE FEUILLÈRE" ], [ "ROMANCE", "in_language", "FRENCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 14259, 1997 2216, ALONG THE GREAT DIVIDE 33132, ARNOLD SCHWARZENEGGER 9589, BLUE 37414, FRANZ KAFKA 21574, KIRK DOUGLAS 39841, LAST ACTION HERO 22519, LAST TRAIN FROM GUN HILL 3937, POSSE 21732, SUTURE 18456, THE BALLAD OF LITTLE JO 29540, THE BIG SKY 13392, THE CASTLE 7009, THE LAST SUNSET 27535, THE VILLAIN 6789, THE WAR WAGON 19240, TOMBSTONE 36026, WESTERN src, edge_attr, dst 2216, has_genre, 36026 2216, starred_actors, 21574 9589, has_genre, 36026 9589, release_year, 24438 39841, has_tags, 33132 39841, release_year, 24438 39841, starred_actors, 33132 22519, has_genre, 36026 22519, starred_actors, 21574 3937, directed_by, 21574 3937, has_genre, 36026 3937, release_year, 24438 3937, starred_actors, 21574 21732, release_year, 24438 18456, has_genre, 36026 18456, release_year, 24438 29540, has_genre, 36026 29540, starred_actors, 21574 13392, has_tags, 37414 13392, release_year, 14259 13392, written_by, 37414 7009, has_genre, 36026 7009, starred_actors, 21574 27535, has_genre, 36026 27535, starred_actors, 33132 27535, starred_actors, 21574 6789, has_genre, 36026 6789, has_tags, 21574 6789, starred_actors, 21574 19240, has_tags, 36026 19240, release_year, 24438 36026, release_year, 14259 Question: How are FRANZ KAFKA, SUTURE, and THE VILLAIN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FRANZ KAFKA", "SUTURE", "THE VILLAIN" ], "valid_edges": [ [ "ALONG THE GREAT DIVIDE", "has_genre", "WESTERN" ], [ "ALONG THE GREAT DIVIDE", "starred_actors", "KIRK DOUGLAS" ], [ "BLUE", "has_genre", "WESTERN" ], [ "BLUE", "release_year", "1993" ], [ "LAST ACTION HERO", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "LAST ACTION HERO", "release_year", "1993" ], [ "LAST ACTION HERO", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "LAST TRAIN FROM GUN HILL", "has_genre", "WESTERN" ], [ "LAST TRAIN FROM GUN HILL", "starred_actors", "KIRK DOUGLAS" ], [ "POSSE", "directed_by", "KIRK DOUGLAS" ], [ "POSSE", "has_genre", "WESTERN" ], [ "POSSE", "release_year", "1993" ], [ "POSSE", "starred_actors", "KIRK DOUGLAS" ], [ "SUTURE", "release_year", "1993" ], [ "THE BALLAD OF LITTLE JO", "has_genre", "WESTERN" ], [ "THE BALLAD OF LITTLE JO", "release_year", "1993" ], [ "THE BIG SKY", "has_genre", "WESTERN" ], [ "THE BIG SKY", "starred_actors", "KIRK DOUGLAS" ], [ "THE CASTLE", "has_tags", "FRANZ KAFKA" ], [ "THE CASTLE", "release_year", "1997" ], [ "THE CASTLE", "written_by", "FRANZ KAFKA" ], [ "THE LAST SUNSET", "has_genre", "WESTERN" ], [ "THE LAST SUNSET", "starred_actors", "KIRK DOUGLAS" ], [ "THE VILLAIN", "has_genre", "WESTERN" ], [ "THE VILLAIN", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "THE VILLAIN", "starred_actors", "KIRK DOUGLAS" ], [ "THE WAR WAGON", "has_genre", "WESTERN" ], [ "THE WAR WAGON", "has_tags", "KIRK DOUGLAS" ], [ "THE WAR WAGON", "starred_actors", "KIRK DOUGLAS" ], [ "TOMBSTONE", "has_tags", "WESTERN" ], [ "TOMBSTONE", "release_year", "1993" ], [ "WESTERN", "release_year", "1997" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 26762, 2008 18239, A RAISIN IN THE SUN 35253, ACE OF HEARTS 25639, BEDTIME STORIES 21862, COLLEGE ROAD TRIP 10509, FAMILY 25086, FRENCH FILM 15629, HOME ALONE 4 21518, HONEY, I SHRUNK THE KIDS 6713, KAMCHATKA 33783, KRISTINE SUTHERLAND 31974, MANITO 20844, MEET DAVE 14026, PINOCCHIO 1507, ROAD TO PERDITION 24467, SPEED RACER 32587, SUMMER HOURS 7013, THE COUNTRY BEARS 4872, THE SPIDERWICK CHRONICLES 15632, THUNDERPANTS 900, TUCK EVERLASTING src, edge_attr, dst 18239, has_tags, 10509 18239, release_year, 26762 35253, has_genre, 10509 35253, release_year, 26762 25639, has_genre, 10509 25639, release_year, 26762 21862, has_tags, 10509 21862, release_year, 26762 25086, release_year, 26762 15629, has_genre, 10509 15629, release_year, 35935 21518, has_genre, 10509 21518, has_tags, 10509 21518, starred_actors, 33783 6713, has_tags, 10509 6713, release_year, 35935 31974, has_genre, 10509 31974, release_year, 35935 20844, has_genre, 10509 20844, release_year, 26762 14026, has_genre, 10509 14026, release_year, 35935 1507, has_tags, 10509 1507, release_year, 35935 24467, has_genre, 10509 24467, release_year, 26762 32587, has_genre, 10509 32587, release_year, 26762 7013, has_genre, 10509 7013, release_year, 35935 4872, has_genre, 10509 4872, release_year, 26762 15632, has_genre, 10509 15632, release_year, 35935 900, has_genre, 10509 900, release_year, 35935 Question: How are FRENCH FILM, KRISTINE SUTHERLAND, and MANITO related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FRENCH FILM", "KRISTINE SUTHERLAND", "MANITO" ], "valid_edges": [ [ "A RAISIN IN THE SUN", "has_tags", "FAMILY" ], [ "A RAISIN IN THE SUN", "release_year", "2008" ], [ "ACE OF HEARTS", "has_genre", "FAMILY" ], [ "ACE OF HEARTS", "release_year", "2008" ], [ "BEDTIME STORIES", "has_genre", "FAMILY" ], [ "BEDTIME STORIES", "release_year", "2008" ], [ "COLLEGE ROAD TRIP", "has_tags", "FAMILY" ], [ "COLLEGE ROAD TRIP", "release_year", "2008" ], [ "FRENCH FILM", "release_year", "2008" ], [ "HOME ALONE 4", "has_genre", "FAMILY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "HONEY, I SHRUNK THE KIDS", "has_genre", "FAMILY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "FAMILY" ], [ "HONEY, I SHRUNK THE KIDS", "starred_actors", "KRISTINE SUTHERLAND" ], [ "KAMCHATKA", "has_tags", "FAMILY" ], [ "KAMCHATKA", "release_year", "2002" ], [ "MANITO", "has_genre", "FAMILY" ], [ "MANITO", "release_year", "2002" ], [ "MEET DAVE", "has_genre", "FAMILY" ], [ "MEET DAVE", "release_year", "2008" ], [ "PINOCCHIO", "has_genre", "FAMILY" ], [ "PINOCCHIO", "release_year", "2002" ], [ "ROAD TO PERDITION", "has_tags", "FAMILY" ], [ "ROAD TO PERDITION", "release_year", "2002" ], [ "SPEED RACER", "has_genre", "FAMILY" ], [ "SPEED RACER", "release_year", "2008" ], [ "SUMMER HOURS", "has_genre", "FAMILY" ], [ "SUMMER HOURS", "release_year", "2008" ], [ "THE COUNTRY BEARS", "has_genre", "FAMILY" ], [ "THE COUNTRY BEARS", "release_year", "2002" ], [ "THE SPIDERWICK CHRONICLES", "has_genre", "FAMILY" ], [ "THE SPIDERWICK CHRONICLES", "release_year", "2008" ], [ "THUNDERPANTS", "has_genre", "FAMILY" ], [ "THUNDERPANTS", "release_year", "2002" ], [ "TUCK EVERLASTING", "has_genre", "FAMILY" ], [ "TUCK EVERLASTING", "release_year", "2002" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14004, 1955 29424, 2011 23373, ARTISTS AND MODELS 12155, DADDY LONG LEGS 4057, FOOTLIGHT PARADE 28905, GOLD DIGGERS OF 1933 12244, GUYS AND DOLLS 6813, IT'S ALWAYS FAIR WEATHER 5208, JAMES CAGNEY 103, LOVE ME OR LEAVE ME 7765, LOVELY TO LOOK AT 34605, MERVYN LEROY 6961, MILLION DOLLAR MERMAID 31701, MISTER ROBERTS 9327, MONTE CARLO 24593, MUSICAL 8397, MY SISTER EILEEN 18184, OKLAHOMA! 33981, PARANORMAL ACTIVITY 3 20243, RUN FOR COVER 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 30311, THE COURT JESTER 12773, THE GLASS SLIPPER 11189, THE MUPPETS 31313, THE WEST POINT STORY 3043, YANKEE DOODLE DANDY src, edge_attr, dst 23373, has_genre, 24593 23373, release_year, 14004 12155, has_genre, 24593 12155, has_tags, 24593 12155, release_year, 14004 4057, has_genre, 24593 4057, has_tags, 5208 4057, has_tags, 24593 4057, starred_actors, 5208 28905, directed_by, 34605 28905, has_genre, 24593 28905, has_tags, 34605 12244, has_genre, 24593 12244, release_year, 14004 6813, has_genre, 24593 6813, release_year, 14004 103, release_year, 14004 103, starred_actors, 5208 7765, directed_by, 34605 7765, has_genre, 24593 6961, directed_by, 34605 6961, has_genre, 24593 31701, directed_by, 34605 31701, has_tags, 5208 31701, has_tags, 34605 31701, release_year, 14004 31701, starred_actors, 5208 9327, has_genre, 24593 9327, release_year, 29424 8397, has_genre, 24593 8397, release_year, 14004 18184, has_genre, 24593 18184, has_tags, 24593 18184, release_year, 14004 33981, release_year, 29424 20243, release_year, 14004 20243, starred_actors, 5208 10409, has_genre, 24593 30311, has_tags, 24593 30311, release_year, 14004 12773, has_genre, 24593 12773, release_year, 14004 11189, has_genre, 24593 11189, has_tags, 24593 11189, release_year, 29424 31313, has_tags, 5208 31313, has_tags, 24593 31313, starred_actors, 5208 3043, has_genre, 24593 3043, has_tags, 5208 3043, has_tags, 24593 3043, starred_actors, 5208 Question: For what reason are MISTER ROBERTS, PARANORMAL ACTIVITY 3, and THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MISTER ROBERTS", "PARANORMAL ACTIVITY 3", "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER" ], "valid_edges": [ [ "ARTISTS AND MODELS", "has_genre", "MUSICAL" ], [ "ARTISTS AND MODELS", "release_year", "1955" ], [ "DADDY LONG LEGS", "has_genre", "MUSICAL" ], [ "DADDY LONG LEGS", "has_tags", "MUSICAL" ], [ "DADDY LONG LEGS", "release_year", "1955" ], [ "FOOTLIGHT PARADE", "has_genre", "MUSICAL" ], [ "FOOTLIGHT PARADE", "has_tags", "JAMES CAGNEY" ], [ "FOOTLIGHT PARADE", "has_tags", "MUSICAL" ], [ "FOOTLIGHT PARADE", "starred_actors", "JAMES CAGNEY" ], [ "GOLD DIGGERS OF 1933", "directed_by", "MERVYN LEROY" ], [ "GOLD DIGGERS OF 1933", "has_genre", "MUSICAL" ], [ "GOLD DIGGERS OF 1933", "has_tags", "MERVYN LEROY" ], [ "GUYS AND DOLLS", "has_genre", "MUSICAL" ], [ "GUYS AND DOLLS", "release_year", "1955" ], [ "IT'S ALWAYS FAIR WEATHER", "has_genre", "MUSICAL" ], [ "IT'S ALWAYS FAIR WEATHER", "release_year", "1955" ], [ "LOVE ME OR LEAVE ME", "release_year", "1955" ], [ "LOVE ME OR LEAVE ME", "starred_actors", "JAMES CAGNEY" ], [ "LOVELY TO LOOK AT", "directed_by", "MERVYN LEROY" ], [ "LOVELY TO LOOK AT", "has_genre", "MUSICAL" ], [ "MILLION DOLLAR MERMAID", "directed_by", "MERVYN LEROY" ], [ "MILLION DOLLAR MERMAID", "has_genre", "MUSICAL" ], [ "MISTER ROBERTS", "directed_by", "MERVYN LEROY" ], [ "MISTER ROBERTS", "has_tags", "JAMES CAGNEY" ], [ "MISTER ROBERTS", "has_tags", "MERVYN LEROY" ], [ "MISTER ROBERTS", "release_year", "1955" ], [ "MISTER ROBERTS", "starred_actors", "JAMES CAGNEY" ], [ "MONTE CARLO", "has_genre", "MUSICAL" ], [ "MONTE CARLO", "release_year", "2011" ], [ "MY SISTER EILEEN", "has_genre", "MUSICAL" ], [ "MY SISTER EILEEN", "release_year", "1955" ], [ "OKLAHOMA!", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_tags", "MUSICAL" ], [ "OKLAHOMA!", "release_year", "1955" ], [ "PARANORMAL ACTIVITY 3", "release_year", "2011" ], [ "RUN FOR COVER", "release_year", "1955" ], [ "RUN FOR COVER", "starred_actors", "JAMES CAGNEY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "MUSICAL" ], [ "THE COURT JESTER", "has_tags", "MUSICAL" ], [ "THE COURT JESTER", "release_year", "1955" ], [ "THE GLASS SLIPPER", "has_genre", "MUSICAL" ], [ "THE GLASS SLIPPER", "release_year", "1955" ], [ "THE MUPPETS", "has_genre", "MUSICAL" ], [ "THE MUPPETS", "has_tags", "MUSICAL" ], [ "THE MUPPETS", "release_year", "2011" ], [ "THE WEST POINT STORY", "has_tags", "JAMES CAGNEY" ], [ "THE WEST POINT STORY", "has_tags", "MUSICAL" ], [ "THE WEST POINT STORY", "starred_actors", "JAMES CAGNEY" ], [ "YANKEE DOODLE DANDY", "has_genre", "MUSICAL" ], [ "YANKEE DOODLE DANDY", "has_tags", "JAMES CAGNEY" ], [ "YANKEE DOODLE DANDY", "has_tags", "MUSICAL" ], [ "YANKEE DOODLE DANDY", "starred_actors", "JAMES CAGNEY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 30146, A CHRISTMAS CAROL 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 16486, AGENT CODY BANKS 39750, ALIENS 10507, ALIENS IN THE ATTIC 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 18310, AROUND THE WORLD IN 80 DAYS 38657, BEAT THE DEVIL 16795, CASANOVA'S BIG NIGHT 524, CHARLIE'S ANGELS 30463, COMEDY 30802, CUTTHROAT ISLAND 1329, ENVY 2449, EUROTRIP 549, GENTARO NAKAJIMA 39494, HOLES 358, HOWARD THE DUCK 1628, HUMPDAY 24061, INFESTATION 28405, JENNIFER'S BODY 6222, JOHN LARROQUETTE 34939, LO 26370, MADHOUSE 32058, MUPPET TREASURE ISLAND 14797, O BROTHER, WHERE ART THOU? 2391, PIRATES 31703, PUSS IN BOOTS 28221, ROMANCING THE STONE 35586, SAHARA 5629, SCOOBY-DOO! THE MYSTERY BEGINS 38231, SHANGHAI NOON 34989, STAR TREK 26790, SWEPT AWAY 13521, THE ADVENTURES OF FORD FAIRLANE 21330, THE CRIMSON PIRATE 18263, THE DUKES OF HAZZARD 4068, THE GENERAL 18150, THE JEWEL OF THE NILE 31851, THE PRISONER OF ZENDA 35221, THE REVENANT 30746, THE SECRET LIFE OF WALTER MITTY 15608, THE SPONGEBOB SQUAREPANTS MOVIE 7816, THE THREE MUSKETEERS 25443, TOM JONES 26828, TORMENTED 14499, TOY STORY 2 14057, TRANSYLMANIA 11659, VIVA MARIA! 36315, WARNING FROM SPACE src, edge_attr, dst 30146, has_genre, 30463 30146, release_year, 27261 16054, has_genre, 4763 16054, has_genre, 30463 16054, has_tags, 4763 16486, has_genre, 4763 16486, has_genre, 30463 39750, has_genre, 4763 10507, has_genre, 30463 10507, release_year, 27261 22412, has_genre, 4763 22412, has_genre, 30463 22412, has_tags, 4763 18310, has_genre, 4763 18310, has_genre, 30463 38657, has_genre, 4763 38657, has_genre, 30463 16795, has_genre, 4763 16795, has_genre, 30463 524, has_genre, 4763 524, has_genre, 30463 30802, has_genre, 4763 30802, has_genre, 30463 30802, has_tags, 4763 1329, has_genre, 30463 1329, release_year, 27261 2449, has_genre, 4763 2449, has_genre, 30463 2449, has_tags, 30463 39494, has_genre, 4763 39494, has_genre, 30463 358, has_genre, 4763 358, has_genre, 30463 1628, has_genre, 30463 1628, has_tags, 30463 1628, release_year, 27261 24061, has_genre, 30463 24061, release_year, 27261 28405, has_genre, 30463 28405, has_tags, 30463 28405, release_year, 27261 34939, has_genre, 30463 34939, release_year, 27261 26370, has_genre, 30463 26370, starred_actors, 6222 32058, has_genre, 4763 32058, has_genre, 30463 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 2391, has_genre, 4763 2391, has_genre, 30463 31703, has_genre, 4763 31703, has_genre, 30463 28221, has_genre, 4763 28221, has_genre, 30463 28221, has_tags, 4763 35586, has_genre, 4763 35586, has_genre, 30463 5629, has_genre, 4763 5629, has_genre, 30463 5629, release_year, 27261 38231, has_genre, 4763 38231, has_genre, 30463 34989, has_genre, 4763 34989, has_tags, 4763 34989, release_year, 27261 26790, has_genre, 4763 26790, has_genre, 30463 13521, has_genre, 4763 13521, has_genre, 30463 13521, has_tags, 30463 21330, has_genre, 4763 21330, has_genre, 30463 18263, has_genre, 4763 18263, has_genre, 30463 4068, has_genre, 4763 4068, has_genre, 30463 4068, has_tags, 30463 18150, has_genre, 4763 18150, has_genre, 30463 18150, has_tags, 4763 18150, has_tags, 30463 31851, has_genre, 4763 31851, has_genre, 30463 35221, has_genre, 30463 35221, release_year, 27261 30746, has_genre, 4763 30746, has_genre, 30463 15608, has_genre, 4763 15608, has_genre, 30463 7816, has_genre, 4763 7816, has_genre, 30463 25443, has_genre, 4763 25443, has_genre, 30463 26828, has_tags, 30463 26828, release_year, 27261 14499, has_genre, 4763 14499, has_genre, 30463 14057, has_genre, 30463 14057, release_year, 27261 11659, has_genre, 4763 11659, has_genre, 30463 36315, has_tags, 39750 36315, written_by, 549 Question: In what context are GENTARO NAKAJIMA, JOHN LARROQUETTE, and SCOOBY-DOO! THE MYSTERY BEGINS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GENTARO NAKAJIMA", "JOHN LARROQUETTE", "SCOOBY-DOO! THE MYSTERY BEGINS" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "release_year", "2009" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "COMEDY" ], [ "ALIENS", "has_genre", "ADVENTURE" ], [ "ALIENS IN THE ATTIC", "has_genre", "COMEDY" ], [ "ALIENS IN THE ATTIC", "release_year", "2009" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "ADVENTURE" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "ENVY", "has_genre", "COMEDY" ], [ "ENVY", "release_year", "2009" ], [ "EUROTRIP", "has_genre", "ADVENTURE" ], [ "EUROTRIP", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_tags", "COMEDY" ], [ "HOLES", "has_genre", "ADVENTURE" ], [ "HOLES", "has_genre", "COMEDY" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "HUMPDAY", "has_genre", "COMEDY" ], [ "HUMPDAY", "has_tags", "COMEDY" ], [ "HUMPDAY", "release_year", "2009" ], [ "INFESTATION", "has_genre", "COMEDY" ], [ "INFESTATION", "release_year", "2009" ], [ "JENNIFER'S BODY", "has_genre", "COMEDY" ], [ "JENNIFER'S BODY", "has_tags", "COMEDY" ], [ "JENNIFER'S BODY", "release_year", "2009" ], [ "LO", "has_genre", "COMEDY" ], [ "LO", "release_year", "2009" ], [ "MADHOUSE", "has_genre", "COMEDY" ], [ "MADHOUSE", "starred_actors", "JOHN LARROQUETTE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "PIRATES", "has_genre", "ADVENTURE" ], [ "PIRATES", "has_genre", "COMEDY" ], [ "PUSS IN BOOTS", "has_genre", "ADVENTURE" ], [ "PUSS IN BOOTS", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "ADVENTURE" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "COMEDY" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "release_year", "2009" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHANGHAI NOON", "has_genre", "COMEDY" ], [ "STAR TREK", "has_genre", "ADVENTURE" ], [ "STAR TREK", "has_tags", "ADVENTURE" ], [ "STAR TREK", "release_year", "2009" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_genre", "COMEDY" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE DUKES OF HAZZARD", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_genre", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE REVENANT", "has_genre", "COMEDY" ], [ "THE REVENANT", "release_year", "2009" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "ADVENTURE" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_genre", "COMEDY" ], [ "TORMENTED", "has_tags", "COMEDY" ], [ "TORMENTED", "release_year", "2009" ], [ "TOY STORY 2", "has_genre", "ADVENTURE" ], [ "TOY STORY 2", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "release_year", "2009" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "WARNING FROM SPACE", "has_tags", "ALIENS" ], [ "WARNING FROM SPACE", "written_by", "GENTARO NAKAJIMA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24004, 10 21931, 1941 31486, 1970 724, 1979 25221, 1981 3085, A LITTLE PRINCESS 12649, A LITTLE ROMANCE 21158, A TOUCH OF CLASS 1216, AMERICATHON 36833, BARBRA STREISAND 34744, BEING THERE 23022, BOARDING SCHOOL 16452, BORN TO WIN 37601, BREAKING AWAY 5800, CARBON COPY 13302, CHAPTER TWO 38678, CHILLY SCENES OF WINTER 30463, COMEDY 36212, DRAMA 19367, ESCAPE TO ATHENA 9048, EVIL 9130, FUN WITH DICK AND JANE 19579, GEORGE SEGAL 10481, GLENDA JACKSON 35760, H.O.T.S. 20263, HAIR 24681, LOOK WHO'S TALKING 2781, LOST AND FOUND 11331, LOVE AT FIRST BITE 34700, LOVING 33790, MANHATTAN 6108, MEATBALLS 27102, MELVIN FRANK 26484, MORE AMERICAN GRAFFITI 6773, REAL LIFE 22107, ROCK 'N' ROLL HIGH SCHOOL 27231, STARTING OVER 16018, THE APPLE DUMPLING GANG RIDES AGAIN 28510, THE FRISCO KID 32636, THE HOT ROCK 19104, THE IN-LAWS 33024, THE JERK 4091, THE LADY VANISHES 32382, THE MAIN EVENT 17527, THE MIRROR HAS TWO FACES 12809, THE MUPPET MOVIE 2080, THE OWL AND THE PUSSYCAT 31851, THE PRISONER OF ZENDA 26036, THE TEMPEST 31435, UNCLE MARIN, THE BILLIONAIRE 28231, WHERE'S POPPA? 14695, WHO IS KILLING THE GREAT CHEFS OF EUROPE? 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 22774, WISE BLOOD src, edge_attr, dst 24004, has_genre, 30463 24004, release_year, 724 21931, has_genre, 30463 21931, release_year, 724 25221, has_genre, 30463 3085, has_genre, 36212 3085, has_tags, 23022 12649, has_genre, 30463 12649, release_year, 724 21158, directed_by, 27102 21158, has_genre, 30463 21158, starred_actors, 19579 21158, starred_actors, 10481 21158, written_by, 27102 1216, has_genre, 30463 1216, release_year, 724 34744, has_genre, 30463 34744, release_year, 724 16452, has_genre, 30463 16452, starred_actors, 19579 37601, has_genre, 30463 37601, release_year, 724 5800, has_genre, 30463 5800, release_year, 25221 5800, starred_actors, 19579 13302, has_genre, 30463 13302, release_year, 724 38678, has_genre, 30463 38678, release_year, 724 19367, has_genre, 30463 19367, release_year, 724 9048, has_genre, 36212 9048, has_tags, 23022 9130, has_genre, 30463 9130, starred_actors, 19579 35760, has_genre, 30463 35760, release_year, 724 20263, has_genre, 30463 20263, release_year, 724 24681, has_genre, 30463 24681, has_tags, 30463 24681, starred_actors, 19579 2781, directed_by, 27102 2781, release_year, 724 2781, starred_actors, 19579 2781, starred_actors, 10481 2781, written_by, 27102 11331, has_genre, 30463 11331, release_year, 724 34700, has_genre, 30463 34700, release_year, 31486 34700, starred_actors, 19579 33790, has_genre, 30463 33790, has_tags, 30463 33790, release_year, 724 6108, has_genre, 30463 6108, release_year, 724 26484, has_genre, 30463 26484, release_year, 724 6773, has_genre, 30463 6773, release_year, 724 22107, has_genre, 30463 22107, release_year, 724 27231, has_genre, 30463 27231, release_year, 724 16018, has_genre, 30463 16018, release_year, 724 28510, has_genre, 30463 28510, release_year, 724 32636, has_genre, 30463 32636, starred_actors, 19579 19104, has_genre, 30463 19104, release_year, 724 33024, has_genre, 30463 33024, release_year, 724 4091, has_genre, 30463 4091, release_year, 724 32382, has_genre, 30463 32382, release_year, 724 17527, directed_by, 36833 17527, has_genre, 30463 17527, has_genre, 36212 17527, has_tags, 36833 17527, starred_actors, 36833 17527, starred_actors, 19579 12809, has_genre, 30463 12809, release_year, 724 2080, has_genre, 30463 2080, release_year, 31486 2080, starred_actors, 36833 2080, starred_actors, 19579 31851, has_genre, 30463 31851, release_year, 724 26036, has_genre, 30463 26036, release_year, 724 31435, has_genre, 30463 31435, release_year, 724 28231, has_genre, 30463 28231, release_year, 31486 28231, starred_actors, 19579 14695, has_genre, 30463 14695, starred_actors, 19579 35212, has_genre, 36212 35212, starred_actors, 19579 22774, has_genre, 30463 22774, release_year, 724 Question: In what context are BOARDING SCHOOL, GEORGE SEGAL, and THE MUPPET MOVIE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BOARDING SCHOOL", "GEORGE SEGAL", "THE MUPPET MOVIE" ], "valid_edges": [ [ "10", "has_genre", "COMEDY" ], [ "10", "release_year", "1979" ], [ "1941", "has_genre", "COMEDY" ], [ "1941", "release_year", "1979" ], [ "1981", "has_genre", "COMEDY" ], [ "A LITTLE PRINCESS", "has_genre", "DRAMA" ], [ "A LITTLE PRINCESS", "has_tags", "BOARDING SCHOOL" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "release_year", "1979" ], [ "A TOUCH OF CLASS", "directed_by", "MELVIN FRANK" ], [ "A TOUCH OF CLASS", "has_genre", "COMEDY" ], [ "A TOUCH OF CLASS", "starred_actors", "GEORGE SEGAL" ], [ "A TOUCH OF CLASS", "starred_actors", "GLENDA JACKSON" ], [ "A TOUCH OF CLASS", "written_by", "MELVIN FRANK" ], [ "AMERICATHON", "has_genre", "COMEDY" ], [ "AMERICATHON", "release_year", "1979" ], [ "BEING THERE", "has_genre", "COMEDY" ], [ "BEING THERE", "release_year", "1979" ], [ "BORN TO WIN", "has_genre", "COMEDY" ], [ "BORN TO WIN", "starred_actors", "GEORGE SEGAL" ], [ "BREAKING AWAY", "has_genre", "COMEDY" ], [ "BREAKING AWAY", "release_year", "1979" ], [ "CARBON COPY", "has_genre", "COMEDY" ], [ "CARBON COPY", "release_year", "1981" ], [ "CARBON COPY", "starred_actors", "GEORGE SEGAL" ], [ "CHAPTER TWO", "has_genre", "COMEDY" ], [ "CHAPTER TWO", "release_year", "1979" ], [ "CHILLY SCENES OF WINTER", "has_genre", "COMEDY" ], [ "CHILLY SCENES OF WINTER", "release_year", "1979" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "ESCAPE TO ATHENA", "release_year", "1979" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "has_tags", "BOARDING SCHOOL" ], [ "FUN WITH DICK AND JANE", "has_genre", "COMEDY" ], [ "FUN WITH DICK AND JANE", "starred_actors", "GEORGE SEGAL" ], [ "H.O.T.S.", "has_genre", "COMEDY" ], [ "H.O.T.S.", "release_year", "1979" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "release_year", "1979" ], [ "LOOK WHO'S TALKING", "has_genre", "COMEDY" ], [ "LOOK WHO'S TALKING", "has_tags", "COMEDY" ], [ "LOOK WHO'S TALKING", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "directed_by", "MELVIN FRANK" ], [ "LOST AND FOUND", "release_year", "1979" ], [ "LOST AND FOUND", "starred_actors", "GEORGE SEGAL" ], [ "LOST AND FOUND", "starred_actors", "GLENDA JACKSON" ], [ "LOST AND FOUND", "written_by", "MELVIN FRANK" ], [ "LOVE AT FIRST BITE", "has_genre", "COMEDY" ], [ "LOVE AT FIRST BITE", "release_year", "1979" ], [ "LOVING", "has_genre", "COMEDY" ], [ "LOVING", "release_year", "1970" ], [ "LOVING", "starred_actors", "GEORGE SEGAL" ], [ "MANHATTAN", "has_genre", "COMEDY" ], [ "MANHATTAN", "has_tags", "COMEDY" ], [ "MANHATTAN", "release_year", "1979" ], [ "MEATBALLS", "has_genre", "COMEDY" ], [ "MEATBALLS", "release_year", "1979" ], [ "MORE AMERICAN GRAFFITI", "has_genre", "COMEDY" ], [ "MORE AMERICAN GRAFFITI", "release_year", "1979" ], [ "REAL LIFE", "has_genre", "COMEDY" ], [ "REAL LIFE", "release_year", "1979" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "release_year", "1979" ], [ "STARTING OVER", "has_genre", "COMEDY" ], [ "STARTING OVER", "release_year", "1979" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "has_genre", "COMEDY" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "release_year", "1979" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "release_year", "1979" ], [ "THE HOT ROCK", "has_genre", "COMEDY" ], [ "THE HOT ROCK", "starred_actors", "GEORGE SEGAL" ], [ "THE IN-LAWS", "has_genre", "COMEDY" ], [ "THE IN-LAWS", "release_year", "1979" ], [ "THE JERK", "has_genre", "COMEDY" ], [ "THE JERK", "release_year", "1979" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1979" ], [ "THE MAIN EVENT", "has_genre", "COMEDY" ], [ "THE MAIN EVENT", "release_year", "1979" ], [ "THE MIRROR HAS TWO FACES", "directed_by", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "COMEDY" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "DRAMA" ], [ "THE MIRROR HAS TWO FACES", "has_tags", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "BARBRA STREISAND" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "GEORGE SEGAL" ], [ "THE MUPPET MOVIE", "has_genre", "COMEDY" ], [ "THE MUPPET MOVIE", "release_year", "1979" ], [ "THE OWL AND THE PUSSYCAT", "has_genre", "COMEDY" ], [ "THE OWL AND THE PUSSYCAT", "release_year", "1970" ], [ "THE OWL AND THE PUSSYCAT", "starred_actors", "BARBRA STREISAND" ], [ "THE OWL AND THE PUSSYCAT", "starred_actors", "GEORGE SEGAL" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "release_year", "1979" ], [ "THE TEMPEST", "has_genre", "COMEDY" ], [ "THE TEMPEST", "release_year", "1979" ], [ "UNCLE MARIN, THE BILLIONAIRE", "has_genre", "COMEDY" ], [ "UNCLE MARIN, THE BILLIONAIRE", "release_year", "1979" ], [ "WHERE'S POPPA?", "has_genre", "COMEDY" ], [ "WHERE'S POPPA?", "release_year", "1970" ], [ "WHERE'S POPPA?", "starred_actors", "GEORGE SEGAL" ], [ "WHO IS KILLING THE GREAT CHEFS OF EUROPE?", "has_genre", "COMEDY" ], [ "WHO IS KILLING THE GREAT CHEFS OF EUROPE?", "starred_actors", "GEORGE SEGAL" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_genre", "DRAMA" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "starred_actors", "GEORGE SEGAL" ], [ "WISE BLOOD", "has_genre", "COMEDY" ], [ "WISE BLOOD", "release_year", "1979" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18132, 1938 25221, 1981 36647, 8 WOMEN 30146, A CHRISTMAS CAROL 9698, A CHRISTMAS TALE 12649, A LITTLE ROMANCE 16566, A MONKEY IN WINTER 9230, A SLIGHT CASE OF MURDER 11188, A WOMAN IS A WOMAN 4028, AALTRA 13939, ALL TOGETHER 12224, AMÉLIE 36929, ANNABEL TAKES A TOUR 6200, ATTILA MARCEL 17083, BABYSITTING 10067, BERNIE 340, BLOCK-HEADS 11298, BOLIVIA 10081, BOTTLE SHOCK 8655, BOY MEETS GIRL 15416, BOYFRIENDS AND GIRLFRIENDS 235, BRINGING UP BABY 23286, CARNAGE 230, CARNIVAL IN FLANDERS 18400, CASE DÉPART 21981, CHOUCHOU 30463, COMEDY 16536, CYRANO DE BERGERAC 22667, DAYS OF DARKNESS 9709, DE L'AUTRE CÔTÉ DU LIT 6375, DELICACY 30433, DELUSIONS OF GRANDEUR 36212, DRAMA 32892, ENGLISH VINGLISH 17072, FAREWELL, HOME SWEET HOME 22941, FATHER AND GUNS 33845, FISTON 9539, FREDDY FLORES 6012, FRENCH 4096, FRENCH KISS 13389, FRENCH TWIST 23743, GET OUT YOUR HANDKERCHIEFS 5527, GIGI 37514, GOING PLACES 26909, GREEN CARD 38162, HAPPINESS IS IN THE FIELD 34345, HAPPINESS NEVER COMES ALONE 12085, HAPPY NEW YEAR 11783, HEARTBREAKER 7289, HOLIDAY 4429, HOW MUCH DO YOU LOVE ME? 10411, HOW TASTY WAS MY LITTLE FRENCHMAN 35625, HUMAN NATURE 38589, I DO 27285, I WAS A MALE WAR BRIDE 38392, I, CESAR 18699, JULIET OF THE SPIRITS 23366, JUST AROUND THE CORNER 16839, JUST VISITING 14209, KING OF HEARTS 24238, L'AGE D'OR 15175, LE HAVRE 22443, LE MILLION 19966, LE PLAISIR 25390, LIFE IS A LONG QUIET RIVER 16814, LITTLE WHITE LIES 17372, LOL 10284, LOVE FINDS ANDY HARDY 10560, MAN BITES DOG 34969, MAN-PROOF 39509, MARCEL PAGNOL 22420, ME, MYSELF AND MUM 3092, MERRILY WE LIVE 31657, MON ONCLE 17748, MY WIFE IS AN ACTRESS 12152, NOTHING TO DECLARE 32901, ON TOUR 352, ONE HUNDRED AND ONE NIGHTS 11056, PAULETTE 5958, PERCHED ON A TREE 5311, PLAYTIME 10493, POPULAIRE 33032, PORT OF SHADOWS 11213, POTICHE 15021, PROFESSOR BEWARE 9019, RATATOUILLE 22488, REBECCA OF SUNNYBROOK FARM 6201, ROOM SERVICE 18478, RUSH HOUR 3 4689, SABRINA 24060, SEDUCING DOCTOR LEWIS 6603, SEX IS COMEDY 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 39915, SHALL WE KISS? 28126, SHEITAN 15380, SIDEWALKS OF LONDON 30664, SMOKING/NO SMOKING 17447, SON OF RAMBOW 7175, STOLEN KISSES 39270, SUBWAY 16165, SUPERCONDRIAQUE 345, TANGUY 10732, TAXI 8416, TAXI 3 24351, TAXI 4 9091, THE ADVENTURES OF PICASSO 24625, THE APARTMENT 39795, THE ARTIST 8234, THE BAKER'S WIFE 38965, THE BARBARIAN INVASIONS 32454, THE BIG PICTURE 14643, THE BRAIN 39773, THE CLINK OF ICE 30164, THE CLOSET 33017, THE COWBOY AND THE LADY 13316, THE DECLINE OF THE AMERICAN EMPIRE 29539, THE DIVORCE OF LADY X 38918, THE FAMILY 12169, THE FRENCH MINISTER 9093, THE GRAND MANEUVER 22995, THE HAPPY ROAD 6289, THE INTOUCHABLES 4091, THE LADY VANISHES 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 31569, THE LOVE PARADE 7954, THE MAD MISS MANTON 33513, THE MAN WHO LOVED WOMEN 32297, THE MERRY WIDOW 38843, THE MURDERER LIVES AT NUMBER 21 31851, THE PRISONER OF ZENDA 37461, THE RULES OF THE GAME 11383, THE SCIENCE OF SLEEP 15930, THE SUCKER 36903, THE SUITOR 26678, THE SWINDLE 11663, THE TALL BLOND MAN WITH ONE BLACK SHOE 26185, THE TOY 25591, THE TRIPLETS OF BELLEVILLE 4542, THE VALET 13003, THE WELL-DIGGER'S DAUGHTER 26408, THE WISE GUYS 6471, THE YOUNG IN HEART 5128, THERE GOES MY HEART 22238, THERE'S ALWAYS A WOMAN 1459, TOO BEAUTIFUL FOR YOU 17536, TRAFIC 12860, TRUE LIES 3286, UNDER THE ROOFS OF PARIS 31732, URANUS 37344, VERY HAPPY ALEXANDER 11659, VIVA MARIA! 13631, VIVACIOUS LADY 29077, WASABI 35511, WE HAVE A POPE 22241, WE'RE NO ANGELS 33483, WEEKEND 5927, WELLS ROOT 38905, WHAT'S IN A NAME? 3569, WHY NOT ME? 22756, WINDOW TO PARIS 367, WITH LOVE... FROM THE AGE OF REASON 8184, YOU CAN'T TAKE IT WITH YOU src, edge_attr, dst 25221, has_genre, 30463 25221, in_language, 6012 36647, has_genre, 30463 36647, has_tags, 6012 36647, in_language, 6012 30146, has_genre, 30463 30146, release_year, 18132 9698, has_genre, 30463 9698, in_language, 6012 12649, has_genre, 30463 12649, in_language, 6012 16566, has_genre, 30463 16566, in_language, 6012 9230, has_genre, 30463 9230, has_tags, 30463 9230, release_year, 18132 11188, has_genre, 30463 11188, in_language, 6012 4028, has_genre, 30463 4028, in_language, 6012 13939, has_genre, 30463 13939, in_language, 6012 12224, has_genre, 30463 12224, has_tags, 30463 12224, has_tags, 6012 12224, in_language, 6012 36929, has_genre, 30463 36929, release_year, 18132 6200, has_genre, 30463 6200, in_language, 6012 17083, has_genre, 30463 17083, in_language, 6012 10067, has_genre, 30463 10067, in_language, 6012 340, has_genre, 30463 340, release_year, 18132 11298, has_genre, 36212 11298, starred_actors, 9539 10081, has_genre, 30463 10081, in_language, 6012 8655, has_genre, 30463 8655, in_language, 6012 8655, release_year, 18132 15416, has_genre, 30463 15416, in_language, 6012 235, has_genre, 30463 235, has_tags, 30463 235, release_year, 18132 23286, has_genre, 30463 23286, in_language, 6012 230, has_genre, 30463 230, in_language, 6012 18400, has_genre, 30463 18400, has_tags, 6012 18400, in_language, 6012 21981, has_genre, 30463 21981, has_tags, 6012 21981, in_language, 6012 16536, has_genre, 30463 16536, has_tags, 6012 16536, in_language, 6012 22667, has_genre, 30463 22667, in_language, 6012 9709, has_genre, 30463 9709, in_language, 6012 6375, has_genre, 30463 6375, in_language, 6012 30433, has_genre, 30463 30433, in_language, 6012 32892, has_genre, 30463 32892, in_language, 6012 17072, has_genre, 30463 17072, in_language, 6012 22941, has_genre, 30463 22941, in_language, 6012 33845, has_genre, 30463 33845, has_tags, 6012 33845, in_language, 6012 4096, has_genre, 30463 4096, has_tags, 30463 4096, in_language, 6012 13389, has_genre, 30463 13389, in_language, 6012 23743, has_genre, 30463 23743, in_language, 6012 5527, has_genre, 30463 5527, in_language, 6012 37514, has_genre, 30463 37514, in_language, 6012 26909, has_genre, 30463 26909, in_language, 6012 38162, has_genre, 30463 38162, in_language, 6012 34345, has_genre, 30463 34345, in_language, 6012 12085, has_genre, 30463 12085, in_language, 6012 11783, has_genre, 30463 11783, has_tags, 6012 11783, in_language, 6012 7289, has_genre, 30463 7289, has_tags, 30463 7289, release_year, 18132 4429, has_genre, 30463 4429, in_language, 6012 10411, has_genre, 30463 10411, in_language, 6012 35625, has_genre, 30463 35625, in_language, 6012 38589, has_genre, 30463 38589, has_tags, 6012 38589, in_language, 6012 27285, has_genre, 30463 27285, in_language, 6012 38392, has_genre, 30463 38392, has_tags, 6012 38392, in_language, 6012 18699, has_genre, 30463 18699, in_language, 6012 23366, has_genre, 30463 23366, release_year, 18132 16839, has_genre, 30463 16839, in_language, 6012 14209, has_genre, 30463 14209, in_language, 6012 24238, has_genre, 30463 24238, in_language, 6012 15175, has_genre, 30463 15175, in_language, 6012 22443, has_genre, 30463 22443, in_language, 6012 19966, has_genre, 30463 19966, in_language, 6012 25390, has_genre, 30463 25390, in_language, 6012 16814, has_genre, 30463 16814, in_language, 6012 17372, has_genre, 30463 17372, in_language, 6012 10284, has_genre, 30463 10284, release_year, 18132 10560, has_genre, 30463 10560, in_language, 6012 34969, has_genre, 30463 34969, release_year, 18132 22420, has_genre, 30463 22420, in_language, 6012 3092, has_genre, 30463 3092, release_year, 18132 31657, has_genre, 30463 31657, in_language, 6012 17748, has_genre, 30463 17748, in_language, 6012 12152, has_genre, 30463 12152, has_tags, 30463 12152, in_language, 6012 32901, has_genre, 30463 32901, in_language, 6012 352, has_genre, 30463 352, in_language, 6012 11056, has_genre, 30463 11056, in_language, 6012 5958, has_genre, 30463 5958, in_language, 6012 5311, has_genre, 30463 5311, in_language, 6012 10493, has_genre, 30463 10493, in_language, 6012 33032, in_language, 6012 33032, release_year, 18132 11213, has_genre, 30463 11213, in_language, 6012 15021, has_genre, 30463 15021, release_year, 18132 9019, has_genre, 30463 9019, in_language, 6012 22488, has_genre, 30463 22488, release_year, 18132 6201, has_genre, 30463 6201, release_year, 18132 18478, has_genre, 30463 18478, has_tags, 30463 18478, in_language, 6012 4689, has_genre, 30463 4689, in_language, 6012 24060, has_genre, 30463 24060, in_language, 6012 6603, has_genre, 30463 6603, in_language, 6012 25060, has_genre, 30463 25060, in_language, 6012 39915, has_genre, 30463 39915, in_language, 6012 28126, has_genre, 30463 28126, in_language, 6012 15380, has_genre, 30463 15380, release_year, 18132 30664, has_genre, 30463 30664, in_language, 6012 17447, has_genre, 30463 17447, in_language, 6012 7175, has_genre, 30463 7175, in_language, 6012 39270, has_genre, 30463 39270, in_language, 6012 16165, has_genre, 30463 16165, in_language, 6012 345, has_genre, 30463 345, in_language, 6012 10732, has_genre, 30463 10732, has_tags, 30463 10732, has_tags, 6012 10732, in_language, 6012 8416, has_genre, 30463 8416, in_language, 6012 24351, has_genre, 30463 24351, in_language, 6012 9091, has_genre, 30463 9091, in_language, 6012 24625, has_genre, 30463 24625, has_tags, 30463 24625, in_language, 6012 39795, has_genre, 30463 39795, has_tags, 6012 39795, in_language, 6012 8234, directed_by, 39509 8234, has_genre, 30463 8234, has_tags, 39509 8234, in_language, 6012 8234, release_year, 18132 38965, has_genre, 30463 38965, in_language, 6012 32454, has_genre, 30463 32454, has_tags, 6012 32454, in_language, 6012 14643, has_genre, 30463 14643, in_language, 6012 39773, has_genre, 30463 39773, in_language, 6012 30164, has_genre, 30463 30164, has_tags, 30463 30164, has_tags, 6012 30164, in_language, 6012 33017, has_genre, 30463 33017, release_year, 18132 13316, has_genre, 30463 13316, in_language, 6012 29539, has_genre, 30463 29539, release_year, 18132 38918, has_genre, 30463 38918, in_language, 6012 12169, has_genre, 30463 12169, has_tags, 6012 12169, in_language, 6012 9093, has_genre, 30463 9093, in_language, 6012 22995, has_genre, 30463 22995, in_language, 6012 6289, has_genre, 30463 6289, has_tags, 6012 6289, in_language, 6012 4091, has_genre, 30463 4091, release_year, 18132 28217, has_genre, 30463 28217, has_tags, 30463 28217, in_language, 6012 31569, has_genre, 30463 31569, in_language, 6012 7954, has_genre, 30463 7954, release_year, 18132 33513, has_genre, 30463 33513, in_language, 6012 32297, has_genre, 30463 32297, in_language, 6012 38843, has_genre, 30463 38843, in_language, 6012 31851, has_genre, 30463 31851, has_genre, 36212 31851, written_by, 5927 37461, has_genre, 30463 37461, has_tags, 30463 37461, in_language, 6012 11383, has_genre, 30463 11383, in_language, 6012 15930, has_genre, 30463 15930, in_language, 6012 36903, has_genre, 30463 36903, in_language, 6012 26678, has_genre, 30463 26678, in_language, 6012 11663, has_genre, 30463 11663, in_language, 6012 26185, has_genre, 30463 26185, in_language, 6012 25591, has_genre, 30463 25591, has_tags, 6012 25591, in_language, 6012 4542, has_genre, 30463 4542, has_tags, 30463 4542, has_tags, 6012 4542, in_language, 6012 13003, directed_by, 39509 13003, has_genre, 30463 13003, has_tags, 39509 13003, in_language, 6012 13003, written_by, 39509 26408, has_genre, 30463 26408, in_language, 6012 6471, has_genre, 30463 6471, release_year, 18132 5128, has_genre, 30463 5128, release_year, 18132 22238, has_genre, 30463 22238, release_year, 18132 1459, has_genre, 30463 1459, in_language, 6012 17536, has_genre, 30463 17536, in_language, 6012 12860, has_genre, 30463 12860, has_tags, 30463 12860, in_language, 6012 3286, has_genre, 30463 3286, in_language, 6012 31732, has_genre, 30463 31732, in_language, 6012 37344, has_genre, 30463 37344, in_language, 6012 11659, has_genre, 30463 11659, has_tags, 6012 11659, in_language, 6012 13631, has_genre, 30463 13631, release_year, 18132 29077, has_genre, 30463 29077, has_tags, 30463 29077, in_language, 6012 35511, has_genre, 30463 35511, has_tags, 30463 35511, in_language, 6012 22241, has_genre, 30463 22241, has_tags, 30463 22241, in_language, 6012 33483, has_genre, 30463 33483, has_tags, 6012 33483, in_language, 6012 38905, has_genre, 30463 38905, has_tags, 6012 38905, in_language, 6012 3569, has_genre, 30463 3569, has_tags, 6012 3569, in_language, 6012 22756, has_genre, 30463 22756, in_language, 6012 367, has_genre, 30463 367, in_language, 6012 8184, has_genre, 30463 8184, release_year, 18132 Question: How are FREDDY FLORES, THE BAKER'S WIFE, and WELLS ROOT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FREDDY FLORES", "THE BAKER'S WIFE", "WELLS ROOT" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "in_language", "FRENCH" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "has_tags", "FRENCH" ], [ "8 WOMEN", "in_language", "FRENCH" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "release_year", "1938" ], [ "A CHRISTMAS TALE", "has_genre", "COMEDY" ], [ "A CHRISTMAS TALE", "in_language", "FRENCH" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "in_language", "FRENCH" ], [ "A MONKEY IN WINTER", "has_genre", "COMEDY" ], [ "A MONKEY IN WINTER", "in_language", "FRENCH" ], [ "A SLIGHT CASE OF MURDER", "has_genre", "COMEDY" ], [ "A SLIGHT CASE OF MURDER", "has_tags", "COMEDY" ], [ "A SLIGHT CASE OF MURDER", "release_year", "1938" ], [ "A WOMAN IS A WOMAN", "has_genre", "COMEDY" ], [ "A WOMAN IS A WOMAN", "in_language", "FRENCH" ], [ "AALTRA", "has_genre", "COMEDY" ], [ "AALTRA", "in_language", "FRENCH" ], [ "ALL TOGETHER", "has_genre", "COMEDY" ], [ "ALL TOGETHER", "in_language", "FRENCH" ], [ "AMÉLIE", "has_genre", "COMEDY" ], [ "AMÉLIE", "has_tags", "COMEDY" ], [ "AMÉLIE", "has_tags", "FRENCH" ], [ "AMÉLIE", "in_language", "FRENCH" ], [ "ANNABEL TAKES A TOUR", "has_genre", "COMEDY" ], [ "ANNABEL TAKES A TOUR", "release_year", "1938" ], [ "ATTILA MARCEL", "has_genre", "COMEDY" ], [ "ATTILA MARCEL", "in_language", "FRENCH" ], [ "BABYSITTING", "has_genre", "COMEDY" ], [ "BABYSITTING", "in_language", "FRENCH" ], [ "BERNIE", "has_genre", "COMEDY" ], [ "BERNIE", "in_language", "FRENCH" ], [ "BLOCK-HEADS", "has_genre", "COMEDY" ], [ "BLOCK-HEADS", "release_year", "1938" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "starred_actors", "FREDDY FLORES" ], [ "BOTTLE SHOCK", "has_genre", "COMEDY" ], [ "BOTTLE SHOCK", "in_language", "FRENCH" ], [ "BOY MEETS GIRL", "has_genre", "COMEDY" ], [ "BOY MEETS GIRL", "in_language", "FRENCH" ], [ "BOY MEETS GIRL", "release_year", "1938" ], [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "in_language", "FRENCH" ], [ "BRINGING UP BABY", "has_genre", "COMEDY" ], [ "BRINGING UP BABY", "has_tags", "COMEDY" ], [ "BRINGING UP BABY", "release_year", "1938" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "in_language", "FRENCH" ], [ "CARNIVAL IN FLANDERS", "has_genre", "COMEDY" ], [ "CARNIVAL IN FLANDERS", "in_language", "FRENCH" ], [ "CASE DÉPART", "has_genre", "COMEDY" ], [ "CASE DÉPART", "has_tags", "FRENCH" ], [ "CASE DÉPART", "in_language", "FRENCH" ], [ "CHOUCHOU", "has_genre", "COMEDY" ], [ "CHOUCHOU", "has_tags", "FRENCH" ], [ "CHOUCHOU", "in_language", "FRENCH" ], [ "CYRANO DE BERGERAC", "has_genre", "COMEDY" ], [ "CYRANO DE BERGERAC", "has_tags", "FRENCH" ], [ "CYRANO DE BERGERAC", "in_language", "FRENCH" ], [ "DAYS OF DARKNESS", "has_genre", "COMEDY" ], [ "DAYS OF DARKNESS", "in_language", "FRENCH" ], [ "DE L'AUTRE CÔTÉ DU LIT", "has_genre", "COMEDY" ], [ "DE L'AUTRE CÔTÉ DU LIT", "in_language", "FRENCH" ], [ "DELICACY", "has_genre", "COMEDY" ], [ "DELICACY", "in_language", "FRENCH" ], [ "DELUSIONS OF GRANDEUR", "has_genre", "COMEDY" ], [ "DELUSIONS OF GRANDEUR", "in_language", "FRENCH" ], [ "ENGLISH VINGLISH", "has_genre", "COMEDY" ], [ "ENGLISH VINGLISH", "in_language", "FRENCH" ], [ "FAREWELL, HOME SWEET HOME", "has_genre", "COMEDY" ], [ "FAREWELL, HOME SWEET HOME", "in_language", "FRENCH" ], [ "FATHER AND GUNS", "has_genre", "COMEDY" ], [ "FATHER AND GUNS", "in_language", "FRENCH" ], [ "FISTON", "has_genre", "COMEDY" ], [ "FISTON", "has_tags", "FRENCH" ], [ "FISTON", "in_language", "FRENCH" ], [ "FRENCH KISS", "has_genre", "COMEDY" ], [ "FRENCH KISS", "has_tags", "COMEDY" ], [ "FRENCH KISS", "in_language", "FRENCH" ], [ "FRENCH TWIST", "has_genre", "COMEDY" ], [ "FRENCH TWIST", "in_language", "FRENCH" ], [ "GET OUT YOUR HANDKERCHIEFS", "has_genre", "COMEDY" ], [ "GET OUT YOUR HANDKERCHIEFS", "in_language", "FRENCH" ], [ "GIGI", "has_genre", "COMEDY" ], [ "GIGI", "in_language", "FRENCH" ], [ "GOING PLACES", "has_genre", "COMEDY" ], [ "GOING PLACES", "in_language", "FRENCH" ], [ "GREEN CARD", "has_genre", "COMEDY" ], [ "GREEN CARD", "in_language", "FRENCH" ], [ "HAPPINESS IS IN THE FIELD", "has_genre", "COMEDY" ], [ "HAPPINESS IS IN THE FIELD", "in_language", "FRENCH" ], [ "HAPPINESS NEVER COMES ALONE", "has_genre", "COMEDY" ], [ "HAPPINESS NEVER COMES ALONE", "in_language", "FRENCH" ], [ "HAPPY NEW YEAR", "has_genre", "COMEDY" ], [ "HAPPY NEW YEAR", "in_language", "FRENCH" ], [ "HEARTBREAKER", "has_genre", "COMEDY" ], [ "HEARTBREAKER", "has_tags", "FRENCH" ], [ "HEARTBREAKER", "in_language", "FRENCH" ], [ "HOLIDAY", "has_genre", "COMEDY" ], [ "HOLIDAY", "has_tags", "COMEDY" ], [ "HOLIDAY", "release_year", "1938" ], [ "HOW MUCH DO YOU LOVE ME?", "has_genre", "COMEDY" ], [ "HOW MUCH DO YOU LOVE ME?", "in_language", "FRENCH" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "has_genre", "COMEDY" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "in_language", "FRENCH" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "in_language", "FRENCH" ], [ "I DO", "has_genre", "COMEDY" ], [ "I DO", "has_tags", "FRENCH" ], [ "I DO", "in_language", "FRENCH" ], [ "I WAS A MALE WAR BRIDE", "has_genre", "COMEDY" ], [ "I WAS A MALE WAR BRIDE", "in_language", "FRENCH" ], [ "I, CESAR", "has_genre", "COMEDY" ], [ "I, CESAR", "has_tags", "FRENCH" ], [ "I, CESAR", "in_language", "FRENCH" ], [ "JULIET OF THE SPIRITS", "has_genre", "COMEDY" ], [ "JULIET OF THE SPIRITS", "in_language", "FRENCH" ], [ "JUST AROUND THE CORNER", "has_genre", "COMEDY" ], [ "JUST AROUND THE CORNER", "release_year", "1938" ], [ "JUST VISITING", "has_genre", "COMEDY" ], [ "JUST VISITING", "in_language", "FRENCH" ], [ "KING OF HEARTS", "has_genre", "COMEDY" ], [ "KING OF HEARTS", "in_language", "FRENCH" ], [ "L'AGE D'OR", "has_genre", "COMEDY" ], [ "L'AGE D'OR", "in_language", "FRENCH" ], [ "LE HAVRE", "has_genre", "COMEDY" ], [ "LE HAVRE", "in_language", "FRENCH" ], [ "LE MILLION", "has_genre", "COMEDY" ], [ "LE MILLION", "in_language", "FRENCH" ], [ "LE PLAISIR", "has_genre", "COMEDY" ], [ "LE PLAISIR", "in_language", "FRENCH" ], [ "LIFE IS A LONG QUIET RIVER", "has_genre", "COMEDY" ], [ "LIFE IS A LONG QUIET RIVER", "in_language", "FRENCH" ], [ "LITTLE WHITE LIES", "has_genre", "COMEDY" ], [ "LITTLE WHITE LIES", "in_language", "FRENCH" ], [ "LOL", "has_genre", "COMEDY" ], [ "LOL", "in_language", "FRENCH" ], [ "LOVE FINDS ANDY HARDY", "has_genre", "COMEDY" ], [ "LOVE FINDS ANDY HARDY", "release_year", "1938" ], [ "MAN BITES DOG", "has_genre", "COMEDY" ], [ "MAN BITES DOG", "in_language", "FRENCH" ], [ "MAN-PROOF", "has_genre", "COMEDY" ], [ "MAN-PROOF", "release_year", "1938" ], [ "ME, MYSELF AND MUM", "has_genre", "COMEDY" ], [ "ME, MYSELF AND MUM", "in_language", "FRENCH" ], [ "MERRILY WE LIVE", "has_genre", "COMEDY" ], [ "MERRILY WE LIVE", "release_year", "1938" ], [ "MON ONCLE", "has_genre", "COMEDY" ], [ "MON ONCLE", "in_language", "FRENCH" ], [ "MY WIFE IS AN ACTRESS", "has_genre", "COMEDY" ], [ "MY WIFE IS AN ACTRESS", "in_language", "FRENCH" ], [ "NOTHING TO DECLARE", "has_genre", "COMEDY" ], [ "NOTHING TO DECLARE", "has_tags", "COMEDY" ], [ "NOTHING TO DECLARE", "in_language", "FRENCH" ], [ "ON TOUR", "has_genre", "COMEDY" ], [ "ON TOUR", "in_language", "FRENCH" ], [ "ONE HUNDRED AND ONE NIGHTS", "has_genre", "COMEDY" ], [ "ONE HUNDRED AND ONE NIGHTS", "in_language", "FRENCH" ], [ "PAULETTE", "has_genre", "COMEDY" ], [ "PAULETTE", "in_language", "FRENCH" ], [ "PERCHED ON A TREE", "has_genre", "COMEDY" ], [ "PERCHED ON A TREE", "in_language", "FRENCH" ], [ "PLAYTIME", "has_genre", "COMEDY" ], [ "PLAYTIME", "in_language", "FRENCH" ], [ "POPULAIRE", "has_genre", "COMEDY" ], [ "POPULAIRE", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "release_year", "1938" ], [ "POTICHE", "has_genre", "COMEDY" ], [ "POTICHE", "in_language", "FRENCH" ], [ "PROFESSOR BEWARE", "has_genre", "COMEDY" ], [ "PROFESSOR BEWARE", "release_year", "1938" ], [ "RATATOUILLE", "has_genre", "COMEDY" ], [ "RATATOUILLE", "in_language", "FRENCH" ], [ "REBECCA OF SUNNYBROOK FARM", "has_genre", "COMEDY" ], [ "REBECCA OF SUNNYBROOK FARM", "release_year", "1938" ], [ "ROOM SERVICE", "has_genre", "COMEDY" ], [ "ROOM SERVICE", "release_year", "1938" ], [ "RUSH HOUR 3", "has_genre", "COMEDY" ], [ "RUSH HOUR 3", "has_tags", "COMEDY" ], [ "RUSH HOUR 3", "in_language", "FRENCH" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "in_language", "FRENCH" ], [ "SEDUCING DOCTOR LEWIS", "has_genre", "COMEDY" ], [ "SEDUCING DOCTOR LEWIS", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "has_genre", "COMEDY" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "has_genre", "COMEDY" ], [ "SHALL WE KISS?", "in_language", "FRENCH" ], [ "SHEITAN", "has_genre", "COMEDY" ], [ "SHEITAN", "in_language", "FRENCH" ], [ "SIDEWALKS OF LONDON", "has_genre", "COMEDY" ], [ "SIDEWALKS OF LONDON", "release_year", "1938" ], [ "SMOKING/NO SMOKING", "has_genre", "COMEDY" ], [ "SMOKING/NO SMOKING", "in_language", "FRENCH" ], [ "SON OF RAMBOW", "has_genre", "COMEDY" ], [ "SON OF RAMBOW", "in_language", "FRENCH" ], [ "STOLEN KISSES", "has_genre", "COMEDY" ], [ "STOLEN KISSES", "in_language", "FRENCH" ], [ "SUBWAY", "has_genre", "COMEDY" ], [ "SUBWAY", "in_language", "FRENCH" ], [ "SUPERCONDRIAQUE", "has_genre", "COMEDY" ], [ "SUPERCONDRIAQUE", "in_language", "FRENCH" ], [ "TANGUY", "has_genre", "COMEDY" ], [ "TANGUY", "in_language", "FRENCH" ], [ "TAXI", "has_genre", "COMEDY" ], [ "TAXI", "has_tags", "COMEDY" ], [ "TAXI", "has_tags", "FRENCH" ], [ "TAXI", "in_language", "FRENCH" ], [ "TAXI 3", "has_genre", "COMEDY" ], [ "TAXI 3", "in_language", "FRENCH" ], [ "TAXI 4", "has_genre", "COMEDY" ], [ "TAXI 4", "in_language", "FRENCH" ], [ "THE ADVENTURES OF PICASSO", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PICASSO", "in_language", "FRENCH" ], [ "THE APARTMENT", "has_genre", "COMEDY" ], [ "THE APARTMENT", "has_tags", "COMEDY" ], [ "THE APARTMENT", "in_language", "FRENCH" ], [ "THE ARTIST", "has_genre", "COMEDY" ], [ "THE ARTIST", "has_tags", "FRENCH" ], [ "THE ARTIST", "in_language", "FRENCH" ], [ "THE BAKER'S WIFE", "directed_by", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "has_genre", "COMEDY" ], [ "THE BAKER'S WIFE", "has_tags", "MARCEL PAGNOL" ], [ "THE BAKER'S WIFE", "in_language", "FRENCH" ], [ "THE BAKER'S WIFE", "release_year", "1938" ], [ "THE BARBARIAN INVASIONS", "has_genre", "COMEDY" ], [ "THE BARBARIAN INVASIONS", "in_language", "FRENCH" ], [ "THE BIG PICTURE", "has_genre", "COMEDY" ], [ "THE BIG PICTURE", "has_tags", "FRENCH" ], [ "THE BIG PICTURE", "in_language", "FRENCH" ], [ "THE BRAIN", "has_genre", "COMEDY" ], [ "THE BRAIN", "in_language", "FRENCH" ], [ "THE CLINK OF ICE", "has_genre", "COMEDY" ], [ "THE CLINK OF ICE", "in_language", "FRENCH" ], [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE CLOSET", "has_tags", "FRENCH" ], [ "THE CLOSET", "in_language", "FRENCH" ], [ "THE COWBOY AND THE LADY", "has_genre", "COMEDY" ], [ "THE COWBOY AND THE LADY", "release_year", "1938" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "COMEDY" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "in_language", "FRENCH" ], [ "THE DIVORCE OF LADY X", "has_genre", "COMEDY" ], [ "THE DIVORCE OF LADY X", "release_year", "1938" ], [ "THE FAMILY", "has_genre", "COMEDY" ], [ "THE FAMILY", "in_language", "FRENCH" ], [ "THE FRENCH MINISTER", "has_genre", "COMEDY" ], [ "THE FRENCH MINISTER", "has_tags", "FRENCH" ], [ "THE FRENCH MINISTER", "in_language", "FRENCH" ], [ "THE GRAND MANEUVER", "has_genre", "COMEDY" ], [ "THE GRAND MANEUVER", "in_language", "FRENCH" ], [ "THE HAPPY ROAD", "has_genre", "COMEDY" ], [ "THE HAPPY ROAD", "in_language", "FRENCH" ], [ "THE INTOUCHABLES", "has_genre", "COMEDY" ], [ "THE INTOUCHABLES", "has_tags", "FRENCH" ], [ "THE INTOUCHABLES", "in_language", "FRENCH" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "COMEDY" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_tags", "COMEDY" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "in_language", "FRENCH" ], [ "THE LOVE PARADE", "has_genre", "COMEDY" ], [ "THE LOVE PARADE", "in_language", "FRENCH" ], [ "THE MAD MISS MANTON", "has_genre", "COMEDY" ], [ "THE MAD MISS MANTON", "release_year", "1938" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "COMEDY" ], [ "THE MAN WHO LOVED WOMEN", "in_language", "FRENCH" ], [ "THE MERRY WIDOW", "has_genre", "COMEDY" ], [ "THE MERRY WIDOW", "in_language", "FRENCH" ], [ "THE MURDERER LIVES AT NUMBER 21", "has_genre", "COMEDY" ], [ "THE MURDERER LIVES AT NUMBER 21", "in_language", "FRENCH" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE PRISONER OF ZENDA", "written_by", "WELLS ROOT" ], [ "THE RULES OF THE GAME", "has_genre", "COMEDY" ], [ "THE RULES OF THE GAME", "has_tags", "COMEDY" ], [ "THE RULES OF THE GAME", "in_language", "FRENCH" ], [ "THE SCIENCE OF SLEEP", "has_genre", "COMEDY" ], [ "THE SCIENCE OF SLEEP", "in_language", "FRENCH" ], [ "THE SUCKER", "has_genre", "COMEDY" ], [ "THE SUCKER", "in_language", "FRENCH" ], [ "THE SUITOR", "has_genre", "COMEDY" ], [ "THE SUITOR", "in_language", "FRENCH" ], [ "THE SWINDLE", "has_genre", "COMEDY" ], [ "THE SWINDLE", "in_language", "FRENCH" ], [ "THE TALL BLOND MAN WITH ONE BLACK SHOE", "has_genre", "COMEDY" ], [ "THE TALL BLOND MAN WITH ONE BLACK SHOE", "in_language", "FRENCH" ], [ "THE TOY", "has_genre", "COMEDY" ], [ "THE TOY", "in_language", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "has_genre", "COMEDY" ], [ "THE TRIPLETS OF BELLEVILLE", "has_tags", "FRENCH" ], [ "THE TRIPLETS OF BELLEVILLE", "in_language", "FRENCH" ], [ "THE VALET", "has_genre", "COMEDY" ], [ "THE VALET", "has_tags", "COMEDY" ], [ "THE VALET", "has_tags", "FRENCH" ], [ "THE VALET", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "directed_by", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "COMEDY" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_tags", "MARCEL PAGNOL" ], [ "THE WELL-DIGGER'S DAUGHTER", "in_language", "FRENCH" ], [ "THE WELL-DIGGER'S DAUGHTER", "written_by", "MARCEL PAGNOL" ], [ "THE WISE GUYS", "has_genre", "COMEDY" ], [ "THE WISE GUYS", "in_language", "FRENCH" ], [ "THE YOUNG IN HEART", "has_genre", "COMEDY" ], [ "THE YOUNG IN HEART", "release_year", "1938" ], [ "THERE GOES MY HEART", "has_genre", "COMEDY" ], [ "THERE GOES MY HEART", "release_year", "1938" ], [ "THERE'S ALWAYS A WOMAN", "has_genre", "COMEDY" ], [ "THERE'S ALWAYS A WOMAN", "release_year", "1938" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "COMEDY" ], [ "TOO BEAUTIFUL FOR YOU", "in_language", "FRENCH" ], [ "TRAFIC", "has_genre", "COMEDY" ], [ "TRAFIC", "in_language", "FRENCH" ], [ "TRUE LIES", "has_genre", "COMEDY" ], [ "TRUE LIES", "has_tags", "COMEDY" ], [ "TRUE LIES", "in_language", "FRENCH" ], [ "UNDER THE ROOFS OF PARIS", "has_genre", "COMEDY" ], [ "UNDER THE ROOFS OF PARIS", "in_language", "FRENCH" ], [ "URANUS", "has_genre", "COMEDY" ], [ "URANUS", "in_language", "FRENCH" ], [ "VERY HAPPY ALEXANDER", "has_genre", "COMEDY" ], [ "VERY HAPPY ALEXANDER", "in_language", "FRENCH" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "VIVA MARIA!", "has_tags", "FRENCH" ], [ "VIVA MARIA!", "in_language", "FRENCH" ], [ "VIVACIOUS LADY", "has_genre", "COMEDY" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "WASABI", "has_genre", "COMEDY" ], [ "WASABI", "has_tags", "COMEDY" ], [ "WASABI", "in_language", "FRENCH" ], [ "WE HAVE A POPE", "has_genre", "COMEDY" ], [ "WE HAVE A POPE", "has_tags", "COMEDY" ], [ "WE HAVE A POPE", "in_language", "FRENCH" ], [ "WE'RE NO ANGELS", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "COMEDY" ], [ "WE'RE NO ANGELS", "in_language", "FRENCH" ], [ "WEEKEND", "has_genre", "COMEDY" ], [ "WEEKEND", "has_tags", "FRENCH" ], [ "WEEKEND", "in_language", "FRENCH" ], [ "WHAT'S IN A NAME?", "has_genre", "COMEDY" ], [ "WHAT'S IN A NAME?", "has_tags", "FRENCH" ], [ "WHAT'S IN A NAME?", "in_language", "FRENCH" ], [ "WHY NOT ME?", "has_genre", "COMEDY" ], [ "WHY NOT ME?", "has_tags", "FRENCH" ], [ "WHY NOT ME?", "in_language", "FRENCH" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "in_language", "FRENCH" ], [ "WITH LOVE... FROM THE AGE OF REASON", "has_genre", "COMEDY" ], [ "WITH LOVE... FROM THE AGE OF REASON", "in_language", "FRENCH" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 319, A BUG'S LIFE 33657, A NIGHT AT THE ROXBURY 35485, ALMOST HEROES 35941, ANTZ 8321, BASEKETBALL 36971, BEDROOMS AND HALLWAYS 29908, BILLY'S HOLLYWOOD SCREEN KISS 212, BLACK CAT, WHITE CAT 7318, BLOOD, GUTS, BULLETS AND OCTANE 16023, BLUES BROTHERS 2000 31902, BRIDE OF CHUCKY 32530, BUFFALO '66 5776, BULWORTH 16129, CAN'T HARDLY WAIT 26848, CELEBRITY 36568, CLAY PIGEONS 30463, COMEDY 36016, COUSIN BETTE 8872, DANCER, TEXAS POP. 81 25018, DEAD HUSBANDS 36117, DEAD MAN ON CAMPUS 39905, DECAMPITATED 29689, DIRTY WORK 3911, DIVORCING JACK 35714, DOG PARK 1200, DUPLICATE 3426, EDGE OF SEVENTEEN 24644, ERNEST IN THE ARMY 30820, FEAR AND LOATHING IN LAS VEGAS 3955, FINDING NORTH 30704, FREE MONEY 2547, GLASBLÅSARNS BARN 4278, HALF BAKED 17933, HAPPINESS 35633, HOLY MAN 7980, HOMEGROWN 24023, HOUSEBOUND 22348, I GOT THE HOOK UP 33211, I'LL BE HOME FOR CHRISTMAS 19868, JACK FROST 25363, JERRY AND TOM 14711, KISSING A FOOL 28004, KUCH KUCH HOTA HAI 37426, LIVING OUT LOUD 38721, LOCK, STOCK AND TWO SMOKING BARRELS 14997, MACKENZIE CROOK 37141, MEET THE DEEDLES 38276, MIDNIGHT 112, MUSIC FROM ANOTHER ROOM 16841, MY GIANT 22946, NEXT STOP WONDERLAND 10734, ORPHANS 4235, OUT OF SIGHT 1300, OVERNIGHT DELIVERY 3297, PATCH ADAMS 10640, PECKER 14282, PLEASANTVILLE 30118, POLISH WEDDING 16172, PRACTICAL MAGIC 22150, RIDE 24415, RINGMASTER 32607, RUSH HOUR 12153, RUSHMORE 8020, SAFE MEN 34686, SAMURAI FICTION 20220, SENSELESS 39218, SEX LIVES OF THE POTATO MEN 3657, SHAKESPEARE IN LOVE 217, SIMON BIRCH 23608, SIX DAYS SEVEN NIGHTS 32807, SIX-STRING SAMURAI 31596, SLAPPY AND THE STINKERS 34249, SLC PUNK! 28065, SLIDING DOORS 31526, SLUMS OF BEVERLY HILLS 36556, SMALL SOLDIERS 32731, SOME GIRL 6831, SOMEWHERE IN THE CITY 10819, SOUR GRAPES 33439, STEPMOM 10732, TAXI 4519, THE ADVENTURES OF SEBASTIAN COLE 36412, THE BIG HIT 14696, THE BIG LEBOWSKI 27549, THE BOOK OF LIFE 4068, THE GENERAL 40028, THE GODSON 17872, THE IDIOTS 32440, THE IMPOSTORS 4223, THE INTERVIEW 9059, THE LAST DAYS OF DISCO 844, THE LOVE LETTER 34003, THE MISADVENTURES OF MARGARET 22210, THE NAKED MAN 15569, THE OBJECT OF MY AFFECTION 24357, THE PARENT TRAP 27932, THE PENTAGON WARS 16573, THE PLAYERS CLUB 17460, THE RUGRATS MOVIE 36038, THE WATERBOY 11628, THE WEDDING SINGER 13738, THERE'S SOMETHING ABOUT MARY 8012, TOMORROW NIGHT 15511, TORRENTE, EL BRAZO TONTO DE LA LEY 7379, VERY BAD THINGS 4736, WHERE'S MARLOWE? 19679, WIDE AWAKE 25949, WOO 9552, WRONGFULLY ACCUSED 15808, YOU'VE GOT MAIL src, edge_attr, dst 319, has_genre, 30463 319, has_tags, 30463 319, release_year, 2133 33657, has_genre, 30463 33657, release_year, 2133 35485, has_genre, 30463 35485, release_year, 2133 35941, has_genre, 30463 35941, release_year, 2133 8321, has_genre, 30463 8321, has_tags, 30463 8321, release_year, 2133 36971, has_genre, 30463 36971, release_year, 2133 29908, has_genre, 30463 29908, release_year, 2133 212, has_genre, 30463 212, release_year, 2133 7318, has_genre, 30463 7318, release_year, 2133 16023, has_genre, 30463 16023, release_year, 2133 31902, has_genre, 30463 31902, release_year, 2133 32530, has_genre, 30463 32530, release_year, 2133 5776, has_genre, 30463 5776, has_tags, 30463 5776, release_year, 2133 16129, has_genre, 30463 16129, release_year, 2133 26848, has_genre, 30463 26848, release_year, 2133 36568, has_genre, 30463 36568, release_year, 2133 36016, has_genre, 30463 36016, release_year, 2133 8872, has_genre, 30463 8872, release_year, 2133 25018, has_genre, 30463 25018, release_year, 2133 36117, has_genre, 30463 36117, release_year, 2133 39905, has_genre, 30463 39905, release_year, 2133 29689, has_genre, 30463 29689, has_tags, 30463 29689, release_year, 2133 3911, has_genre, 30463 3911, has_tags, 30463 3911, release_year, 2133 35714, has_genre, 30463 35714, release_year, 2133 1200, has_genre, 30463 1200, release_year, 2133 3426, has_genre, 30463 3426, release_year, 2133 24644, has_genre, 30463 24644, release_year, 2133 30820, has_genre, 30463 30820, has_tags, 30463 30820, release_year, 2133 3955, has_genre, 30463 3955, release_year, 2133 30704, has_genre, 30463 30704, release_year, 2133 2547, release_year, 2133 4278, has_genre, 30463 4278, has_tags, 30463 4278, release_year, 2133 17933, has_genre, 30463 17933, release_year, 2133 35633, has_genre, 30463 35633, release_year, 2133 7980, has_genre, 30463 7980, release_year, 2133 24023, has_genre, 30463 22348, has_genre, 30463 22348, release_year, 2133 33211, has_genre, 30463 33211, release_year, 2133 19868, has_genre, 30463 19868, release_year, 2133 25363, has_genre, 30463 25363, release_year, 2133 14711, has_genre, 30463 14711, release_year, 2133 28004, has_genre, 30463 28004, release_year, 2133 37426, has_genre, 30463 37426, release_year, 2133 38721, has_genre, 30463 38721, has_tags, 30463 38721, release_year, 2133 37141, has_genre, 30463 37141, release_year, 2133 38276, has_genre, 30463 38276, release_year, 2133 112, has_genre, 30463 112, release_year, 2133 16841, has_genre, 30463 16841, release_year, 2133 22946, has_genre, 30463 22946, release_year, 2133 10734, has_genre, 30463 10734, release_year, 2133 4235, has_genre, 30463 4235, release_year, 2133 1300, has_genre, 30463 1300, release_year, 2133 3297, has_genre, 30463 3297, release_year, 2133 10640, has_genre, 30463 10640, release_year, 2133 14282, has_genre, 30463 14282, release_year, 2133 30118, has_genre, 30463 30118, release_year, 2133 16172, has_genre, 30463 16172, release_year, 2133 22150, has_genre, 30463 22150, release_year, 2133 24415, has_genre, 30463 24415, release_year, 2133 32607, has_genre, 30463 32607, has_tags, 30463 32607, release_year, 2133 12153, has_genre, 30463 12153, has_tags, 30463 12153, release_year, 2133 8020, has_genre, 30463 8020, release_year, 2133 34686, has_genre, 30463 34686, release_year, 2133 20220, has_genre, 30463 20220, release_year, 2133 39218, has_genre, 30463 39218, starred_actors, 14997 3657, has_genre, 30463 3657, release_year, 2133 217, has_genre, 30463 217, release_year, 2133 23608, has_genre, 30463 23608, has_tags, 30463 23608, release_year, 2133 32807, has_genre, 30463 32807, release_year, 2133 31596, has_genre, 30463 31596, release_year, 2133 34249, has_genre, 30463 34249, release_year, 2133 28065, has_genre, 30463 28065, release_year, 2133 31526, has_genre, 30463 31526, release_year, 2133 36556, has_genre, 30463 36556, release_year, 2133 32731, has_genre, 30463 32731, release_year, 2133 6831, has_genre, 30463 6831, release_year, 2133 10819, has_genre, 30463 10819, release_year, 2133 33439, has_genre, 30463 33439, release_year, 2133 10732, has_genre, 30463 10732, has_tags, 30463 10732, release_year, 2133 4519, has_genre, 30463 4519, release_year, 2133 36412, has_genre, 30463 36412, has_tags, 30463 36412, release_year, 2133 14696, has_genre, 30463 14696, has_tags, 30463 14696, release_year, 2133 27549, has_genre, 30463 27549, release_year, 2133 4068, has_genre, 30463 4068, has_tags, 30463 4068, release_year, 2133 40028, has_genre, 30463 40028, release_year, 2133 17872, has_genre, 30463 17872, release_year, 2133 32440, has_genre, 30463 32440, release_year, 2133 4223, has_genre, 30463 4223, has_tags, 30463 4223, release_year, 2133 9059, has_genre, 30463 9059, release_year, 2133 844, has_genre, 30463 844, release_year, 2133 34003, has_genre, 30463 34003, release_year, 2133 22210, has_genre, 30463 22210, release_year, 2133 15569, has_genre, 30463 15569, release_year, 2133 24357, has_genre, 30463 24357, release_year, 2133 27932, has_genre, 30463 27932, release_year, 2133 16573, has_genre, 30463 16573, release_year, 2133 17460, has_genre, 30463 17460, release_year, 2133 36038, has_genre, 30463 36038, has_tags, 30463 36038, release_year, 2133 11628, has_genre, 30463 11628, has_tags, 30463 11628, release_year, 2133 13738, has_genre, 30463 13738, has_tags, 30463 13738, release_year, 2133 8012, has_genre, 30463 8012, has_tags, 30463 8012, release_year, 2133 15511, has_genre, 30463 15511, release_year, 2133 7379, has_genre, 30463 7379, release_year, 2133 4736, has_genre, 30463 4736, release_year, 2133 19679, has_genre, 30463 19679, release_year, 2133 25949, has_genre, 30463 25949, release_year, 2133 9552, has_genre, 30463 9552, release_year, 2133 15808, has_genre, 30463 15808, has_tags, 30463 15808, release_year, 2133 Question: In what context are GLASBLÅSARNS BARN, HOUSEBOUND, and MACKENZIE CROOK connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GLASBLÅSARNS BARN", "HOUSEBOUND", "MACKENZIE CROOK" ], "valid_edges": [ [ "A BUG'S LIFE", "has_genre", "COMEDY" ], [ "A BUG'S LIFE", "has_tags", "COMEDY" ], [ "A BUG'S LIFE", "release_year", "1998" ], [ "A NIGHT AT THE ROXBURY", "has_genre", "COMEDY" ], [ "A NIGHT AT THE ROXBURY", "release_year", "1998" ], [ "ALMOST HEROES", "has_genre", "COMEDY" ], [ "ALMOST HEROES", "release_year", "1998" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "release_year", "1998" ], [ "BASEKETBALL", "has_genre", "COMEDY" ], [ "BASEKETBALL", "has_tags", "COMEDY" ], [ "BASEKETBALL", "release_year", "1998" ], [ "BEDROOMS AND HALLWAYS", "has_genre", "COMEDY" ], [ "BEDROOMS AND HALLWAYS", "release_year", "1998" ], [ "BILLY'S HOLLYWOOD SCREEN KISS", "has_genre", "COMEDY" ], [ "BILLY'S HOLLYWOOD SCREEN KISS", "release_year", "1998" ], [ "BLACK CAT, WHITE CAT", "has_genre", "COMEDY" ], [ "BLACK CAT, WHITE CAT", "release_year", "1998" ], [ "BLOOD, GUTS, BULLETS AND OCTANE", "has_genre", "COMEDY" ], [ "BLOOD, GUTS, BULLETS AND OCTANE", "release_year", "1998" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "release_year", "1998" ], [ "BRIDE OF CHUCKY", "has_genre", "COMEDY" ], [ "BRIDE OF CHUCKY", "release_year", "1998" ], [ "BUFFALO '66", "has_genre", "COMEDY" ], [ "BUFFALO '66", "release_year", "1998" ], [ "BULWORTH", "has_genre", "COMEDY" ], [ "BULWORTH", "has_tags", "COMEDY" ], [ "BULWORTH", "release_year", "1998" ], [ "CAN'T HARDLY WAIT", "has_genre", "COMEDY" ], [ "CAN'T HARDLY WAIT", "release_year", "1998" ], [ "CELEBRITY", "has_genre", "COMEDY" ], [ "CELEBRITY", "release_year", "1998" ], [ "CLAY PIGEONS", "has_genre", "COMEDY" ], [ "CLAY PIGEONS", "release_year", "1998" ], [ "COUSIN BETTE", "has_genre", "COMEDY" ], [ "COUSIN BETTE", "release_year", "1998" ], [ "DANCER, TEXAS POP. 81", "has_genre", "COMEDY" ], [ "DANCER, TEXAS POP. 81", "release_year", "1998" ], [ "DEAD HUSBANDS", "has_genre", "COMEDY" ], [ "DEAD HUSBANDS", "release_year", "1998" ], [ "DEAD MAN ON CAMPUS", "has_genre", "COMEDY" ], [ "DEAD MAN ON CAMPUS", "release_year", "1998" ], [ "DECAMPITATED", "has_genre", "COMEDY" ], [ "DECAMPITATED", "release_year", "1998" ], [ "DIRTY WORK", "has_genre", "COMEDY" ], [ "DIRTY WORK", "has_tags", "COMEDY" ], [ "DIRTY WORK", "release_year", "1998" ], [ "DIVORCING JACK", "has_genre", "COMEDY" ], [ "DIVORCING JACK", "has_tags", "COMEDY" ], [ "DIVORCING JACK", "release_year", "1998" ], [ "DOG PARK", "has_genre", "COMEDY" ], [ "DOG PARK", "release_year", "1998" ], [ "DUPLICATE", "has_genre", "COMEDY" ], [ "DUPLICATE", "release_year", "1998" ], [ "EDGE OF SEVENTEEN", "has_genre", "COMEDY" ], [ "EDGE OF SEVENTEEN", "release_year", "1998" ], [ "ERNEST IN THE ARMY", "has_genre", "COMEDY" ], [ "ERNEST IN THE ARMY", "release_year", "1998" ], [ "FEAR AND LOATHING IN LAS VEGAS", "has_genre", "COMEDY" ], [ "FEAR AND LOATHING IN LAS VEGAS", "has_tags", "COMEDY" ], [ "FEAR AND LOATHING IN LAS VEGAS", "release_year", "1998" ], [ "FINDING NORTH", "has_genre", "COMEDY" ], [ "FINDING NORTH", "release_year", "1998" ], [ "FREE MONEY", "has_genre", "COMEDY" ], [ "FREE MONEY", "release_year", "1998" ], [ "GLASBLÅSARNS BARN", "release_year", "1998" ], [ "HALF BAKED", "has_genre", "COMEDY" ], [ "HALF BAKED", "has_tags", "COMEDY" ], [ "HALF BAKED", "release_year", "1998" ], [ "HAPPINESS", "has_genre", "COMEDY" ], [ "HAPPINESS", "release_year", "1998" ], [ "HOLY MAN", "has_genre", "COMEDY" ], [ "HOLY MAN", "release_year", "1998" ], [ "HOMEGROWN", "has_genre", "COMEDY" ], [ "HOMEGROWN", "release_year", "1998" ], [ "HOUSEBOUND", "has_genre", "COMEDY" ], [ "I GOT THE HOOK UP", "has_genre", "COMEDY" ], [ "I GOT THE HOOK UP", "release_year", "1998" ], [ "I'LL BE HOME FOR CHRISTMAS", "has_genre", "COMEDY" ], [ "I'LL BE HOME FOR CHRISTMAS", "release_year", "1998" ], [ "JACK FROST", "has_genre", "COMEDY" ], [ "JACK FROST", "release_year", "1998" ], [ "JERRY AND TOM", "has_genre", "COMEDY" ], [ "JERRY AND TOM", "release_year", "1998" ], [ "KISSING A FOOL", "has_genre", "COMEDY" ], [ "KISSING A FOOL", "release_year", "1998" ], [ "KUCH KUCH HOTA HAI", "has_genre", "COMEDY" ], [ "KUCH KUCH HOTA HAI", "release_year", "1998" ], [ "LIVING OUT LOUD", "has_genre", "COMEDY" ], [ "LIVING OUT LOUD", "release_year", "1998" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_genre", "COMEDY" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_tags", "COMEDY" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "release_year", "1998" ], [ "MEET THE DEEDLES", "has_genre", "COMEDY" ], [ "MEET THE DEEDLES", "release_year", "1998" ], [ "MIDNIGHT", "has_genre", "COMEDY" ], [ "MIDNIGHT", "release_year", "1998" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "COMEDY" ], [ "MUSIC FROM ANOTHER ROOM", "release_year", "1998" ], [ "MY GIANT", "has_genre", "COMEDY" ], [ "MY GIANT", "release_year", "1998" ], [ "NEXT STOP WONDERLAND", "has_genre", "COMEDY" ], [ "NEXT STOP WONDERLAND", "release_year", "1998" ], [ "ORPHANS", "has_genre", "COMEDY" ], [ "ORPHANS", "release_year", "1998" ], [ "OUT OF SIGHT", "has_genre", "COMEDY" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "OVERNIGHT DELIVERY", "has_genre", "COMEDY" ], [ "OVERNIGHT DELIVERY", "release_year", "1998" ], [ "PATCH ADAMS", "has_genre", "COMEDY" ], [ "PATCH ADAMS", "release_year", "1998" ], [ "PECKER", "has_genre", "COMEDY" ], [ "PECKER", "release_year", "1998" ], [ "PLEASANTVILLE", "has_genre", "COMEDY" ], [ "PLEASANTVILLE", "release_year", "1998" ], [ "POLISH WEDDING", "has_genre", "COMEDY" ], [ "POLISH WEDDING", "release_year", "1998" ], [ "PRACTICAL MAGIC", "has_genre", "COMEDY" ], [ "PRACTICAL MAGIC", "release_year", "1998" ], [ "RIDE", "has_genre", "COMEDY" ], [ "RIDE", "release_year", "1998" ], [ "RINGMASTER", "has_genre", "COMEDY" ], [ "RINGMASTER", "release_year", "1998" ], [ "RUSH HOUR", "has_genre", "COMEDY" ], [ "RUSH HOUR", "has_tags", "COMEDY" ], [ "RUSH HOUR", "release_year", "1998" ], [ "RUSHMORE", "has_genre", "COMEDY" ], [ "RUSHMORE", "has_tags", "COMEDY" ], [ "RUSHMORE", "release_year", "1998" ], [ "SAFE MEN", "has_genre", "COMEDY" ], [ "SAFE MEN", "release_year", "1998" ], [ "SAMURAI FICTION", "has_genre", "COMEDY" ], [ "SAMURAI FICTION", "release_year", "1998" ], [ "SENSELESS", "has_genre", "COMEDY" ], [ "SENSELESS", "release_year", "1998" ], [ "SEX LIVES OF THE POTATO MEN", "has_genre", "COMEDY" ], [ "SEX LIVES OF THE POTATO MEN", "starred_actors", "MACKENZIE CROOK" ], [ "SHAKESPEARE IN LOVE", "has_genre", "COMEDY" ], [ "SHAKESPEARE IN LOVE", "release_year", "1998" ], [ "SIMON BIRCH", "has_genre", "COMEDY" ], [ "SIMON BIRCH", "release_year", "1998" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "release_year", "1998" ], [ "SIX-STRING SAMURAI", "has_genre", "COMEDY" ], [ "SIX-STRING SAMURAI", "release_year", "1998" ], [ "SLAPPY AND THE STINKERS", "has_genre", "COMEDY" ], [ "SLAPPY AND THE STINKERS", "release_year", "1998" ], [ "SLC PUNK!", "has_genre", "COMEDY" ], [ "SLC PUNK!", "release_year", "1998" ], [ "SLIDING DOORS", "has_genre", "COMEDY" ], [ "SLIDING DOORS", "release_year", "1998" ], [ "SLUMS OF BEVERLY HILLS", "has_genre", "COMEDY" ], [ "SLUMS OF BEVERLY HILLS", "release_year", "1998" ], [ "SMALL SOLDIERS", "has_genre", "COMEDY" ], [ "SMALL SOLDIERS", "release_year", "1998" ], [ "SOME GIRL", "has_genre", "COMEDY" ], [ "SOME GIRL", "release_year", "1998" ], [ "SOMEWHERE IN THE CITY", "has_genre", "COMEDY" ], [ "SOMEWHERE IN THE CITY", "release_year", "1998" ], [ "SOUR GRAPES", "has_genre", "COMEDY" ], [ "SOUR GRAPES", "release_year", "1998" ], [ "STEPMOM", "has_genre", "COMEDY" ], [ "STEPMOM", "release_year", "1998" ], [ "TAXI", "has_genre", "COMEDY" ], [ "TAXI", "has_tags", "COMEDY" ], [ "TAXI", "release_year", "1998" ], [ "THE ADVENTURES OF SEBASTIAN COLE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF SEBASTIAN COLE", "release_year", "1998" ], [ "THE BIG HIT", "has_genre", "COMEDY" ], [ "THE BIG HIT", "has_tags", "COMEDY" ], [ "THE BIG HIT", "release_year", "1998" ], [ "THE BIG LEBOWSKI", "has_genre", "COMEDY" ], [ "THE BIG LEBOWSKI", "has_tags", "COMEDY" ], [ "THE BIG LEBOWSKI", "release_year", "1998" ], [ "THE BOOK OF LIFE", "has_genre", "COMEDY" ], [ "THE BOOK OF LIFE", "release_year", "1998" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE GENERAL", "release_year", "1998" ], [ "THE GODSON", "has_genre", "COMEDY" ], [ "THE GODSON", "release_year", "1998" ], [ "THE IDIOTS", "has_genre", "COMEDY" ], [ "THE IDIOTS", "release_year", "1998" ], [ "THE IMPOSTORS", "has_genre", "COMEDY" ], [ "THE IMPOSTORS", "release_year", "1998" ], [ "THE INTERVIEW", "has_genre", "COMEDY" ], [ "THE INTERVIEW", "has_tags", "COMEDY" ], [ "THE INTERVIEW", "release_year", "1998" ], [ "THE LAST DAYS OF DISCO", "has_genre", "COMEDY" ], [ "THE LAST DAYS OF DISCO", "release_year", "1998" ], [ "THE LOVE LETTER", "has_genre", "COMEDY" ], [ "THE LOVE LETTER", "release_year", "1998" ], [ "THE MISADVENTURES OF MARGARET", "has_genre", "COMEDY" ], [ "THE MISADVENTURES OF MARGARET", "release_year", "1998" ], [ "THE NAKED MAN", "has_genre", "COMEDY" ], [ "THE NAKED MAN", "release_year", "1998" ], [ "THE OBJECT OF MY AFFECTION", "has_genre", "COMEDY" ], [ "THE OBJECT OF MY AFFECTION", "release_year", "1998" ], [ "THE PARENT TRAP", "has_genre", "COMEDY" ], [ "THE PARENT TRAP", "release_year", "1998" ], [ "THE PENTAGON WARS", "has_genre", "COMEDY" ], [ "THE PENTAGON WARS", "release_year", "1998" ], [ "THE PLAYERS CLUB", "has_genre", "COMEDY" ], [ "THE PLAYERS CLUB", "release_year", "1998" ], [ "THE RUGRATS MOVIE", "has_genre", "COMEDY" ], [ "THE RUGRATS MOVIE", "release_year", "1998" ], [ "THE WATERBOY", "has_genre", "COMEDY" ], [ "THE WATERBOY", "has_tags", "COMEDY" ], [ "THE WATERBOY", "release_year", "1998" ], [ "THE WEDDING SINGER", "has_genre", "COMEDY" ], [ "THE WEDDING SINGER", "has_tags", "COMEDY" ], [ "THE WEDDING SINGER", "release_year", "1998" ], [ "THERE'S SOMETHING ABOUT MARY", "has_genre", "COMEDY" ], [ "THERE'S SOMETHING ABOUT MARY", "has_tags", "COMEDY" ], [ "THERE'S SOMETHING ABOUT MARY", "release_year", "1998" ], [ "TOMORROW NIGHT", "has_genre", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "COMEDY" ], [ "TOMORROW NIGHT", "release_year", "1998" ], [ "TORRENTE, EL BRAZO TONTO DE LA LEY", "has_genre", "COMEDY" ], [ "TORRENTE, EL BRAZO TONTO DE LA LEY", "release_year", "1998" ], [ "VERY BAD THINGS", "has_genre", "COMEDY" ], [ "VERY BAD THINGS", "release_year", "1998" ], [ "WHERE'S MARLOWE?", "has_genre", "COMEDY" ], [ "WHERE'S MARLOWE?", "release_year", "1998" ], [ "WIDE AWAKE", "has_genre", "COMEDY" ], [ "WIDE AWAKE", "release_year", "1998" ], [ "WOO", "has_genre", "COMEDY" ], [ "WOO", "release_year", "1998" ], [ "WRONGFULLY ACCUSED", "has_genre", "COMEDY" ], [ "WRONGFULLY ACCUSED", "release_year", "1998" ], [ "YOU'VE GOT MAIL", "has_genre", "COMEDY" ], [ "YOU'VE GOT MAIL", "has_tags", "COMEDY" ], [ "YOU'VE GOT MAIL", "release_year", "1998" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 9655, EXECUTION 5870, HORROR 37036, JACK BENNY 18923, ROBERT HILTZIK 18299, SLEEPAWAY CAMP 37380, THE HORROR SHOW 3640, TO BE OR NOT TO BE src, edge_attr, dst 18299, directed_by, 18923 18299, has_genre, 5870 18299, has_tags, 5870 18299, release_year, 16055 18299, written_by, 18923 37380, has_genre, 5870 37380, has_tags, 9655 3640, release_year, 16055 3640, starred_actors, 37036 Question: How are EXECUTION, JACK BENNY, and ROBERT HILTZIK related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EXECUTION", "JACK BENNY", "ROBERT HILTZIK" ], "valid_edges": [ [ "SLEEPAWAY CAMP", "directed_by", "ROBERT HILTZIK" ], [ "SLEEPAWAY CAMP", "has_genre", "HORROR" ], [ "SLEEPAWAY CAMP", "has_tags", "HORROR" ], [ "SLEEPAWAY CAMP", "release_year", "1983" ], [ "SLEEPAWAY CAMP", "written_by", "ROBERT HILTZIK" ], [ "THE HORROR SHOW", "has_genre", "HORROR" ], [ "THE HORROR SHOW", "has_tags", "EXECUTION" ], [ "TO BE OR NOT TO BE", "release_year", "1983" ], [ "TO BE OR NOT TO BE", "starred_actors", "JACK BENNY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4763, ADVENTURE 14409, ANTHONY ANDERSON 9449, ARTHUR MAYSE 30463, COMEDY 35313, DESPERATE SEARCH 36212, DRAMA 37372, JUNO 2368, KANGAROO JACK 12571, TEEN 38200, TEENAGER 17931, THE BREAKFAST CLUB src, edge_attr, dst 35313, has_genre, 4763 35313, has_genre, 36212 35313, written_by, 9449 37372, has_genre, 30463 37372, has_genre, 36212 37372, has_tags, 30463 37372, has_tags, 12571 37372, has_tags, 38200 2368, has_genre, 4763 2368, has_genre, 30463 2368, has_tags, 30463 2368, starred_actors, 14409 17931, has_genre, 30463 17931, has_genre, 36212 17931, has_tags, 30463 17931, has_tags, 36212 17931, has_tags, 12571 17931, has_tags, 38200 Question: In what context are ANTHONY ANDERSON, ARTHUR MAYSE, and TEENAGER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANTHONY ANDERSON", "ARTHUR MAYSE", "TEENAGER" ], "valid_edges": [ [ "DESPERATE SEARCH", "has_genre", "ADVENTURE" ], [ "DESPERATE SEARCH", "has_genre", "DRAMA" ], [ "DESPERATE SEARCH", "written_by", "ARTHUR MAYSE" ], [ "JUNO", "has_genre", "COMEDY" ], [ "JUNO", "has_genre", "DRAMA" ], [ "JUNO", "has_tags", "COMEDY" ], [ "JUNO", "has_tags", "TEEN" ], [ "JUNO", "has_tags", "TEENAGER" ], [ "KANGAROO JACK", "has_genre", "ADVENTURE" ], [ "KANGAROO JACK", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_tags", "COMEDY" ], [ "KANGAROO JACK", "starred_actors", "ANTHONY ANDERSON" ], [ "THE BREAKFAST CLUB", "has_genre", "COMEDY" ], [ "THE BREAKFAST CLUB", "has_genre", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "COMEDY" ], [ "THE BREAKFAST CLUB", "has_tags", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "TEEN" ], [ "THE BREAKFAST CLUB", "has_tags", "TEENAGER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35798, 2010 14771, A CAT IN PARIS 32158, A SCREAMING MAN 39824, BABIES 10045, BD-R 7051, BLACK VENUS 5840, CERTIFIED COPY 33512, DUE DATE 8176, FAREWELL 6012, FRENCH 11783, HEARTBREAKER 5387, HEREAFTER 10124, JOHN KORTY 16814, LITTLE WHITE LIES 9792, LOVE CRIME 19594, MAMMUTH 33422, MAN AT BATH 18073, MOZART'S SISTER 5452, MY AFTERNOONS WITH MARGUERITTE 12152, NOTHING TO DECLARE 27983, OF GODS AND MEN 32901, ON TOUR 745, OUR DAY WILL COME 35556, OUTSIDE THE LAW 21835, POINT BLANK 11213, POTICHE 3729, ROMANTICS ANONYMOUS 32454, THE BIG PICTURE 39773, THE CLINK OF ICE 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 25529, THE ILLUSIONIST 33265, THE NAMES OF LOVE 27456, THE PRINCESS OF MONTPENSIER 23150, THE WOMEN ON THE 6TH FLOOR 24440, TOUT CE QUI BRILLE 39715, TWICE UPON A TIME 16992, TWO IN THE WAVE 367, WITH LOVE... FROM THE AGE OF REASON src, edge_attr, dst 35798, has_tags, 10045 14771, in_language, 6012 14771, release_year, 35798 32158, in_language, 6012 32158, release_year, 35798 39824, has_tags, 6012 39824, release_year, 35798 7051, in_language, 6012 7051, release_year, 35798 5840, in_language, 6012 5840, release_year, 35798 33512, release_year, 35798 8176, in_language, 6012 11783, has_tags, 6012 11783, in_language, 6012 11783, release_year, 35798 5387, has_tags, 6012 5387, in_language, 6012 5387, release_year, 35798 16814, in_language, 6012 16814, release_year, 35798 9792, in_language, 6012 9792, release_year, 35798 19594, in_language, 6012 19594, release_year, 35798 33422, has_tags, 6012 33422, in_language, 6012 33422, release_year, 35798 18073, in_language, 6012 18073, release_year, 35798 5452, in_language, 6012 5452, release_year, 35798 12152, in_language, 6012 12152, release_year, 35798 27983, in_language, 6012 27983, release_year, 35798 32901, in_language, 6012 32901, release_year, 35798 745, in_language, 6012 745, release_year, 35798 35556, has_tags, 6012 35556, in_language, 6012 35556, release_year, 35798 21835, in_language, 6012 21835, release_year, 35798 11213, in_language, 6012 11213, release_year, 35798 3729, has_tags, 6012 3729, in_language, 6012 3729, release_year, 35798 32454, has_tags, 6012 32454, in_language, 6012 32454, release_year, 35798 39773, in_language, 6012 39773, release_year, 35798 10344, has_tags, 6012 10344, in_language, 6012 10344, release_year, 35798 25529, in_language, 6012 25529, release_year, 35798 33265, has_tags, 6012 33265, in_language, 6012 33265, release_year, 35798 27456, in_language, 6012 27456, release_year, 35798 23150, in_language, 6012 23150, release_year, 35798 24440, in_language, 6012 24440, release_year, 35798 39715, directed_by, 10124 39715, has_tags, 10045 39715, has_tags, 10124 39715, written_by, 10124 16992, in_language, 6012 16992, release_year, 35798 367, in_language, 6012 367, release_year, 35798 Question: In what context are DUE DATE, FAREWELL, and JOHN KORTY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DUE DATE", "FAREWELL", "JOHN KORTY" ], "valid_edges": [ [ "2010", "has_tags", "BD-R" ], [ "A CAT IN PARIS", "in_language", "FRENCH" ], [ "A CAT IN PARIS", "release_year", "2010" ], [ "A SCREAMING MAN", "in_language", "FRENCH" ], [ "A SCREAMING MAN", "release_year", "2010" ], [ "BABIES", "has_tags", "FRENCH" ], [ "BABIES", "release_year", "2010" ], [ "BLACK VENUS", "in_language", "FRENCH" ], [ "BLACK VENUS", "release_year", "2010" ], [ "CERTIFIED COPY", "in_language", "FRENCH" ], [ "CERTIFIED COPY", "release_year", "2010" ], [ "DUE DATE", "release_year", "2010" ], [ "FAREWELL", "in_language", "FRENCH" ], [ "HEARTBREAKER", "has_tags", "FRENCH" ], [ "HEARTBREAKER", "in_language", "FRENCH" ], [ "HEARTBREAKER", "release_year", "2010" ], [ "HEREAFTER", "has_tags", "FRENCH" ], [ "HEREAFTER", "in_language", "FRENCH" ], [ "HEREAFTER", "release_year", "2010" ], [ "LITTLE WHITE LIES", "in_language", "FRENCH" ], [ "LITTLE WHITE LIES", "release_year", "2010" ], [ "LOVE CRIME", "in_language", "FRENCH" ], [ "LOVE CRIME", "release_year", "2010" ], [ "MAMMUTH", "in_language", "FRENCH" ], [ "MAMMUTH", "release_year", "2010" ], [ "MAN AT BATH", "has_tags", "FRENCH" ], [ "MAN AT BATH", "in_language", "FRENCH" ], [ "MAN AT BATH", "release_year", "2010" ], [ "MOZART'S SISTER", "in_language", "FRENCH" ], [ "MOZART'S SISTER", "release_year", "2010" ], [ "MY AFTERNOONS WITH MARGUERITTE", "in_language", "FRENCH" ], [ "MY AFTERNOONS WITH MARGUERITTE", "release_year", "2010" ], [ "NOTHING TO DECLARE", "in_language", "FRENCH" ], [ "NOTHING TO DECLARE", "release_year", "2010" ], [ "OF GODS AND MEN", "in_language", "FRENCH" ], [ "OF GODS AND MEN", "release_year", "2010" ], [ "ON TOUR", "in_language", "FRENCH" ], [ "ON TOUR", "release_year", "2010" ], [ "OUR DAY WILL COME", "in_language", "FRENCH" ], [ "OUR DAY WILL COME", "release_year", "2010" ], [ "OUTSIDE THE LAW", "has_tags", "FRENCH" ], [ "OUTSIDE THE LAW", "in_language", "FRENCH" ], [ "OUTSIDE THE LAW", "release_year", "2010" ], [ "POINT BLANK", "in_language", "FRENCH" ], [ "POINT BLANK", "release_year", "2010" ], [ "POTICHE", "in_language", "FRENCH" ], [ "POTICHE", "release_year", "2010" ], [ "ROMANTICS ANONYMOUS", "has_tags", "FRENCH" ], [ "ROMANTICS ANONYMOUS", "in_language", "FRENCH" ], [ "ROMANTICS ANONYMOUS", "release_year", "2010" ], [ "THE BIG PICTURE", "has_tags", "FRENCH" ], [ "THE BIG PICTURE", "in_language", "FRENCH" ], [ "THE BIG PICTURE", "release_year", "2010" ], [ "THE CLINK OF ICE", "in_language", "FRENCH" ], [ "THE CLINK OF ICE", "release_year", "2010" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_tags", "FRENCH" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "in_language", "FRENCH" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "release_year", "2010" ], [ "THE ILLUSIONIST", "in_language", "FRENCH" ], [ "THE ILLUSIONIST", "release_year", "2010" ], [ "THE NAMES OF LOVE", "has_tags", "FRENCH" ], [ "THE NAMES OF LOVE", "in_language", "FRENCH" ], [ "THE NAMES OF LOVE", "release_year", "2010" ], [ "THE PRINCESS OF MONTPENSIER", "in_language", "FRENCH" ], [ "THE PRINCESS OF MONTPENSIER", "release_year", "2010" ], [ "THE WOMEN ON THE 6TH FLOOR", "in_language", "FRENCH" ], [ "THE WOMEN ON THE 6TH FLOOR", "release_year", "2010" ], [ "TOUT CE QUI BRILLE", "in_language", "FRENCH" ], [ "TOUT CE QUI BRILLE", "release_year", "2010" ], [ "TWICE UPON A TIME", "directed_by", "JOHN KORTY" ], [ "TWICE UPON A TIME", "has_tags", "BD-R" ], [ "TWICE UPON A TIME", "has_tags", "JOHN KORTY" ], [ "TWICE UPON A TIME", "written_by", "JOHN KORTY" ], [ "TWO IN THE WAVE", "in_language", "FRENCH" ], [ "TWO IN THE WAVE", "release_year", "2010" ], [ "WITH LOVE... FROM THE AGE OF REASON", "in_language", "FRENCH" ], [ "WITH LOVE... FROM THE AGE OF REASON", "release_year", "2010" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 17480, 1988 24438, 1993 37616, BORN YESTERDAY 7646, D.O.A. 27105, HERO AND THE TERROR 11421, STEFANO QUANTESTORIE 11310, THE REFORMER AND THE REDHEAD 17568, THE VANISHING src, edge_attr, dst 37616, release_year, 26423 37616, release_year, 24438 7646, release_year, 26423 7646, release_year, 17480 27105, release_year, 17480 11421, release_year, 24438 11310, release_year, 26423 17568, release_year, 17480 17568, release_year, 24438 Question: For what reason are HERO AND THE TERROR, STEFANO QUANTESTORIE, and THE REFORMER AND THE REDHEAD associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HERO AND THE TERROR", "STEFANO QUANTESTORIE", "THE REFORMER AND THE REDHEAD" ], "valid_edges": [ [ "BORN YESTERDAY", "release_year", "1950" ], [ "BORN YESTERDAY", "release_year", "1993" ], [ "D.O.A.", "release_year", "1950" ], [ "D.O.A.", "release_year", "1988" ], [ "HERO AND THE TERROR", "release_year", "1988" ], [ "STEFANO QUANTESTORIE", "release_year", "1993" ], [ "THE REFORMER AND THE REDHEAD", "release_year", "1950" ], [ "THE VANISHING", "release_year", "1988" ], [ "THE VANISHING", "release_year", "1993" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 29628, 28 DAYS 33688, ABERDEEN 21087, ADANGGAMAN 29155, ADRIAN HODGES 25900, ALMOST FAMOUS 37611, ANIMAL FACTORY 9078, APRIL CAPTAINS 24455, AUTUMN IN NEW YORK 33000, BAD LUCK LOVE 668, BATTLE FOR HADITHA 33410, BEFORE NIGHT FALLS 34615, BIG EDEN 39085, BILLY ELLIOT 3292, BOILER ROOM 18836, BOOTMEN 26583, BOUNCE 18439, BREAD AND ROSES 25059, CAST AWAY 395, CENTER STAGE 4476, CHOCOLAT 9601, COMEDY OF INNOCENCE 34253, COYOTE UGLY 19379, CRUEL INTENTIONS 2 3465, DANCER IN THE DARK 22930, DANCING AT THE BLUE IGUANA 22665, DIAMOND MEN 35235, DIRTY PICTURES 36212, DRAMA 27336, ERIN BROCKOVICH 16970, EUREKA 35306, EVERYTHING PUT TOGETHER 34004, FAIL SAFE 7108, FAITHLESS 8272, FINAL DESTINATION 34503, FINDING FORRESTER 32434, GEORGE WASHINGTON 4685, GIRLFIGHT 9778, GLADIATOR 32380, GOSSIP 20941, HAMLET 13413, HANGING UP 35023, HERE ON EARTH 6785, HEY RAM 22945, HIGH FIDELITY 33603, HOW TO KILL YOUR NEIGHBOR'S DOG 35899, JOE GOULD'S SECRET 37108, KING OF THE JUNGLE 17279, KIPPUR 40116, LAKEBOAT 18494, LIAM 1130, LISA PICARD IS FAMOUS 14822, LOCKDOWN 34628, MALÈNA 32842, ME YOU THEM 24153, MEN OF HONOR 21701, MERCY STREETS 31515, METROLAND 25561, MOHABBATEIN 2487, MY WEEK WITH MARILYN 1922, NINE QUEENS 30889, ON THE BEACH 28530, PASSION OF MIND 9995, PAY IT FORWARD 27893, POSSESSED 37084, PRICE OF GLORY 1687, PURELY BELTER 28745, RED PLANET 5193, REMEMBER THE TITANS 34510, REQUIEM FOR A DREAM 35664, RESTLESS 1372, RETURN TO ME 6759, RULES OF ENGAGEMENT 20488, SONGCATCHER 19388, STARDOM 30787, SUCH IS LIFE 2268, SUNSET STRIP 37356, SUSPICIOUS RIVER 30285, THE BEACH 16983, THE BENCH 5013, THE CIRCLE 15323, THE CONTENDER 16929, THE GIRL 39873, THE GOLDEN BOWL 29697, THE MILLION DOLLAR HOTEL 20674, THE NEXT BEST THING 36328, THE OPPORTUNISTS 39217, THE PERFECT STORM 29326, THE PRINCESS AND THE WARRIOR 29643, THE TAO OF STEVE 11250, THE TOWN IS QUIET 11360, THIRTEEN DAYS 3934, TIGERLAND 22625, TOGETHER 33836, TRAFFIC 24743, TULLY 24452, UNBREAKABLE 26494, UNDER SUSPICION 38911, WAKING THE DEAD 1183, WATER DROPS ON BURNING ROCKS 1524, WHAT LIES BENEATH 3572, WHAT'S COOKING? 33070, WHERE THE HEART IS 12162, YOU CAN COUNT ON ME src, edge_attr, dst 29628, has_genre, 36212 29628, release_year, 6776 33688, has_genre, 36212 33688, release_year, 6776 21087, has_genre, 36212 21087, release_year, 6776 25900, has_genre, 36212 25900, has_tags, 36212 25900, release_year, 6776 37611, has_genre, 36212 37611, release_year, 6776 9078, has_genre, 36212 9078, release_year, 6776 24455, has_genre, 36212 24455, release_year, 6776 33000, has_genre, 36212 33000, release_year, 6776 668, has_genre, 36212 33410, has_genre, 36212 33410, release_year, 6776 34615, has_genre, 36212 34615, release_year, 6776 39085, has_genre, 36212 39085, has_tags, 36212 39085, release_year, 6776 3292, has_genre, 36212 3292, release_year, 6776 18836, has_genre, 36212 18836, release_year, 6776 26583, has_genre, 36212 26583, release_year, 6776 18439, has_genre, 36212 18439, release_year, 6776 25059, has_genre, 36212 25059, has_tags, 36212 25059, release_year, 6776 395, has_genre, 36212 395, release_year, 6776 4476, has_genre, 36212 4476, release_year, 6776 9601, has_genre, 36212 9601, release_year, 6776 34253, has_genre, 36212 34253, release_year, 6776 19379, has_genre, 36212 19379, release_year, 6776 3465, has_genre, 36212 3465, has_tags, 36212 3465, release_year, 6776 22930, has_genre, 36212 22930, release_year, 6776 22665, has_genre, 36212 22665, release_year, 6776 35235, has_genre, 36212 35235, release_year, 6776 27336, has_genre, 36212 27336, has_tags, 36212 27336, release_year, 6776 16970, has_genre, 36212 16970, release_year, 6776 35306, has_genre, 36212 35306, release_year, 6776 34004, has_genre, 36212 34004, has_tags, 36212 34004, release_year, 6776 7108, has_genre, 36212 7108, release_year, 6776 8272, has_tags, 36212 8272, release_year, 6776 34503, has_genre, 36212 34503, release_year, 6776 32434, has_genre, 36212 32434, release_year, 6776 4685, has_genre, 36212 4685, has_tags, 36212 4685, release_year, 6776 9778, has_genre, 36212 9778, has_tags, 36212 9778, release_year, 6776 32380, has_genre, 36212 32380, release_year, 6776 20941, has_genre, 36212 20941, has_tags, 36212 20941, release_year, 6776 13413, has_genre, 36212 13413, release_year, 6776 35023, has_genre, 36212 35023, release_year, 6776 6785, has_genre, 36212 6785, release_year, 6776 22945, has_genre, 36212 22945, has_tags, 36212 22945, release_year, 6776 33603, has_genre, 36212 33603, release_year, 6776 35899, has_genre, 36212 35899, release_year, 6776 37108, has_genre, 36212 37108, release_year, 6776 17279, has_genre, 36212 17279, release_year, 6776 40116, has_genre, 36212 40116, release_year, 6776 18494, has_genre, 36212 18494, release_year, 6776 1130, has_genre, 36212 1130, release_year, 6776 14822, has_genre, 36212 14822, release_year, 6776 34628, has_genre, 36212 34628, has_tags, 36212 34628, release_year, 6776 32842, has_genre, 36212 32842, release_year, 6776 24153, has_genre, 36212 24153, release_year, 6776 21701, has_genre, 36212 21701, release_year, 6776 31515, has_genre, 36212 31515, written_by, 29155 25561, has_genre, 36212 25561, release_year, 6776 2487, has_genre, 36212 2487, written_by, 29155 1922, has_genre, 36212 1922, release_year, 6776 30889, has_genre, 36212 30889, release_year, 6776 28530, has_genre, 36212 28530, release_year, 6776 9995, has_genre, 36212 9995, has_tags, 36212 9995, release_year, 6776 27893, has_genre, 36212 27893, release_year, 6776 37084, has_genre, 36212 37084, release_year, 6776 1687, has_genre, 36212 1687, release_year, 6776 28745, release_year, 6776 5193, has_genre, 36212 5193, has_tags, 36212 5193, release_year, 6776 34510, has_genre, 36212 34510, has_tags, 36212 34510, release_year, 6776 35664, has_genre, 36212 35664, release_year, 6776 1372, has_genre, 36212 1372, release_year, 6776 6759, has_genre, 36212 6759, release_year, 6776 20488, has_genre, 36212 20488, has_tags, 36212 20488, release_year, 6776 19388, has_genre, 36212 19388, release_year, 6776 30787, has_genre, 36212 30787, release_year, 6776 2268, has_genre, 36212 2268, release_year, 6776 37356, has_genre, 36212 37356, release_year, 6776 30285, has_genre, 36212 30285, release_year, 6776 16983, has_genre, 36212 16983, release_year, 6776 5013, has_genre, 36212 5013, release_year, 6776 15323, has_genre, 36212 15323, release_year, 6776 16929, has_genre, 36212 16929, release_year, 6776 39873, has_genre, 36212 39873, release_year, 6776 29697, has_genre, 36212 29697, has_tags, 36212 29697, release_year, 6776 20674, has_genre, 36212 20674, release_year, 6776 36328, has_genre, 36212 36328, release_year, 6776 39217, has_genre, 36212 39217, has_tags, 36212 39217, release_year, 6776 29326, has_genre, 36212 29326, release_year, 6776 29643, has_genre, 36212 29643, release_year, 6776 11250, has_genre, 36212 11250, release_year, 6776 11360, has_genre, 36212 11360, release_year, 6776 3934, has_genre, 36212 3934, release_year, 6776 22625, has_genre, 36212 22625, release_year, 6776 33836, has_genre, 36212 33836, release_year, 6776 24743, has_genre, 36212 24743, release_year, 6776 24452, has_genre, 36212 24452, release_year, 6776 26494, has_genre, 36212 26494, release_year, 6776 38911, has_genre, 36212 38911, has_tags, 36212 38911, release_year, 6776 1183, has_genre, 36212 1183, release_year, 6776 1524, has_genre, 36212 1524, release_year, 6776 3572, has_genre, 36212 3572, release_year, 6776 33070, has_genre, 36212 33070, release_year, 6776 12162, has_genre, 36212 12162, release_year, 6776 Question: For what reason are ADRIAN HODGES, BATTLE FOR HADITHA, and RED PLANET associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ADRIAN HODGES", "BATTLE FOR HADITHA", "RED PLANET" ], "valid_edges": [ [ "28 DAYS", "has_genre", "DRAMA" ], [ "28 DAYS", "release_year", "2000" ], [ "ABERDEEN", "has_genre", "DRAMA" ], [ "ABERDEEN", "release_year", "2000" ], [ "ADANGGAMAN", "has_genre", "DRAMA" ], [ "ADANGGAMAN", "release_year", "2000" ], [ "ALMOST FAMOUS", "has_genre", "DRAMA" ], [ "ALMOST FAMOUS", "has_tags", "DRAMA" ], [ "ALMOST FAMOUS", "release_year", "2000" ], [ "ANIMAL FACTORY", "has_genre", "DRAMA" ], [ "ANIMAL FACTORY", "release_year", "2000" ], [ "APRIL CAPTAINS", "has_genre", "DRAMA" ], [ "APRIL CAPTAINS", "release_year", "2000" ], [ "AUTUMN IN NEW YORK", "has_genre", "DRAMA" ], [ "AUTUMN IN NEW YORK", "release_year", "2000" ], [ "BAD LUCK LOVE", "has_genre", "DRAMA" ], [ "BAD LUCK LOVE", "release_year", "2000" ], [ "BATTLE FOR HADITHA", "has_genre", "DRAMA" ], [ "BEFORE NIGHT FALLS", "has_genre", "DRAMA" ], [ "BEFORE NIGHT FALLS", "release_year", "2000" ], [ "BIG EDEN", "has_genre", "DRAMA" ], [ "BIG EDEN", "release_year", "2000" ], [ "BILLY ELLIOT", "has_genre", "DRAMA" ], [ "BILLY ELLIOT", "has_tags", "DRAMA" ], [ "BILLY ELLIOT", "release_year", "2000" ], [ "BOILER ROOM", "has_genre", "DRAMA" ], [ "BOILER ROOM", "release_year", "2000" ], [ "BOOTMEN", "has_genre", "DRAMA" ], [ "BOOTMEN", "release_year", "2000" ], [ "BOUNCE", "has_genre", "DRAMA" ], [ "BOUNCE", "release_year", "2000" ], [ "BREAD AND ROSES", "has_genre", "DRAMA" ], [ "BREAD AND ROSES", "release_year", "2000" ], [ "CAST AWAY", "has_genre", "DRAMA" ], [ "CAST AWAY", "has_tags", "DRAMA" ], [ "CAST AWAY", "release_year", "2000" ], [ "CENTER STAGE", "has_genre", "DRAMA" ], [ "CENTER STAGE", "release_year", "2000" ], [ "CHOCOLAT", "has_genre", "DRAMA" ], [ "CHOCOLAT", "release_year", "2000" ], [ "COMEDY OF INNOCENCE", "has_genre", "DRAMA" ], [ "COMEDY OF INNOCENCE", "release_year", "2000" ], [ "COYOTE UGLY", "has_genre", "DRAMA" ], [ "COYOTE UGLY", "release_year", "2000" ], [ "CRUEL INTENTIONS 2", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 2", "release_year", "2000" ], [ "DANCER IN THE DARK", "has_genre", "DRAMA" ], [ "DANCER IN THE DARK", "has_tags", "DRAMA" ], [ "DANCER IN THE DARK", "release_year", "2000" ], [ "DANCING AT THE BLUE IGUANA", "has_genre", "DRAMA" ], [ "DANCING AT THE BLUE IGUANA", "release_year", "2000" ], [ "DIAMOND MEN", "has_genre", "DRAMA" ], [ "DIAMOND MEN", "release_year", "2000" ], [ "DIRTY PICTURES", "has_genre", "DRAMA" ], [ "DIRTY PICTURES", "release_year", "2000" ], [ "ERIN BROCKOVICH", "has_genre", "DRAMA" ], [ "ERIN BROCKOVICH", "has_tags", "DRAMA" ], [ "ERIN BROCKOVICH", "release_year", "2000" ], [ "EUREKA", "has_genre", "DRAMA" ], [ "EUREKA", "release_year", "2000" ], [ "EVERYTHING PUT TOGETHER", "has_genre", "DRAMA" ], [ "EVERYTHING PUT TOGETHER", "release_year", "2000" ], [ "FAIL SAFE", "has_genre", "DRAMA" ], [ "FAIL SAFE", "has_tags", "DRAMA" ], [ "FAIL SAFE", "release_year", "2000" ], [ "FAITHLESS", "has_genre", "DRAMA" ], [ "FAITHLESS", "release_year", "2000" ], [ "FINAL DESTINATION", "has_tags", "DRAMA" ], [ "FINAL DESTINATION", "release_year", "2000" ], [ "FINDING FORRESTER", "has_genre", "DRAMA" ], [ "FINDING FORRESTER", "release_year", "2000" ], [ "GEORGE WASHINGTON", "has_genre", "DRAMA" ], [ "GEORGE WASHINGTON", "release_year", "2000" ], [ "GIRLFIGHT", "has_genre", "DRAMA" ], [ "GIRLFIGHT", "has_tags", "DRAMA" ], [ "GIRLFIGHT", "release_year", "2000" ], [ "GLADIATOR", "has_genre", "DRAMA" ], [ "GLADIATOR", "has_tags", "DRAMA" ], [ "GLADIATOR", "release_year", "2000" ], [ "GOSSIP", "has_genre", "DRAMA" ], [ "GOSSIP", "release_year", "2000" ], [ "HAMLET", "has_genre", "DRAMA" ], [ "HAMLET", "has_tags", "DRAMA" ], [ "HAMLET", "release_year", "2000" ], [ "HANGING UP", "has_genre", "DRAMA" ], [ "HANGING UP", "release_year", "2000" ], [ "HERE ON EARTH", "has_genre", "DRAMA" ], [ "HERE ON EARTH", "release_year", "2000" ], [ "HEY RAM", "has_genre", "DRAMA" ], [ "HEY RAM", "release_year", "2000" ], [ "HIGH FIDELITY", "has_genre", "DRAMA" ], [ "HIGH FIDELITY", "has_tags", "DRAMA" ], [ "HIGH FIDELITY", "release_year", "2000" ], [ "HOW TO KILL YOUR NEIGHBOR'S DOG", "has_genre", "DRAMA" ], [ "HOW TO KILL YOUR NEIGHBOR'S DOG", "release_year", "2000" ], [ "JOE GOULD'S SECRET", "has_genre", "DRAMA" ], [ "JOE GOULD'S SECRET", "release_year", "2000" ], [ "KING OF THE JUNGLE", "has_genre", "DRAMA" ], [ "KING OF THE JUNGLE", "release_year", "2000" ], [ "KIPPUR", "has_genre", "DRAMA" ], [ "KIPPUR", "release_year", "2000" ], [ "LAKEBOAT", "has_genre", "DRAMA" ], [ "LAKEBOAT", "release_year", "2000" ], [ "LIAM", "has_genre", "DRAMA" ], [ "LIAM", "release_year", "2000" ], [ "LISA PICARD IS FAMOUS", "has_genre", "DRAMA" ], [ "LISA PICARD IS FAMOUS", "release_year", "2000" ], [ "LOCKDOWN", "has_genre", "DRAMA" ], [ "LOCKDOWN", "release_year", "2000" ], [ "MALÈNA", "has_genre", "DRAMA" ], [ "MALÈNA", "has_tags", "DRAMA" ], [ "MALÈNA", "release_year", "2000" ], [ "ME YOU THEM", "has_genre", "DRAMA" ], [ "ME YOU THEM", "release_year", "2000" ], [ "MEN OF HONOR", "has_genre", "DRAMA" ], [ "MEN OF HONOR", "release_year", "2000" ], [ "MERCY STREETS", "has_genre", "DRAMA" ], [ "MERCY STREETS", "release_year", "2000" ], [ "METROLAND", "has_genre", "DRAMA" ], [ "METROLAND", "written_by", "ADRIAN HODGES" ], [ "MOHABBATEIN", "has_genre", "DRAMA" ], [ "MOHABBATEIN", "release_year", "2000" ], [ "MY WEEK WITH MARILYN", "has_genre", "DRAMA" ], [ "MY WEEK WITH MARILYN", "written_by", "ADRIAN HODGES" ], [ "NINE QUEENS", "has_genre", "DRAMA" ], [ "NINE QUEENS", "release_year", "2000" ], [ "ON THE BEACH", "has_genre", "DRAMA" ], [ "ON THE BEACH", "release_year", "2000" ], [ "PASSION OF MIND", "has_genre", "DRAMA" ], [ "PASSION OF MIND", "release_year", "2000" ], [ "PAY IT FORWARD", "has_genre", "DRAMA" ], [ "PAY IT FORWARD", "has_tags", "DRAMA" ], [ "PAY IT FORWARD", "release_year", "2000" ], [ "POSSESSED", "has_genre", "DRAMA" ], [ "POSSESSED", "release_year", "2000" ], [ "PRICE OF GLORY", "has_genre", "DRAMA" ], [ "PRICE OF GLORY", "release_year", "2000" ], [ "PURELY BELTER", "has_genre", "DRAMA" ], [ "PURELY BELTER", "release_year", "2000" ], [ "RED PLANET", "release_year", "2000" ], [ "REMEMBER THE TITANS", "has_genre", "DRAMA" ], [ "REMEMBER THE TITANS", "has_tags", "DRAMA" ], [ "REMEMBER THE TITANS", "release_year", "2000" ], [ "REQUIEM FOR A DREAM", "has_genre", "DRAMA" ], [ "REQUIEM FOR A DREAM", "has_tags", "DRAMA" ], [ "REQUIEM FOR A DREAM", "release_year", "2000" ], [ "RESTLESS", "has_genre", "DRAMA" ], [ "RESTLESS", "release_year", "2000" ], [ "RETURN TO ME", "has_genre", "DRAMA" ], [ "RETURN TO ME", "release_year", "2000" ], [ "RULES OF ENGAGEMENT", "has_genre", "DRAMA" ], [ "RULES OF ENGAGEMENT", "release_year", "2000" ], [ "SONGCATCHER", "has_genre", "DRAMA" ], [ "SONGCATCHER", "has_tags", "DRAMA" ], [ "SONGCATCHER", "release_year", "2000" ], [ "STARDOM", "has_genre", "DRAMA" ], [ "STARDOM", "release_year", "2000" ], [ "SUCH IS LIFE", "has_genre", "DRAMA" ], [ "SUCH IS LIFE", "release_year", "2000" ], [ "SUNSET STRIP", "has_genre", "DRAMA" ], [ "SUNSET STRIP", "release_year", "2000" ], [ "SUSPICIOUS RIVER", "has_genre", "DRAMA" ], [ "SUSPICIOUS RIVER", "release_year", "2000" ], [ "THE BEACH", "has_genre", "DRAMA" ], [ "THE BEACH", "release_year", "2000" ], [ "THE BENCH", "has_genre", "DRAMA" ], [ "THE BENCH", "release_year", "2000" ], [ "THE CIRCLE", "has_genre", "DRAMA" ], [ "THE CIRCLE", "release_year", "2000" ], [ "THE CONTENDER", "has_genre", "DRAMA" ], [ "THE CONTENDER", "release_year", "2000" ], [ "THE GIRL", "has_genre", "DRAMA" ], [ "THE GIRL", "release_year", "2000" ], [ "THE GOLDEN BOWL", "has_genre", "DRAMA" ], [ "THE GOLDEN BOWL", "release_year", "2000" ], [ "THE MILLION DOLLAR HOTEL", "has_genre", "DRAMA" ], [ "THE MILLION DOLLAR HOTEL", "has_tags", "DRAMA" ], [ "THE MILLION DOLLAR HOTEL", "release_year", "2000" ], [ "THE NEXT BEST THING", "has_genre", "DRAMA" ], [ "THE NEXT BEST THING", "release_year", "2000" ], [ "THE OPPORTUNISTS", "has_genre", "DRAMA" ], [ "THE OPPORTUNISTS", "release_year", "2000" ], [ "THE PERFECT STORM", "has_genre", "DRAMA" ], [ "THE PERFECT STORM", "has_tags", "DRAMA" ], [ "THE PERFECT STORM", "release_year", "2000" ], [ "THE PRINCESS AND THE WARRIOR", "has_genre", "DRAMA" ], [ "THE PRINCESS AND THE WARRIOR", "release_year", "2000" ], [ "THE TAO OF STEVE", "has_genre", "DRAMA" ], [ "THE TAO OF STEVE", "release_year", "2000" ], [ "THE TOWN IS QUIET", "has_genre", "DRAMA" ], [ "THE TOWN IS QUIET", "release_year", "2000" ], [ "THIRTEEN DAYS", "has_genre", "DRAMA" ], [ "THIRTEEN DAYS", "release_year", "2000" ], [ "TIGERLAND", "has_genre", "DRAMA" ], [ "TIGERLAND", "release_year", "2000" ], [ "TOGETHER", "has_genre", "DRAMA" ], [ "TOGETHER", "release_year", "2000" ], [ "TRAFFIC", "has_genre", "DRAMA" ], [ "TRAFFIC", "release_year", "2000" ], [ "TULLY", "has_genre", "DRAMA" ], [ "TULLY", "release_year", "2000" ], [ "UNBREAKABLE", "has_genre", "DRAMA" ], [ "UNBREAKABLE", "release_year", "2000" ], [ "UNDER SUSPICION", "has_genre", "DRAMA" ], [ "UNDER SUSPICION", "release_year", "2000" ], [ "WAKING THE DEAD", "has_genre", "DRAMA" ], [ "WAKING THE DEAD", "has_tags", "DRAMA" ], [ "WAKING THE DEAD", "release_year", "2000" ], [ "WATER DROPS ON BURNING ROCKS", "has_genre", "DRAMA" ], [ "WATER DROPS ON BURNING ROCKS", "release_year", "2000" ], [ "WHAT LIES BENEATH", "has_genre", "DRAMA" ], [ "WHAT LIES BENEATH", "release_year", "2000" ], [ "WHAT'S COOKING?", "has_genre", "DRAMA" ], [ "WHAT'S COOKING?", "release_year", "2000" ], [ "WHERE THE HEART IS", "has_genre", "DRAMA" ], [ "WHERE THE HEART IS", "release_year", "2000" ], [ "YOU CAN COUNT ON ME", "has_genre", "DRAMA" ], [ "YOU CAN COUNT ON ME", "release_year", "2000" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 28173, CLIMBING 36212, DRAMA 10487, GUTS 19722, INTERVIEW 1403, TARA ELDERS 7702, TO THE LIMIT src, edge_attr, dst 10487, has_genre, 36212 19722, has_genre, 36212 19722, has_tags, 36212 19722, release_year, 17315 19722, starred_actors, 1403 7702, has_tags, 28173 7702, release_year, 17315 Question: How are CLIMBING, GUTS, and TARA ELDERS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CLIMBING", "GUTS", "TARA ELDERS" ], "valid_edges": [ [ "GUTS", "has_genre", "DRAMA" ], [ "INTERVIEW", "has_genre", "DRAMA" ], [ "INTERVIEW", "has_tags", "DRAMA" ], [ "INTERVIEW", "release_year", "2007" ], [ "INTERVIEW", "starred_actors", "TARA ELDERS" ], [ "TO THE LIMIT", "has_tags", "CLIMBING" ], [ "TO THE LIMIT", "release_year", "2007" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3473, AMAZON WOMEN ON THE MOON 22939, ARSENIO HALL 2627, CLARENCE NASH 30463, COMEDY 9144, COMING TO AMERICA 36212, DRAMA 24494, ELLIE PARKER 5870, HORROR 141, I HEART HUCKABEES 18555, JOHN LANDIS 22764, NAOMI WATTS 19715, ST. VINCENT 2492, THE RING 17409, TRICK OR TREAT 6279, YOU WILL MEET A TALL DARK STRANGER src, edge_attr, dst 3473, directed_by, 18555 3473, has_genre, 30463 3473, starred_actors, 22939 9144, directed_by, 18555 9144, has_genre, 30463 9144, has_tags, 30463 9144, has_tags, 18555 9144, starred_actors, 22939 24494, has_genre, 30463 24494, has_genre, 36212 24494, starred_actors, 22764 141, has_genre, 30463 141, has_tags, 30463 141, has_tags, 22764 19715, has_genre, 30463 19715, has_genre, 36212 19715, has_tags, 22764 19715, starred_actors, 22764 2492, has_genre, 5870 2492, has_tags, 5870 2492, has_tags, 22764 2492, starred_actors, 22764 17409, has_genre, 5870 17409, starred_actors, 2627 6279, has_genre, 30463 6279, has_genre, 36212 6279, has_tags, 30463 6279, has_tags, 36212 6279, has_tags, 22764 Question: In what context are ARSENIO HALL, CLARENCE NASH, and NAOMI WATTS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ARSENIO HALL", "CLARENCE NASH", "NAOMI WATTS" ], "valid_edges": [ [ "AMAZON WOMEN ON THE MOON", "directed_by", "JOHN LANDIS" ], [ "AMAZON WOMEN ON THE MOON", "has_genre", "COMEDY" ], [ "AMAZON WOMEN ON THE MOON", "starred_actors", "ARSENIO HALL" ], [ "COMING TO AMERICA", "directed_by", "JOHN LANDIS" ], [ "COMING TO AMERICA", "has_genre", "COMEDY" ], [ "COMING TO AMERICA", "has_tags", "COMEDY" ], [ "COMING TO AMERICA", "has_tags", "JOHN LANDIS" ], [ "COMING TO AMERICA", "starred_actors", "ARSENIO HALL" ], [ "ELLIE PARKER", "has_genre", "COMEDY" ], [ "ELLIE PARKER", "has_genre", "DRAMA" ], [ "ELLIE PARKER", "starred_actors", "NAOMI WATTS" ], [ "I HEART HUCKABEES", "has_genre", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "NAOMI WATTS" ], [ "ST. VINCENT", "has_genre", "COMEDY" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "has_tags", "NAOMI WATTS" ], [ "ST. VINCENT", "starred_actors", "NAOMI WATTS" ], [ "THE RING", "has_genre", "HORROR" ], [ "THE RING", "has_tags", "HORROR" ], [ "THE RING", "has_tags", "NAOMI WATTS" ], [ "THE RING", "starred_actors", "NAOMI WATTS" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "starred_actors", "CLARENCE NASH" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_genre", "COMEDY" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_genre", "DRAMA" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "COMEDY" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "DRAMA" ], [ "YOU WILL MEET A TALL DARK STRANGER", "has_tags", "NAOMI WATTS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 22845, MUSIC 11061, PAUL ROBESON 238, RIDERS OF DESTINY 39373, SONG OF FREEDOM 15207, THE EMPEROR JONES 19226, THE MARC PEASE EXPERIENCE 23317, WILD BOYS OF THE ROAD src, edge_attr, dst 238, has_genre, 22845 238, release_year, 15506 39373, starred_actors, 11061 15207, release_year, 15506 15207, starred_actors, 11061 19226, has_genre, 22845 23317, release_year, 15506 Question: How are SONG OF FREEDOM, THE MARC PEASE EXPERIENCE, and WILD BOYS OF THE ROAD related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "SONG OF FREEDOM", "THE MARC PEASE EXPERIENCE", "WILD BOYS OF THE ROAD" ], "valid_edges": [ [ "RIDERS OF DESTINY", "has_genre", "MUSIC" ], [ "RIDERS OF DESTINY", "release_year", "1933" ], [ "SONG OF FREEDOM", "starred_actors", "PAUL ROBESON" ], [ "THE EMPEROR JONES", "release_year", "1933" ], [ "THE EMPEROR JONES", "starred_actors", "PAUL ROBESON" ], [ "THE MARC PEASE EXPERIENCE", "has_genre", "MUSIC" ], [ "WILD BOYS OF THE ROAD", "release_year", "1933" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 25221, 1981 28171, 1986 39289, ACTION 4763, ADVENTURE 18169, APRIL FOOL'S DAY 12952, ARMED AND DANGEROUS 35779, ARMOUR OF GOD 32646, AT LONG LAST LOVE 11687, CHARLIE SHEEN 14884, CLASS OF NUKE 'EM HIGH 30463, COMEDY 12489, CRAZY MAMA 6743, CRITTERS 29991, DAVID SELTZER 25400, DENHOLM ELLIOTT 2221, DOLEMITE 24481, FRANCHISE 310, GEORGE LUCAS 15135, GINGER AND FRED 13794, GOON 16240, HARRISON FORD 35856, HEARTS OF THE WEST 5870, HORROR 5068, HOT SHOTS! PART DEUX 10147, HOUSE 358, HOWARD THE DUCK 18585, INDIANA JONES 22790, INDIANA JONES AND THE LAST CRUSADE 8257, LIES MY FATHER TOLD ME 940, LIEV SCHREIBER 8851, LITTLE SHOP OF HORRORS 13183, LOVE AND DEATH 32181, LUCAS 38259, MONEY TALKS 20500, MONSTER IN THE CLOSET 32834, MONTY PYTHON AND THE HOLY GRAIL 32916, MY FRIENDS 26892, NAZIS 26151, NOBODY'S BABY 18416, ONE OF OUR DINOSAURS IS MISSING 8, PHANTOMS 8526, PUNCHLINE 29299, RAIDERS OF THE LOST ARK 34930, RANCHO DELUXE 33108, RUNNING SCARED 30173, SALT 1045, SMILE 34888, SOMETHING WILD 2152, SPIELBERG 23639, SPINNING BORIS 26730, STEVEN SPIELBERG 5932, TERRORVISION 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 5469, THE BEST OF TIMES 13685, THE CHASE 32237, THE FORTUNE 17331, THE LAST DAYS ON MARS 21920, THE OLSEN GANG ON THE TRACK 17910, THE OMEN 10721, THE ROCKY HORROR PICTURE SHOW 23847, THE STEPFORD WIVES 26081, THE SUNSHINE BOYS 9715, THE TEXAS CHAINSAW MASSACRE 2 7816, THE THREE MUSKETEERS src, edge_attr, dst 25221, has_genre, 30463 18169, has_genre, 30463 18169, release_year, 28171 12952, has_genre, 30463 12952, release_year, 28171 35779, has_genre, 30463 35779, release_year, 28171 32646, has_genre, 30463 32646, release_year, 39435 14884, has_genre, 30463 14884, release_year, 28171 12489, has_genre, 30463 12489, release_year, 39435 6743, has_genre, 30463 6743, release_year, 28171 2221, has_genre, 30463 2221, release_year, 39435 15135, has_genre, 30463 15135, release_year, 28171 13794, has_genre, 30463 13794, starred_actors, 940 35856, has_genre, 30463 35856, release_year, 39435 5068, has_genre, 30463 5068, has_tags, 11687 5068, has_tags, 30463 5068, starred_actors, 11687 10147, has_genre, 30463 10147, release_year, 28171 358, has_genre, 30463 358, release_year, 28171 22790, directed_by, 26730 22790, has_genre, 39289 22790, has_genre, 4763 22790, has_tags, 39289 22790, has_tags, 4763 22790, has_tags, 25400 22790, has_tags, 24481 22790, has_tags, 16240 22790, has_tags, 18585 22790, has_tags, 32181 22790, has_tags, 26892 22790, has_tags, 2152 22790, has_tags, 26730 22790, starred_actors, 25400 22790, starred_actors, 16240 22790, written_by, 310 8257, release_year, 39435 8851, has_genre, 30463 8851, release_year, 28171 13183, has_genre, 30463 13183, has_tags, 30463 13183, release_year, 39435 32181, directed_by, 29991 32181, has_genre, 30463 32181, has_tags, 11687 32181, release_year, 28171 32181, starred_actors, 11687 32181, written_by, 29991 38259, has_genre, 30463 38259, starred_actors, 11687 20500, has_genre, 30463 20500, release_year, 28171 32834, has_genre, 30463 32834, has_tags, 30463 32834, release_year, 39435 32916, has_genre, 30463 32916, release_year, 39435 26151, directed_by, 29991 26151, has_genre, 30463 26151, written_by, 29991 18416, has_genre, 30463 18416, release_year, 39435 8, has_genre, 5870 8, starred_actors, 940 8526, directed_by, 29991 8526, has_genre, 30463 8526, written_by, 29991 29299, directed_by, 26730 29299, has_genre, 39289 29299, has_genre, 4763 29299, has_tags, 39289 29299, has_tags, 4763 29299, has_tags, 25400 29299, has_tags, 24481 29299, has_tags, 16240 29299, has_tags, 18585 29299, has_tags, 32181 29299, has_tags, 26892 29299, has_tags, 2152 29299, has_tags, 26730 29299, release_year, 25221 29299, starred_actors, 16240 29299, written_by, 310 34930, has_genre, 30463 34930, release_year, 39435 33108, has_genre, 30463 33108, release_year, 28171 30173, has_genre, 39289 30173, has_tags, 39289 30173, has_tags, 940 30173, starred_actors, 940 1045, has_genre, 30463 1045, release_year, 39435 34888, has_genre, 30463 34888, release_year, 28171 23639, has_genre, 30463 23639, starred_actors, 940 5932, has_genre, 30463 5932, release_year, 28171 10409, has_genre, 30463 10409, release_year, 39435 5469, has_genre, 30463 5469, release_year, 28171 13685, has_genre, 30463 13685, has_tags, 11687 13685, starred_actors, 11687 32237, has_genre, 30463 32237, release_year, 39435 17331, has_genre, 5870 17331, starred_actors, 940 21920, has_genre, 30463 21920, release_year, 39435 17910, has_genre, 5870 17910, has_tags, 5870 17910, starred_actors, 940 17910, written_by, 29991 10721, has_genre, 30463 10721, release_year, 39435 23847, has_genre, 30463 23847, release_year, 39435 26081, has_genre, 30463 26081, release_year, 39435 9715, has_genre, 30463 9715, release_year, 28171 7816, has_genre, 30463 7816, starred_actors, 11687 Question: In what context are LIES MY FATHER TOLD ME, LIEV SCHREIBER, and LUCAS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LIES MY FATHER TOLD ME", "LIEV SCHREIBER", "LUCAS" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "APRIL FOOL'S DAY", "has_genre", "COMEDY" ], [ "APRIL FOOL'S DAY", "release_year", "1986" ], [ "ARMED AND DANGEROUS", "has_genre", "COMEDY" ], [ "ARMED AND DANGEROUS", "release_year", "1986" ], [ "ARMOUR OF GOD", "has_genre", "COMEDY" ], [ "ARMOUR OF GOD", "release_year", "1986" ], [ "AT LONG LAST LOVE", "has_genre", "COMEDY" ], [ "AT LONG LAST LOVE", "release_year", "1975" ], [ "CLASS OF NUKE 'EM HIGH", "has_genre", "COMEDY" ], [ "CLASS OF NUKE 'EM HIGH", "release_year", "1986" ], [ "CRAZY MAMA", "has_genre", "COMEDY" ], [ "CRAZY MAMA", "release_year", "1975" ], [ "CRITTERS", "has_genre", "COMEDY" ], [ "CRITTERS", "release_year", "1986" ], [ "DOLEMITE", "has_genre", "COMEDY" ], [ "DOLEMITE", "release_year", "1975" ], [ "GINGER AND FRED", "has_genre", "COMEDY" ], [ "GINGER AND FRED", "release_year", "1986" ], [ "GOON", "has_genre", "COMEDY" ], [ "GOON", "starred_actors", "LIEV SCHREIBER" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "release_year", "1975" ], [ "HOT SHOTS! PART DEUX", "has_genre", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "has_tags", "CHARLIE SHEEN" ], [ "HOT SHOTS! PART DEUX", "has_tags", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "starred_actors", "CHARLIE SHEEN" ], [ "HOUSE", "has_genre", "COMEDY" ], [ "HOUSE", "release_year", "1986" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "HOWARD THE DUCK", "release_year", "1986" ], [ "INDIANA JONES AND THE LAST CRUSADE", "directed_by", "STEVEN SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "DENHOLM ELLIOTT" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "FRANCHISE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "HARRISON FORD" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "INDIANA JONES" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "LUCAS" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "NAZIS" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "STEVEN SPIELBERG" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "DENHOLM ELLIOTT" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "HARRISON FORD" ], [ "INDIANA JONES AND THE LAST CRUSADE", "written_by", "GEORGE LUCAS" ], [ "LIES MY FATHER TOLD ME", "release_year", "1975" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "COMEDY" ], [ "LITTLE SHOP OF HORRORS", "release_year", "1986" ], [ "LOVE AND DEATH", "has_genre", "COMEDY" ], [ "LOVE AND DEATH", "has_tags", "COMEDY" ], [ "LOVE AND DEATH", "release_year", "1975" ], [ "LUCAS", "directed_by", "DAVID SELTZER" ], [ "LUCAS", "has_genre", "COMEDY" ], [ "LUCAS", "has_tags", "CHARLIE SHEEN" ], [ "LUCAS", "release_year", "1986" ], [ "LUCAS", "starred_actors", "CHARLIE SHEEN" ], [ "LUCAS", "written_by", "DAVID SELTZER" ], [ "MONEY TALKS", "has_genre", "COMEDY" ], [ "MONEY TALKS", "starred_actors", "CHARLIE SHEEN" ], [ "MONSTER IN THE CLOSET", "has_genre", "COMEDY" ], [ "MONSTER IN THE CLOSET", "release_year", "1986" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_genre", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_tags", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "release_year", "1975" ], [ "MY FRIENDS", "has_genre", "COMEDY" ], [ "MY FRIENDS", "release_year", "1975" ], [ "NOBODY'S BABY", "directed_by", "DAVID SELTZER" ], [ "NOBODY'S BABY", "has_genre", "COMEDY" ], [ "NOBODY'S BABY", "written_by", "DAVID SELTZER" ], [ "ONE OF OUR DINOSAURS IS MISSING", "has_genre", "COMEDY" ], [ "ONE OF OUR DINOSAURS IS MISSING", "release_year", "1975" ], [ "PHANTOMS", "has_genre", "HORROR" ], [ "PHANTOMS", "starred_actors", "LIEV SCHREIBER" ], [ "PUNCHLINE", "directed_by", "DAVID SELTZER" ], [ "PUNCHLINE", "has_genre", "COMEDY" ], [ "PUNCHLINE", "written_by", "DAVID SELTZER" ], [ "RAIDERS OF THE LOST ARK", "directed_by", "STEVEN SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "DENHOLM ELLIOTT" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "FRANCHISE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "INDIANA JONES" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "LUCAS" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "NAZIS" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "STEVEN SPIELBERG" ], [ "RAIDERS OF THE LOST ARK", "release_year", "1981" ], [ "RAIDERS OF THE LOST ARK", "starred_actors", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "written_by", "GEORGE LUCAS" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "release_year", "1975" ], [ "RUNNING SCARED", "has_genre", "COMEDY" ], [ "RUNNING SCARED", "release_year", "1986" ], [ "SALT", "has_genre", "ACTION" ], [ "SALT", "has_tags", "ACTION" ], [ "SALT", "has_tags", "LIEV SCHREIBER" ], [ "SALT", "starred_actors", "LIEV SCHREIBER" ], [ "SMILE", "has_genre", "COMEDY" ], [ "SMILE", "release_year", "1975" ], [ "SOMETHING WILD", "has_genre", "COMEDY" ], [ "SOMETHING WILD", "release_year", "1986" ], [ "SPINNING BORIS", "has_genre", "COMEDY" ], [ "SPINNING BORIS", "starred_actors", "LIEV SCHREIBER" ], [ "TERRORVISION", "has_genre", "COMEDY" ], [ "TERRORVISION", "release_year", "1986" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "COMEDY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "release_year", "1975" ], [ "THE BEST OF TIMES", "has_genre", "COMEDY" ], [ "THE BEST OF TIMES", "release_year", "1986" ], [ "THE CHASE", "has_genre", "COMEDY" ], [ "THE CHASE", "has_tags", "CHARLIE SHEEN" ], [ "THE CHASE", "starred_actors", "CHARLIE SHEEN" ], [ "THE FORTUNE", "has_genre", "COMEDY" ], [ "THE FORTUNE", "release_year", "1975" ], [ "THE LAST DAYS ON MARS", "has_genre", "HORROR" ], [ "THE LAST DAYS ON MARS", "starred_actors", "LIEV SCHREIBER" ], [ "THE OLSEN GANG ON THE TRACK", "has_genre", "COMEDY" ], [ "THE OLSEN GANG ON THE TRACK", "release_year", "1975" ], [ "THE OMEN", "has_genre", "HORROR" ], [ "THE OMEN", "has_tags", "HORROR" ], [ "THE OMEN", "starred_actors", "LIEV SCHREIBER" ], [ "THE OMEN", "written_by", "DAVID SELTZER" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "release_year", "1975" ], [ "THE STEPFORD WIVES", "has_genre", "COMEDY" ], [ "THE STEPFORD WIVES", "release_year", "1975" ], [ "THE SUNSHINE BOYS", "has_genre", "COMEDY" ], [ "THE SUNSHINE BOYS", "release_year", "1975" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_genre", "COMEDY" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "release_year", "1986" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "starred_actors", "CHARLIE SHEEN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 1006, 1996 8486, 1999 30146, A CHRISTMAS CAROL 29638, ALICE IN WONDERLAND 10045, BD-R 350, BOYS ON THE SIDE 30182, BURGLAR 33914, CHÉRI 14728, CLASSIC 30463, COMEDY 36212, DRAMA 10757, EDDIE 2939, EMMANUEL MOURET 22958, FAMOUS 36066, FANTASY 6012, FRENCH 12126, GHOSTS OF MISSISSIPPI 22532, GIRL, INTERRUPTED 10964, HOW STELLA GOT HER GROOVE BACK 35335, IT ALL STARTS TODAY 2938, JUMPIN' JACK FLASH 17663, MADE IN AMERICA 21386, POLA X 32180, RAT RACE 8379, ROMANCE 39915, SHALL WE KISS? 8652, SISTER ACT 6882, THE COLOR PURPLE 6150, THE CONFESSION 791, THE DEEP END OF THE OCEAN 9799, THE LOST SON 35362, THE MAGICAL LEGEND OF THE LEPRECHAUNS 29027, THE TELEPHONE 16292, TRUE STORY 37332, WHOOPI GOLDBERG 21449, YOU WILL BE MY SON src, edge_attr, dst 30146, has_genre, 30463 30146, has_genre, 36212 30146, has_genre, 36066 30146, has_imdb_votes, 22958 30146, has_tags, 10045 30146, has_tags, 14728 30146, release_year, 8486 30146, starred_actors, 37332 29638, has_genre, 36066 29638, has_tags, 10045 29638, has_tags, 14728 29638, has_tags, 36066 29638, release_year, 38097 29638, release_year, 8486 29638, starred_actors, 37332 350, has_genre, 30463 350, has_genre, 36212 350, has_tags, 37332 350, starred_actors, 37332 30182, has_genre, 30463 30182, starred_actors, 37332 33914, has_genre, 36212 33914, in_language, 6012 10757, has_genre, 30463 10757, release_year, 1006 10757, starred_actors, 37332 12126, has_genre, 36212 12126, has_tags, 16292 12126, has_tags, 37332 12126, release_year, 1006 12126, starred_actors, 37332 22532, has_genre, 36212 22532, has_tags, 36212 22532, has_tags, 37332 22532, release_year, 8486 10964, has_genre, 36212 10964, has_tags, 37332 10964, starred_actors, 37332 35335, has_genre, 36212 35335, in_language, 6012 2938, has_genre, 30463 2938, has_tags, 37332 2938, starred_actors, 37332 17663, has_genre, 30463 17663, has_tags, 37332 17663, starred_actors, 37332 21386, has_genre, 36212 21386, in_language, 6012 32180, has_genre, 30463 32180, has_tags, 30463 32180, has_tags, 37332 8379, has_genre, 36212 8379, in_language, 6012 39915, directed_by, 2939 39915, has_genre, 30463 39915, in_language, 6012 39915, starred_actors, 2939 39915, written_by, 2939 8652, has_genre, 30463 8652, has_tags, 37332 8652, starred_actors, 37332 6882, has_genre, 36212 6882, has_imdb_votes, 22958 6882, has_tags, 37332 6882, release_year, 38097 6882, starred_actors, 37332 6150, has_genre, 36212 6150, in_language, 6012 791, has_genre, 36212 791, release_year, 8486 791, starred_actors, 37332 9799, has_genre, 36212 9799, in_language, 6012 35362, release_year, 8486 35362, starred_actors, 37332 29027, has_genre, 30463 29027, starred_actors, 37332 16292, has_genre, 36212 16292, has_tags, 36212 21449, has_genre, 36212 21449, in_language, 6012 Question: How are EMMANUEL MOURET, WHOOPI GOLDBERG, and YOU WILL BE MY SON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EMMANUEL MOURET", "WHOOPI GOLDBERG", "YOU WILL BE MY SON" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A CHRISTMAS CAROL", "has_genre", "FANTASY" ], [ "A CHRISTMAS CAROL", "has_imdb_votes", "FAMOUS" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "has_tags", "CLASSIC" ], [ "A CHRISTMAS CAROL", "release_year", "1999" ], [ "A CHRISTMAS CAROL", "starred_actors", "WHOOPI GOLDBERG" ], [ "ALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "ALICE IN WONDERLAND", "has_tags", "BD-R" ], [ "ALICE IN WONDERLAND", "has_tags", "CLASSIC" ], [ "ALICE IN WONDERLAND", "has_tags", "FANTASY" ], [ "ALICE IN WONDERLAND", "release_year", "1985" ], [ "ALICE IN WONDERLAND", "release_year", "1999" ], [ "ALICE IN WONDERLAND", "starred_actors", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_genre", "DRAMA" ], [ "BOYS ON THE SIDE", "has_tags", "WHOOPI GOLDBERG" ], [ "BOYS ON THE SIDE", "starred_actors", "WHOOPI GOLDBERG" ], [ "BURGLAR", "has_genre", "COMEDY" ], [ "BURGLAR", "starred_actors", "WHOOPI GOLDBERG" ], [ "CHÉRI", "has_genre", "DRAMA" ], [ "CHÉRI", "in_language", "FRENCH" ], [ "EDDIE", "has_genre", "COMEDY" ], [ "EDDIE", "release_year", "1996" ], [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "GHOSTS OF MISSISSIPPI", "has_genre", "DRAMA" ], [ "GHOSTS OF MISSISSIPPI", "has_tags", "TRUE STORY" ], [ "GHOSTS OF MISSISSIPPI", "has_tags", "WHOOPI GOLDBERG" ], [ "GHOSTS OF MISSISSIPPI", "release_year", "1996" ], [ "GHOSTS OF MISSISSIPPI", "starred_actors", "WHOOPI GOLDBERG" ], [ "GIRL, INTERRUPTED", "has_genre", "DRAMA" ], [ "GIRL, INTERRUPTED", "has_tags", "DRAMA" ], [ "GIRL, INTERRUPTED", "has_tags", "WHOOPI GOLDBERG" ], [ "GIRL, INTERRUPTED", "release_year", "1999" ], [ "HOW STELLA GOT HER GROOVE BACK", "has_genre", "DRAMA" ], [ "HOW STELLA GOT HER GROOVE BACK", "has_tags", "WHOOPI GOLDBERG" ], [ "HOW STELLA GOT HER GROOVE BACK", "starred_actors", "WHOOPI GOLDBERG" ], [ "IT ALL STARTS TODAY", "has_genre", "DRAMA" ], [ "IT ALL STARTS TODAY", "in_language", "FRENCH" ], [ "JUMPIN' JACK FLASH", "has_genre", "COMEDY" ], [ "JUMPIN' JACK FLASH", "has_tags", "WHOOPI GOLDBERG" ], [ "JUMPIN' JACK FLASH", "starred_actors", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "has_tags", "WHOOPI GOLDBERG" ], [ "MADE IN AMERICA", "starred_actors", "WHOOPI GOLDBERG" ], [ "POLA X", "has_genre", "DRAMA" ], [ "POLA X", "in_language", "FRENCH" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "has_tags", "WHOOPI GOLDBERG" ], [ "ROMANCE", "has_genre", "DRAMA" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "directed_by", "EMMANUEL MOURET" ], [ "SHALL WE KISS?", "has_genre", "COMEDY" ], [ "SHALL WE KISS?", "in_language", "FRENCH" ], [ "SHALL WE KISS?", "starred_actors", "EMMANUEL MOURET" ], [ "SHALL WE KISS?", "written_by", "EMMANUEL MOURET" ], [ "SISTER ACT", "has_genre", "COMEDY" ], [ "SISTER ACT", "has_tags", "WHOOPI GOLDBERG" ], [ "SISTER ACT", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE COLOR PURPLE", "has_genre", "DRAMA" ], [ "THE COLOR PURPLE", "has_imdb_votes", "FAMOUS" ], [ "THE COLOR PURPLE", "has_tags", "WHOOPI GOLDBERG" ], [ "THE COLOR PURPLE", "release_year", "1985" ], [ "THE COLOR PURPLE", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE CONFESSION", "has_genre", "DRAMA" ], [ "THE CONFESSION", "in_language", "FRENCH" ], [ "THE DEEP END OF THE OCEAN", "has_genre", "DRAMA" ], [ "THE DEEP END OF THE OCEAN", "release_year", "1999" ], [ "THE DEEP END OF THE OCEAN", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE LOST SON", "has_genre", "DRAMA" ], [ "THE LOST SON", "in_language", "FRENCH" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "release_year", "1999" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "WHOOPI GOLDBERG" ], [ "THE TELEPHONE", "has_genre", "COMEDY" ], [ "THE TELEPHONE", "starred_actors", "WHOOPI GOLDBERG" ], [ "TRUE STORY", "has_genre", "DRAMA" ], [ "TRUE STORY", "has_tags", "DRAMA" ], [ "YOU WILL BE MY SON", "has_genre", "DRAMA" ], [ "YOU WILL BE MY SON", "in_language", "FRENCH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10825, 1973 17315, 2007 39289, ACTION 36348, AKIRA 9677, ANATOMY OF A MURDER 32828, BADLANDS 19131, BONNIE AND CLYDE 27059, CATCH ME IF YOU CAN 9201, CHARLEY VARRICK 14724, CRIME 7316, DANISH 23396, DIAL M FOR MURDER 23283, EDGE OF DARKNESS 21123, FARGO 1033, FRACTURE 23299, GET CARTER 22449, GOODFELLAS 4423, GUN CRAZY 12189, HARRY BROWN 25061, I AM A FUGITIVE FROM A CHAIN GANG 20430, IN THE BEDROOM 39264, JUST ANOTHER LOVE STORY 10706, MAMI KOYAMA 6267, MARTIN SHEEN 33561, MEAN STREETS 3487, MINORITY REPORT 27827, MONSTER 28476, MURDER 11311, MURDER ON THE ORIENT EXPRESS 37497, NATIONAL FILM REGISTRY 20417, NIGHTWATCH 3935, OLE BORNEDAL 22122, PRETTY POISON 31741, PRIMAL FEAR 12428, RAGE 16364, ROPE 22196, SERPICO 27807, SHAFT 29168, SISSY SPACEK 40046, STRANGERS ON A TRAIN 28619, SUMMER OF SAM 12, TAXI DRIVER 30951, THE CANDY SNATCHERS 22630, THE DON IS DEAD 31555, THE FRESHMAN 13245, THE FRIENDS OF EDDIE COYLE 35551, THE GODFATHER 27885, THE KILLERS 4827, THE MALTESE FALCON 34901, THE OUTFIT 37148, THE SECRET IN THEIR EYES 4294, THE SUBSTITUTE src, edge_attr, dst 36348, has_genre, 39289 36348, has_tags, 39289 36348, starred_actors, 10706 9677, has_genre, 14724 9677, has_tags, 14724 9677, has_tags, 28476 32828, has_genre, 14724 32828, has_tags, 14724 32828, has_tags, 6267 32828, has_tags, 28476 32828, has_tags, 37497 32828, has_tags, 29168 32828, release_year, 10825 32828, starred_actors, 6267 32828, starred_actors, 29168 19131, has_genre, 14724 19131, has_tags, 14724 19131, has_tags, 37497 27059, has_genre, 14724 27059, has_tags, 14724 27059, has_tags, 6267 27059, starred_actors, 6267 9201, has_genre, 14724 9201, release_year, 10825 23396, has_genre, 14724 23396, has_tags, 28476 23283, has_genre, 14724 23283, has_tags, 28476 21123, has_genre, 14724 21123, has_tags, 14724 21123, has_tags, 37497 1033, has_genre, 14724 1033, has_tags, 28476 23299, has_genre, 14724 23299, has_tags, 28476 22449, has_genre, 14724 22449, has_tags, 14724 22449, has_tags, 37497 4423, has_genre, 14724 4423, has_tags, 14724 4423, has_tags, 37497 12189, has_genre, 14724 12189, has_tags, 28476 25061, has_genre, 14724 25061, has_tags, 37497 20430, has_genre, 14724 20430, starred_actors, 29168 39264, directed_by, 3935 39264, in_language, 7316 39264, release_year, 17315 39264, written_by, 3935 33561, has_genre, 14724 33561, has_tags, 37497 33561, release_year, 10825 3487, has_tags, 14724 3487, has_tags, 28476 27827, has_genre, 14724 27827, has_tags, 14724 27827, has_tags, 28476 11311, has_genre, 14724 11311, has_tags, 28476 20417, directed_by, 3935 20417, in_language, 7316 20417, written_by, 3935 22122, has_genre, 14724 22122, has_tags, 28476 31741, has_genre, 14724 31741, has_tags, 14724 31741, has_tags, 28476 12428, has_genre, 14724 12428, has_tags, 14724 12428, starred_actors, 6267 16364, has_genre, 14724 16364, has_tags, 28476 22196, has_genre, 14724 22196, release_year, 10825 27807, has_genre, 14724 27807, has_tags, 37497 40046, has_genre, 14724 40046, has_tags, 28476 28619, has_genre, 14724 28619, has_tags, 28476 12, has_genre, 14724 12, has_tags, 37497 30951, has_genre, 14724 30951, release_year, 10825 22630, has_genre, 14724 22630, release_year, 10825 31555, has_genre, 14724 31555, has_tags, 37497 13245, has_genre, 14724 13245, release_year, 10825 35551, has_genre, 14724 35551, has_tags, 14724 35551, has_tags, 37497 27885, has_genre, 14724 27885, has_tags, 37497 4827, has_genre, 14724 4827, has_tags, 37497 34901, has_genre, 14724 34901, release_year, 10825 37148, has_tags, 14724 37148, has_tags, 28476 4294, directed_by, 3935 4294, has_genre, 39289 4294, has_genre, 14724 4294, in_language, 7316 4294, release_year, 17315 4294, written_by, 3935 Question: For what reason are BADLANDS, MAMI KOYAMA, and OLE BORNEDAL associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BADLANDS", "MAMI KOYAMA", "OLE BORNEDAL" ], "valid_edges": [ [ "AKIRA", "has_genre", "ACTION" ], [ "AKIRA", "has_tags", "ACTION" ], [ "AKIRA", "starred_actors", "MAMI KOYAMA" ], [ "ANATOMY OF A MURDER", "has_genre", "CRIME" ], [ "ANATOMY OF A MURDER", "has_tags", "CRIME" ], [ "ANATOMY OF A MURDER", "has_tags", "MURDER" ], [ "BADLANDS", "has_genre", "CRIME" ], [ "BADLANDS", "has_tags", "CRIME" ], [ "BADLANDS", "has_tags", "MARTIN SHEEN" ], [ "BADLANDS", "has_tags", "MURDER" ], [ "BADLANDS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BADLANDS", "has_tags", "SISSY SPACEK" ], [ "BADLANDS", "release_year", "1973" ], [ "BADLANDS", "starred_actors", "MARTIN SHEEN" ], [ "BADLANDS", "starred_actors", "SISSY SPACEK" ], [ "BONNIE AND CLYDE", "has_genre", "CRIME" ], [ "BONNIE AND CLYDE", "has_tags", "CRIME" ], [ "BONNIE AND CLYDE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "MARTIN SHEEN" ], [ "CATCH ME IF YOU CAN", "starred_actors", "MARTIN SHEEN" ], [ "CHARLEY VARRICK", "has_genre", "CRIME" ], [ "CHARLEY VARRICK", "release_year", "1973" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "has_tags", "MURDER" ], [ "EDGE OF DARKNESS", "has_genre", "CRIME" ], [ "EDGE OF DARKNESS", "has_tags", "MURDER" ], [ "FARGO", "has_genre", "CRIME" ], [ "FARGO", "has_tags", "CRIME" ], [ "FARGO", "has_tags", "NATIONAL FILM REGISTRY" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_tags", "MURDER" ], [ "GET CARTER", "has_genre", "CRIME" ], [ "GET CARTER", "has_tags", "MURDER" ], [ "GOODFELLAS", "has_genre", "CRIME" ], [ "GOODFELLAS", "has_tags", "CRIME" ], [ "GOODFELLAS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "GUN CRAZY", "has_genre", "CRIME" ], [ "GUN CRAZY", "has_tags", "CRIME" ], [ "GUN CRAZY", "has_tags", "NATIONAL FILM REGISTRY" ], [ "HARRY BROWN", "has_genre", "CRIME" ], [ "HARRY BROWN", "has_tags", "MURDER" ], [ "I AM A FUGITIVE FROM A CHAIN GANG", "has_genre", "CRIME" ], [ "I AM A FUGITIVE FROM A CHAIN GANG", "has_tags", "NATIONAL FILM REGISTRY" ], [ "IN THE BEDROOM", "has_genre", "CRIME" ], [ "IN THE BEDROOM", "starred_actors", "SISSY SPACEK" ], [ "JUST ANOTHER LOVE STORY", "directed_by", "OLE BORNEDAL" ], [ "JUST ANOTHER LOVE STORY", "in_language", "DANISH" ], [ "JUST ANOTHER LOVE STORY", "release_year", "2007" ], [ "JUST ANOTHER LOVE STORY", "written_by", "OLE BORNEDAL" ], [ "MEAN STREETS", "has_genre", "CRIME" ], [ "MEAN STREETS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "MEAN STREETS", "release_year", "1973" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "MURDER" ], [ "MONSTER", "has_genre", "CRIME" ], [ "MONSTER", "has_tags", "CRIME" ], [ "MONSTER", "has_tags", "MURDER" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "CRIME" ], [ "MURDER ON THE ORIENT EXPRESS", "has_tags", "MURDER" ], [ "NIGHTWATCH", "directed_by", "OLE BORNEDAL" ], [ "NIGHTWATCH", "in_language", "DANISH" ], [ "NIGHTWATCH", "written_by", "OLE BORNEDAL" ], [ "PRETTY POISON", "has_genre", "CRIME" ], [ "PRETTY POISON", "has_tags", "MURDER" ], [ "PRIMAL FEAR", "has_genre", "CRIME" ], [ "PRIMAL FEAR", "has_tags", "CRIME" ], [ "PRIMAL FEAR", "has_tags", "MURDER" ], [ "RAGE", "has_genre", "CRIME" ], [ "RAGE", "has_tags", "CRIME" ], [ "RAGE", "starred_actors", "MARTIN SHEEN" ], [ "ROPE", "has_genre", "CRIME" ], [ "ROPE", "has_tags", "MURDER" ], [ "SERPICO", "has_genre", "CRIME" ], [ "SERPICO", "release_year", "1973" ], [ "SHAFT", "has_genre", "CRIME" ], [ "SHAFT", "has_tags", "NATIONAL FILM REGISTRY" ], [ "STRANGERS ON A TRAIN", "has_genre", "CRIME" ], [ "STRANGERS ON A TRAIN", "has_tags", "MURDER" ], [ "SUMMER OF SAM", "has_genre", "CRIME" ], [ "SUMMER OF SAM", "has_tags", "MURDER" ], [ "TAXI DRIVER", "has_genre", "CRIME" ], [ "TAXI DRIVER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE CANDY SNATCHERS", "has_genre", "CRIME" ], [ "THE CANDY SNATCHERS", "release_year", "1973" ], [ "THE DON IS DEAD", "has_genre", "CRIME" ], [ "THE DON IS DEAD", "release_year", "1973" ], [ "THE FRESHMAN", "has_genre", "CRIME" ], [ "THE FRESHMAN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE FRIENDS OF EDDIE COYLE", "has_genre", "CRIME" ], [ "THE FRIENDS OF EDDIE COYLE", "release_year", "1973" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "CRIME" ], [ "THE GODFATHER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE KILLERS", "has_genre", "CRIME" ], [ "THE KILLERS", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE MALTESE FALCON", "has_genre", "CRIME" ], [ "THE MALTESE FALCON", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE OUTFIT", "has_genre", "CRIME" ], [ "THE OUTFIT", "release_year", "1973" ], [ "THE SECRET IN THEIR EYES", "has_tags", "CRIME" ], [ "THE SECRET IN THEIR EYES", "has_tags", "MURDER" ], [ "THE SUBSTITUTE", "directed_by", "OLE BORNEDAL" ], [ "THE SUBSTITUTE", "has_genre", "ACTION" ], [ "THE SUBSTITUTE", "has_genre", "CRIME" ], [ "THE SUBSTITUTE", "in_language", "DANISH" ], [ "THE SUBSTITUTE", "release_year", "2007" ], [ "THE SUBSTITUTE", "written_by", "OLE BORNEDAL" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 14896, 3 IDIOTS 319, A BUG'S LIFE 30146, A CHRISTMAS CAROL 24039, A GOOD YEAR 8198, A PRAIRIE HOME COMPANION 6476, A WALK IN THE WOODS 4763, ADVENTURE 30985, ADVENTURELAND 16054, ADVENTURES IN BABYSITTING 28412, AFRICA SCREAMS 16486, AGENT CODY BANKS 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 35485, ALMOST HEROES 38447, ALWAYS LEAVE THEM LAUGHING 39876, ANNIE 35941, ANTZ 18310, AROUND THE WORLD IN 80 DAYS 2385, AROUND THE WORLD IN EIGHTY DAYS 1822, AWAY WE GO 35639, BABY'S DAY OUT 38657, BEAT THE DEVIL 32479, BEWITCHED 18646, BIG SHOTS 11779, BIG TOP PEE-WEE 7314, BOLT 11066, BOMBER 31957, BOY 12910, BRIEF INTERVIEWS WITH HIDEOUS MEN 5823, BROTHER BEAR 2 14480, BUDDIES 10356, BUNTY AUR BABLI 1587, BUSHWHACKED 30039, CAPTAIN JANUARY 33196, CARS 16795, CASANOVA'S BIG NIGHT 524, CHARLIE'S ANGELS 10349, CHICAGO 21479, CITY ISLAND 28503, CLOUDBURST 38556, COLD SOULS 30463, COMEDY 29904, CONDORMAN 30802, CUTTHROAT ISLAND 22663, DAN IN REAL LIFE 32301, DEFENDOR 25657, DELHI-6 36212, DRAMA 5881, ELEPHANT BOY 1329, ENVY 19367, ESCAPE TO ATHENA 2449, EUROTRIP 18031, FAR AND AWAY 15349, FINDING NEMO 2287, FLUSHED AWAY 5287, FROZEN 5514, FUNNY PEOPLE 2320, GRIND 17440, GULLIVER'S TRAVELS 20263, HAIR 4649, HAPPY TEARS 11014, HE'S JUST NOT THAT INTO YOU 1292, HEDWIG AND THE ANGRY INCH 20008, HELP! 39494, HOLES 7811, HORTON HEARS A WHO! 5617, HOT TUB TIME MACHINE 358, HOWARD THE DUCK 38457, I CAN DO BAD ALL BY MYSELF 16371, ICE AGE 38176, IDIOT'S DELIGHT 5747, IMAGINE THAT 32383, JOE DIRT 2368, KANGAROO JACK 32995, LAND HO! 25097, LAND OF THE LOST 17903, LEAVES OF GRASS 19667, LIFE DURING WARTIME 16814, LITTLE WHITE LIES 35457, MADEA GOES TO JAIL 7813, MARY AND MAX 10378, MAURY YESTON 25283, MAVERICK 13873, MIDDLE MEN 17135, MOM AND DAD SAVE THE WORLD 34451, MOTHERHOOD 11444, MR. ROBINSON CRUSOE 32058, MUPPET TREASURE ISLAND 3027, NIGHT AT THE MUSEUM 17860, NINE 32358, NORTH 14797, O BROTHER, WHERE ART THOU? 8108, PAPER MAN 25824, PARADISE 30055, PEE-WEE'S BIG ADVENTURE 23964, PENNIES FROM HEAVEN 2391, PIRATES 31703, PUSS IN BOOTS 30475, RIO 10686, RIO 2 28221, ROMANCING THE STONE 35586, SAHARA 10371, SAINT JOHN OF LAS VEGAS 5629, SCOOBY-DOO! THE MYSTERY BEGINS 4945, SEPARATION CITY 38231, SHANGHAI NOON 29832, SHOW BOAT 23608, SIX DAYS SEVEN NIGHTS 24506, SPACE CHIMPS 18657, SPIES LIKE US 38596, SPREAD 20689, STARSTRUCK 25480, SUPER MARIO BROS. 26790, SWEPT AWAY 32312, TAKING WOODSTOCK 2584, THE ADVENTURES OF BARON MUNCHAUSEN 36394, THE ADVENTURES OF ELMO IN GROUCHLAND 13521, THE ADVENTURES OF FORD FAIRLANE 27549, THE BOOK OF LIFE 22479, THE BOXTROLLS 10194, THE BRAVE LITTLE TOASTER 21330, THE CRIMSON PIRATE 33846, THE CROODS 2102, THE DARWIN AWARDS 18263, THE DUKES OF HAZZARD 4068, THE GENERAL 5518, THE GOONIES 32102, THE HARD WAY 5080, THE HOUSE OF BRANCHING LOVE 18150, THE JEWEL OF THE NILE 32856, THE KING AND FOUR QUEENS 15588, THE LAST REMAKE OF BEAU GESTE 39875, THE LEGO MOVIE 18874, THE MAID 6999, THE MISFORTUNATES 9262, THE MISSING PERSON 9886, THE OPEN ROAD 3765, THE OTHER WOMAN 29641, THE PRINCESS BRIDE 31851, THE PRISONER OF ZENDA 23530, THE ROAD TO EL DORADO 17460, THE RUGRATS MOVIE 2739, THE SAPPHIRES 30746, THE SECRET LIFE OF WALTER MITTY 15608, THE SPONGEBOB SQUAREPANTS MOVIE 23400, THE STUPIDS 7816, THE THREE MUSKETEERS 1772, THE WILD 20291, THE WIZARD 17209, THERE'S NO BUSINESS LIKE SHOW BUSINESS 37331, TO DIE FOR 25443, TOM JONES 9450, TOY STORY 14499, TOY STORY 2 30747, TROOP BEVERLY HILLS 5574, UP 38723, VIBES 11659, VIVA MARIA! 1486, WAKE 11010, WILD AMERICA 12576, YOUTH IN REVOLT 2542, ZAMBEZIA 29480, ZEUS AND ROXANNE src, edge_attr, dst 25221, has_genre, 30463 25221, has_genre, 36212 14896, has_genre, 30463 14896, has_genre, 36212 319, has_genre, 4763 319, has_genre, 30463 319, has_tags, 30463 30146, has_genre, 30463 30146, has_genre, 36212 24039, has_genre, 30463 24039, has_genre, 36212 8198, has_genre, 30463 8198, has_genre, 36212 6476, has_genre, 4763 6476, has_genre, 30463 30985, has_genre, 30463 30985, has_genre, 36212 16054, has_genre, 4763 16054, has_genre, 30463 16054, has_tags, 4763 28412, has_genre, 4763 28412, has_genre, 30463 16486, has_genre, 4763 16486, has_genre, 30463 22412, has_genre, 4763 22412, has_genre, 30463 22412, has_tags, 4763 35485, has_genre, 4763 35485, has_genre, 30463 38447, has_genre, 30463 38447, has_genre, 36212 39876, has_genre, 30463 39876, has_genre, 36212 35941, has_genre, 4763 35941, has_genre, 30463 35941, has_tags, 4763 18310, has_genre, 4763 18310, has_genre, 30463 2385, has_genre, 4763 2385, has_genre, 30463 1822, has_genre, 30463 1822, has_genre, 36212 35639, has_genre, 4763 35639, has_genre, 30463 38657, has_genre, 4763 38657, has_genre, 30463 32479, has_genre, 30463 32479, has_genre, 36212 32479, has_tags, 30463 18646, has_genre, 4763 18646, has_genre, 30463 11779, has_genre, 4763 11779, has_genre, 30463 7314, has_genre, 4763 7314, has_genre, 30463 11066, has_genre, 30463 11066, has_genre, 36212 31957, has_genre, 30463 31957, has_genre, 36212 12910, has_genre, 30463 12910, has_genre, 36212 5823, has_genre, 4763 5823, has_genre, 30463 14480, has_genre, 4763 14480, has_genre, 30463 10356, has_genre, 4763 10356, has_genre, 30463 1587, has_genre, 4763 1587, has_genre, 30463 30039, has_genre, 30463 30039, has_genre, 36212 33196, has_genre, 4763 33196, has_genre, 30463 33196, has_tags, 30463 16795, has_genre, 4763 16795, has_genre, 30463 524, has_genre, 4763 524, has_genre, 30463 10349, has_genre, 30463 10349, has_genre, 36212 21479, has_genre, 30463 21479, has_genre, 36212 28503, has_genre, 4763 28503, has_genre, 30463 28503, has_genre, 36212 38556, has_genre, 30463 38556, has_genre, 36212 29904, has_genre, 4763 29904, has_genre, 30463 30802, has_genre, 4763 30802, has_genre, 30463 30802, has_tags, 4763 22663, has_genre, 30463 22663, has_genre, 36212 32301, has_genre, 30463 32301, has_genre, 36212 25657, has_genre, 30463 25657, has_genre, 36212 5881, has_genre, 4763 1329, has_genre, 30463 1329, has_genre, 36212 19367, has_genre, 4763 19367, has_genre, 30463 2449, has_genre, 4763 2449, has_genre, 30463 2449, has_tags, 30463 18031, has_genre, 4763 18031, has_genre, 36212 15349, has_genre, 4763 15349, has_genre, 30463 15349, has_tags, 30463 2287, has_genre, 4763 2287, has_genre, 30463 5287, has_genre, 30463 5287, has_genre, 36212 5514, has_genre, 30463 5514, has_genre, 36212 5514, has_tags, 30463 5514, has_tags, 36212 2320, has_genre, 4763 2320, has_genre, 30463 17440, has_genre, 4763 17440, has_genre, 30463 17440, has_tags, 30463 20263, has_genre, 30463 20263, has_genre, 36212 4649, has_genre, 30463 4649, has_genre, 36212 11014, has_genre, 30463 11014, has_genre, 36212 1292, has_genre, 30463 1292, has_genre, 36212 20008, has_genre, 4763 20008, has_genre, 30463 39494, has_genre, 4763 39494, has_genre, 30463 39494, has_genre, 36212 7811, has_genre, 4763 7811, has_genre, 30463 7811, has_tags, 30463 5617, has_genre, 4763 5617, has_genre, 30463 5617, has_tags, 30463 358, has_genre, 4763 358, has_genre, 30463 38457, has_genre, 30463 38457, has_genre, 36212 16371, has_genre, 4763 16371, has_genre, 30463 16371, has_tags, 30463 38176, has_genre, 30463 38176, has_genre, 36212 5747, has_genre, 30463 5747, has_genre, 36212 32383, has_genre, 4763 32383, has_genre, 30463 2368, has_genre, 4763 2368, has_genre, 30463 2368, has_tags, 30463 32995, has_genre, 4763 32995, has_genre, 30463 25097, has_genre, 4763 25097, has_genre, 30463 25097, has_tags, 30463 17903, has_genre, 30463 17903, has_genre, 36212 19667, has_genre, 30463 19667, has_genre, 36212 16814, has_genre, 30463 16814, has_genre, 36212 35457, has_genre, 30463 35457, has_genre, 36212 35457, has_tags, 30463 7813, has_genre, 30463 7813, has_genre, 36212 25283, has_genre, 4763 25283, has_genre, 30463 25283, has_tags, 30463 13873, has_genre, 30463 13873, has_genre, 36212 17135, has_genre, 4763 17135, has_genre, 30463 34451, has_genre, 30463 34451, has_genre, 36212 11444, has_genre, 4763 11444, has_genre, 30463 32058, has_genre, 4763 32058, has_genre, 30463 3027, has_genre, 4763 3027, has_genre, 30463 17860, has_genre, 36212 17860, written_by, 10378 32358, has_genre, 4763 32358, has_genre, 30463 32358, has_genre, 36212 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 8108, has_genre, 30463 8108, has_genre, 36212 25824, has_genre, 4763 25824, has_genre, 30463 25824, has_genre, 36212 30055, has_genre, 4763 30055, has_genre, 30463 23964, has_genre, 30463 23964, has_genre, 36212 2391, has_genre, 4763 2391, has_genre, 30463 31703, has_genre, 4763 31703, has_genre, 30463 30475, has_genre, 4763 30475, has_genre, 30463 30475, has_tags, 4763 30475, has_tags, 30463 10686, has_genre, 4763 10686, has_genre, 30463 28221, has_genre, 4763 28221, has_genre, 30463 28221, has_tags, 4763 35586, has_genre, 4763 35586, has_genre, 30463 35586, has_genre, 36212 10371, has_genre, 30463 10371, has_genre, 36212 5629, has_genre, 4763 5629, has_genre, 30463 4945, has_genre, 30463 4945, has_genre, 36212 38231, has_genre, 4763 38231, has_genre, 30463 29832, has_genre, 30463 29832, has_genre, 36212 23608, has_genre, 4763 23608, has_genre, 30463 23608, has_tags, 4763 23608, has_tags, 30463 24506, has_genre, 4763 24506, has_genre, 30463 18657, has_genre, 4763 18657, has_genre, 30463 38596, has_genre, 30463 38596, has_genre, 36212 20689, has_genre, 30463 20689, has_genre, 36212 25480, has_genre, 4763 25480, has_genre, 30463 25480, has_tags, 30463 26790, has_genre, 4763 26790, has_genre, 30463 26790, has_genre, 36212 32312, has_genre, 30463 32312, has_genre, 36212 2584, has_genre, 4763 2584, has_genre, 30463 36394, has_genre, 4763 36394, has_genre, 30463 13521, has_genre, 4763 13521, has_genre, 30463 13521, has_tags, 30463 27549, has_genre, 4763 27549, has_genre, 30463 22479, has_genre, 4763 22479, has_genre, 30463 22479, has_tags, 4763 10194, has_genre, 4763 10194, has_genre, 30463 21330, has_genre, 4763 21330, has_genre, 30463 33846, has_genre, 4763 33846, has_genre, 30463 33846, has_tags, 30463 2102, has_genre, 4763 2102, has_genre, 30463 18263, has_genre, 4763 18263, has_genre, 30463 4068, has_genre, 4763 4068, has_genre, 30463 4068, has_tags, 30463 5518, has_genre, 4763 5518, has_genre, 30463 5518, has_tags, 4763 32102, has_genre, 30463 32102, has_genre, 36212 5080, has_genre, 30463 5080, has_genre, 36212 18150, has_genre, 4763 18150, has_genre, 30463 18150, has_tags, 4763 18150, has_tags, 30463 32856, has_genre, 4763 32856, has_genre, 30463 15588, has_genre, 4763 15588, has_genre, 30463 39875, has_genre, 4763 39875, has_genre, 30463 18874, has_genre, 30463 18874, has_genre, 36212 6999, has_genre, 30463 6999, has_genre, 36212 9262, has_genre, 30463 9262, has_genre, 36212 9886, has_genre, 30463 9886, has_genre, 36212 3765, has_genre, 30463 3765, has_genre, 36212 29641, has_genre, 4763 29641, has_genre, 30463 29641, has_tags, 30463 31851, has_genre, 4763 31851, has_genre, 30463 31851, has_genre, 36212 23530, has_genre, 4763 23530, has_genre, 30463 17460, has_genre, 4763 17460, has_genre, 30463 2739, has_genre, 30463 2739, has_genre, 36212 30746, has_genre, 4763 30746, has_genre, 30463 30746, has_genre, 36212 15608, has_genre, 4763 15608, has_genre, 30463 23400, has_genre, 4763 23400, has_genre, 30463 7816, has_genre, 4763 7816, has_genre, 30463 7816, has_genre, 36212 1772, has_genre, 4763 1772, has_genre, 30463 20291, has_genre, 4763 20291, has_genre, 30463 20291, has_genre, 36212 17209, has_genre, 30463 17209, has_genre, 36212 37331, has_genre, 30463 37331, has_genre, 36212 25443, has_genre, 4763 25443, has_genre, 30463 9450, has_genre, 4763 9450, has_genre, 30463 9450, has_tags, 4763 9450, has_tags, 30463 14499, has_genre, 4763 14499, has_genre, 30463 30747, has_genre, 4763 30747, has_genre, 30463 5574, has_genre, 4763 5574, has_genre, 30463 5574, has_tags, 4763 5574, has_tags, 30463 38723, has_genre, 4763 38723, has_genre, 30463 11659, has_genre, 4763 11659, has_genre, 30463 1486, has_genre, 30463 1486, has_genre, 36212 11010, has_genre, 4763 11010, has_genre, 30463 12576, has_genre, 30463 12576, has_genre, 36212 2542, has_genre, 4763 2542, has_genre, 30463 29480, has_genre, 4763 29480, has_genre, 30463 Question: For what reason are DAN IN REAL LIFE, ELEPHANT BOY, and MAURY YESTON associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAN IN REAL LIFE", "ELEPHANT BOY", "MAURY YESTON" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "1981", "has_genre", "DRAMA" ], [ "3 IDIOTS", "has_genre", "COMEDY" ], [ "3 IDIOTS", "has_genre", "DRAMA" ], [ "A BUG'S LIFE", "has_genre", "ADVENTURE" ], [ "A BUG'S LIFE", "has_genre", "COMEDY" ], [ "A BUG'S LIFE", "has_tags", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "has_genre", "DRAMA" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "COMEDY" ], [ "A PRAIRIE HOME COMPANION", "has_genre", "DRAMA" ], [ "A WALK IN THE WOODS", "has_genre", "ADVENTURE" ], [ "A WALK IN THE WOODS", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "DRAMA" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "AFRICA SCREAMS", "has_genre", "ADVENTURE" ], [ "AFRICA SCREAMS", "has_genre", "COMEDY" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "ALMOST HEROES", "has_genre", "ADVENTURE" ], [ "ALMOST HEROES", "has_genre", "COMEDY" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "COMEDY" ], [ "ALWAYS LEAVE THEM LAUGHING", "has_genre", "DRAMA" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANTZ", "has_genre", "ADVENTURE" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "has_tags", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "COMEDY" ], [ "AROUND THE WORLD IN EIGHTY DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN EIGHTY DAYS", "has_genre", "COMEDY" ], [ "AWAY WE GO", "has_genre", "COMEDY" ], [ "AWAY WE GO", "has_genre", "DRAMA" ], [ "BABY'S DAY OUT", "has_genre", "ADVENTURE" ], [ "BABY'S DAY OUT", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_genre", "COMEDY" ], [ "BEWITCHED", "has_genre", "DRAMA" ], [ "BEWITCHED", "has_tags", "COMEDY" ], [ "BIG SHOTS", "has_genre", "ADVENTURE" ], [ "BIG SHOTS", "has_genre", "COMEDY" ], [ "BIG TOP PEE-WEE", "has_genre", "ADVENTURE" ], [ "BIG TOP PEE-WEE", "has_genre", "COMEDY" ], [ "BOLT", "has_genre", "ADVENTURE" ], [ "BOLT", "has_genre", "COMEDY" ], [ "BOMBER", "has_genre", "COMEDY" ], [ "BOMBER", "has_genre", "DRAMA" ], [ "BOY", "has_genre", "COMEDY" ], [ "BOY", "has_genre", "DRAMA" ], [ "BRIEF INTERVIEWS WITH HIDEOUS MEN", "has_genre", "COMEDY" ], [ "BRIEF INTERVIEWS WITH HIDEOUS MEN", "has_genre", "DRAMA" ], [ "BROTHER BEAR 2", "has_genre", "ADVENTURE" ], [ "BROTHER BEAR 2", "has_genre", "COMEDY" ], [ "BUDDIES", "has_genre", "ADVENTURE" ], [ "BUDDIES", "has_genre", "COMEDY" ], [ "BUNTY AUR BABLI", "has_genre", "ADVENTURE" ], [ "BUNTY AUR BABLI", "has_genre", "COMEDY" ], [ "BUSHWHACKED", "has_genre", "ADVENTURE" ], [ "BUSHWHACKED", "has_genre", "COMEDY" ], [ "CAPTAIN JANUARY", "has_genre", "COMEDY" ], [ "CAPTAIN JANUARY", "has_genre", "DRAMA" ], [ "CARS", "has_genre", "ADVENTURE" ], [ "CARS", "has_genre", "COMEDY" ], [ "CARS", "has_tags", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "ADVENTURE" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CITY ISLAND", "has_genre", "COMEDY" ], [ "CITY ISLAND", "has_genre", "DRAMA" ], [ "CLOUDBURST", "has_genre", "ADVENTURE" ], [ "CLOUDBURST", "has_genre", "COMEDY" ], [ "CLOUDBURST", "has_genre", "DRAMA" ], [ "COLD SOULS", "has_genre", "COMEDY" ], [ "COLD SOULS", "has_genre", "DRAMA" ], [ "CONDORMAN", "has_genre", "ADVENTURE" ], [ "CONDORMAN", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "DAN IN REAL LIFE", "has_genre", "COMEDY" ], [ "DAN IN REAL LIFE", "has_genre", "DRAMA" ], [ "DEFENDOR", "has_genre", "COMEDY" ], [ "DEFENDOR", "has_genre", "DRAMA" ], [ "DELHI-6", "has_genre", "COMEDY" ], [ "DELHI-6", "has_genre", "DRAMA" ], [ "ELEPHANT BOY", "has_genre", "ADVENTURE" ], [ "ENVY", "has_genre", "COMEDY" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ESCAPE TO ATHENA", "has_genre", "ADVENTURE" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_genre", "ADVENTURE" ], [ "EUROTRIP", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_tags", "COMEDY" ], [ "FAR AND AWAY", "has_genre", "ADVENTURE" ], [ "FAR AND AWAY", "has_genre", "DRAMA" ], [ "FINDING NEMO", "has_genre", "ADVENTURE" ], [ "FINDING NEMO", "has_genre", "COMEDY" ], [ "FINDING NEMO", "has_tags", "COMEDY" ], [ "FLUSHED AWAY", "has_genre", "ADVENTURE" ], [ "FLUSHED AWAY", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_genre", "COMEDY" ], [ "FUNNY PEOPLE", "has_genre", "DRAMA" ], [ "FUNNY PEOPLE", "has_tags", "COMEDY" ], [ "FUNNY PEOPLE", "has_tags", "DRAMA" ], [ "GRIND", "has_genre", "ADVENTURE" ], [ "GRIND", "has_genre", "COMEDY" ], [ "GULLIVER'S TRAVELS", "has_genre", "ADVENTURE" ], [ "GULLIVER'S TRAVELS", "has_genre", "COMEDY" ], [ "GULLIVER'S TRAVELS", "has_tags", "COMEDY" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "has_genre", "DRAMA" ], [ "HAPPY TEARS", "has_genre", "COMEDY" ], [ "HAPPY TEARS", "has_genre", "DRAMA" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "COMEDY" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HELP!", "has_genre", "ADVENTURE" ], [ "HELP!", "has_genre", "COMEDY" ], [ "HOLES", "has_genre", "ADVENTURE" ], [ "HOLES", "has_genre", "COMEDY" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HORTON HEARS A WHO!", "has_genre", "ADVENTURE" ], [ "HORTON HEARS A WHO!", "has_genre", "COMEDY" ], [ "HORTON HEARS A WHO!", "has_tags", "COMEDY" ], [ "HOT TUB TIME MACHINE", "has_genre", "ADVENTURE" ], [ "HOT TUB TIME MACHINE", "has_genre", "COMEDY" ], [ "HOT TUB TIME MACHINE", "has_tags", "COMEDY" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "I CAN DO BAD ALL BY MYSELF", "has_genre", "COMEDY" ], [ "I CAN DO BAD ALL BY MYSELF", "has_genre", "DRAMA" ], [ "ICE AGE", "has_genre", "ADVENTURE" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "IDIOT'S DELIGHT", "has_genre", "COMEDY" ], [ "IDIOT'S DELIGHT", "has_genre", "DRAMA" ], [ "IMAGINE THAT", "has_genre", "COMEDY" ], [ "IMAGINE THAT", "has_genre", "DRAMA" ], [ "JOE DIRT", "has_genre", "ADVENTURE" ], [ "JOE DIRT", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_genre", "ADVENTURE" ], [ "KANGAROO JACK", "has_genre", "COMEDY" ], [ "KANGAROO JACK", "has_tags", "COMEDY" ], [ "LAND HO!", "has_genre", "ADVENTURE" ], [ "LAND HO!", "has_genre", "COMEDY" ], [ "LAND OF THE LOST", "has_genre", "ADVENTURE" ], [ "LAND OF THE LOST", "has_genre", "COMEDY" ], [ "LAND OF THE LOST", "has_tags", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "DRAMA" ], [ "LIFE DURING WARTIME", "has_genre", "COMEDY" ], [ "LIFE DURING WARTIME", "has_genre", "DRAMA" ], [ "LITTLE WHITE LIES", "has_genre", "COMEDY" ], [ "LITTLE WHITE LIES", "has_genre", "DRAMA" ], [ "MADEA GOES TO JAIL", "has_genre", "COMEDY" ], [ "MADEA GOES TO JAIL", "has_genre", "DRAMA" ], [ "MADEA GOES TO JAIL", "has_tags", "COMEDY" ], [ "MARY AND MAX", "has_genre", "COMEDY" ], [ "MARY AND MAX", "has_genre", "DRAMA" ], [ "MAVERICK", "has_genre", "ADVENTURE" ], [ "MAVERICK", "has_genre", "COMEDY" ], [ "MAVERICK", "has_tags", "COMEDY" ], [ "MIDDLE MEN", "has_genre", "COMEDY" ], [ "MIDDLE MEN", "has_genre", "DRAMA" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "ADVENTURE" ], [ "MOM AND DAD SAVE THE WORLD", "has_genre", "COMEDY" ], [ "MOTHERHOOD", "has_genre", "COMEDY" ], [ "MOTHERHOOD", "has_genre", "DRAMA" ], [ "MR. ROBINSON CRUSOE", "has_genre", "ADVENTURE" ], [ "MR. ROBINSON CRUSOE", "has_genre", "COMEDY" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "has_genre", "ADVENTURE" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NINE", "has_genre", "DRAMA" ], [ "NINE", "written_by", "MAURY YESTON" ], [ "NORTH", "has_genre", "ADVENTURE" ], [ "NORTH", "has_genre", "COMEDY" ], [ "NORTH", "has_genre", "DRAMA" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "PAPER MAN", "has_genre", "COMEDY" ], [ "PAPER MAN", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "ADVENTURE" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PEE-WEE'S BIG ADVENTURE", "has_genre", "ADVENTURE" ], [ "PEE-WEE'S BIG ADVENTURE", "has_genre", "COMEDY" ], [ "PENNIES FROM HEAVEN", "has_genre", "COMEDY" ], [ "PENNIES FROM HEAVEN", "has_genre", "DRAMA" ], [ "PIRATES", "has_genre", "ADVENTURE" ], [ "PIRATES", "has_genre", "COMEDY" ], [ "PUSS IN BOOTS", "has_genre", "ADVENTURE" ], [ "PUSS IN BOOTS", "has_genre", "COMEDY" ], [ "RIO", "has_genre", "ADVENTURE" ], [ "RIO", "has_genre", "COMEDY" ], [ "RIO", "has_tags", "ADVENTURE" ], [ "RIO", "has_tags", "COMEDY" ], [ "RIO 2", "has_genre", "ADVENTURE" ], [ "RIO 2", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAINT JOHN OF LAS VEGAS", "has_genre", "COMEDY" ], [ "SAINT JOHN OF LAS VEGAS", "has_genre", "DRAMA" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "ADVENTURE" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "COMEDY" ], [ "SEPARATION CITY", "has_genre", "COMEDY" ], [ "SEPARATION CITY", "has_genre", "DRAMA" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHANGHAI NOON", "has_genre", "COMEDY" ], [ "SHOW BOAT", "has_genre", "COMEDY" ], [ "SHOW BOAT", "has_genre", "DRAMA" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "ADVENTURE" ], [ "SIX DAYS SEVEN NIGHTS", "has_genre", "COMEDY" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "ADVENTURE" ], [ "SIX DAYS SEVEN NIGHTS", "has_tags", "COMEDY" ], [ "SPACE CHIMPS", "has_genre", "ADVENTURE" ], [ "SPACE CHIMPS", "has_genre", "COMEDY" ], [ "SPIES LIKE US", "has_genre", "ADVENTURE" ], [ "SPIES LIKE US", "has_genre", "COMEDY" ], [ "SPREAD", "has_genre", "COMEDY" ], [ "SPREAD", "has_genre", "DRAMA" ], [ "STARSTRUCK", "has_genre", "COMEDY" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "SUPER MARIO BROS.", "has_genre", "ADVENTURE" ], [ "SUPER MARIO BROS.", "has_genre", "COMEDY" ], [ "SUPER MARIO BROS.", "has_tags", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "TAKING WOODSTOCK", "has_genre", "COMEDY" ], [ "TAKING WOODSTOCK", "has_genre", "DRAMA" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF ELMO IN GROUCHLAND", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF ELMO IN GROUCHLAND", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE BOOK OF LIFE", "has_genre", "ADVENTURE" ], [ "THE BOOK OF LIFE", "has_genre", "COMEDY" ], [ "THE BOXTROLLS", "has_genre", "ADVENTURE" ], [ "THE BOXTROLLS", "has_genre", "COMEDY" ], [ "THE BOXTROLLS", "has_tags", "ADVENTURE" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "ADVENTURE" ], [ "THE BRAVE LITTLE TOASTER", "has_genre", "COMEDY" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_genre", "COMEDY" ], [ "THE CROODS", "has_genre", "ADVENTURE" ], [ "THE CROODS", "has_genre", "COMEDY" ], [ "THE CROODS", "has_tags", "COMEDY" ], [ "THE DARWIN AWARDS", "has_genre", "ADVENTURE" ], [ "THE DARWIN AWARDS", "has_genre", "COMEDY" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE DUKES OF HAZZARD", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE GOONIES", "has_genre", "ADVENTURE" ], [ "THE GOONIES", "has_genre", "COMEDY" ], [ "THE GOONIES", "has_tags", "ADVENTURE" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HOUSE OF BRANCHING LOVE", "has_genre", "COMEDY" ], [ "THE HOUSE OF BRANCHING LOVE", "has_genre", "DRAMA" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_genre", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "COMEDY" ], [ "THE KING AND FOUR QUEENS", "has_genre", "ADVENTURE" ], [ "THE KING AND FOUR QUEENS", "has_genre", "COMEDY" ], [ "THE LAST REMAKE OF BEAU GESTE", "has_genre", "ADVENTURE" ], [ "THE LAST REMAKE OF BEAU GESTE", "has_genre", "COMEDY" ], [ "THE LEGO MOVIE", "has_genre", "ADVENTURE" ], [ "THE LEGO MOVIE", "has_genre", "COMEDY" ], [ "THE MAID", "has_genre", "COMEDY" ], [ "THE MAID", "has_genre", "DRAMA" ], [ "THE MISFORTUNATES", "has_genre", "COMEDY" ], [ "THE MISFORTUNATES", "has_genre", "DRAMA" ], [ "THE MISSING PERSON", "has_genre", "COMEDY" ], [ "THE MISSING PERSON", "has_genre", "DRAMA" ], [ "THE OPEN ROAD", "has_genre", "COMEDY" ], [ "THE OPEN ROAD", "has_genre", "DRAMA" ], [ "THE OTHER WOMAN", "has_genre", "COMEDY" ], [ "THE OTHER WOMAN", "has_genre", "DRAMA" ], [ "THE PRINCESS BRIDE", "has_genre", "ADVENTURE" ], [ "THE PRINCESS BRIDE", "has_genre", "COMEDY" ], [ "THE PRINCESS BRIDE", "has_tags", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE ROAD TO EL DORADO", "has_genre", "ADVENTURE" ], [ "THE ROAD TO EL DORADO", "has_genre", "COMEDY" ], [ "THE RUGRATS MOVIE", "has_genre", "ADVENTURE" ], [ "THE RUGRATS MOVIE", "has_genre", "COMEDY" ], [ "THE SAPPHIRES", "has_genre", "COMEDY" ], [ "THE SAPPHIRES", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "ADVENTURE" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "COMEDY" ], [ "THE STUPIDS", "has_genre", "ADVENTURE" ], [ "THE STUPIDS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE WILD", "has_genre", "ADVENTURE" ], [ "THE WILD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "ADVENTURE" ], [ "THE WIZARD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "DRAMA" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "COMEDY" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "DRAMA" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_genre", "COMEDY" ], [ "TOY STORY", "has_genre", "ADVENTURE" ], [ "TOY STORY", "has_genre", "COMEDY" ], [ "TOY STORY", "has_tags", "ADVENTURE" ], [ "TOY STORY", "has_tags", "COMEDY" ], [ "TOY STORY 2", "has_genre", "ADVENTURE" ], [ "TOY STORY 2", "has_genre", "COMEDY" ], [ "TROOP BEVERLY HILLS", "has_genre", "ADVENTURE" ], [ "TROOP BEVERLY HILLS", "has_genre", "COMEDY" ], [ "UP", "has_genre", "ADVENTURE" ], [ "UP", "has_genre", "COMEDY" ], [ "UP", "has_tags", "ADVENTURE" ], [ "UP", "has_tags", "COMEDY" ], [ "VIBES", "has_genre", "ADVENTURE" ], [ "VIBES", "has_genre", "COMEDY" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "WAKE", "has_genre", "COMEDY" ], [ "WAKE", "has_genre", "DRAMA" ], [ "WILD AMERICA", "has_genre", "ADVENTURE" ], [ "WILD AMERICA", "has_genre", "COMEDY" ], [ "YOUTH IN REVOLT", "has_genre", "COMEDY" ], [ "YOUTH IN REVOLT", "has_genre", "DRAMA" ], [ "ZAMBEZIA", "has_genre", "ADVENTURE" ], [ "ZAMBEZIA", "has_genre", "COMEDY" ], [ "ZEUS AND ROXANNE", "has_genre", "ADVENTURE" ], [ "ZEUS AND ROXANNE", "has_genre", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 29170, BREATHING FIRE 30463, COMEDY 16978, DON'T TELL MOM THE BABYSITTER'S DEAD 21745, EDDIE SAAVEDRA 25973, HITCH 2745, JOSH CHARLES 670, KEVIN BISCH 1053, PIE IN THE SKY 16762, THREESOME src, edge_attr, dst 29170, release_year, 10702 29170, starred_actors, 21745 16978, has_genre, 30463 16978, release_year, 10702 16978, starred_actors, 2745 25973, has_genre, 30463 25973, has_tags, 30463 25973, written_by, 670 1053, has_genre, 30463 1053, starred_actors, 2745 16762, has_genre, 30463 16762, has_tags, 30463 16762, starred_actors, 2745 Question: For what reason are EDDIE SAAVEDRA, JOSH CHARLES, and KEVIN BISCH associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EDDIE SAAVEDRA", "JOSH CHARLES", "KEVIN BISCH" ], "valid_edges": [ [ "BREATHING FIRE", "release_year", "1991" ], [ "BREATHING FIRE", "starred_actors", "EDDIE SAAVEDRA" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "has_genre", "COMEDY" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "release_year", "1991" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "starred_actors", "JOSH CHARLES" ], [ "HITCH", "has_genre", "COMEDY" ], [ "HITCH", "has_tags", "COMEDY" ], [ "HITCH", "written_by", "KEVIN BISCH" ], [ "PIE IN THE SKY", "has_genre", "COMEDY" ], [ "PIE IN THE SKY", "starred_actors", "JOSH CHARLES" ], [ "THREESOME", "has_genre", "COMEDY" ], [ "THREESOME", "has_tags", "COMEDY" ], [ "THREESOME", "starred_actors", "JOSH CHARLES" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 10045, BD-R 398, LOST HIGHWAY 22121, LUST FOR LIFE 20417, NIGHTWATCH 34619, NORMAN CORWIN 28554, PATRICIA ARQUETTE 14254, RICHARD CONDON 29773, THE MANCHURIAN CANDIDATE 24811, THRILLER src, edge_attr, dst 398, has_genre, 24811 398, has_tags, 28554 398, release_year, 14259 398, starred_actors, 28554 22121, has_tags, 10045 22121, written_by, 34619 20417, has_genre, 24811 20417, release_year, 14259 20417, starred_actors, 28554 29773, has_genre, 24811 29773, has_tags, 10045 29773, has_tags, 24811 29773, written_by, 14254 Question: How are NORMAN CORWIN, PATRICIA ARQUETTE, and RICHARD CONDON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "NORMAN CORWIN", "PATRICIA ARQUETTE", "RICHARD CONDON" ], "valid_edges": [ [ "LOST HIGHWAY", "has_genre", "THRILLER" ], [ "LOST HIGHWAY", "has_tags", "PATRICIA ARQUETTE" ], [ "LOST HIGHWAY", "release_year", "1997" ], [ "LOST HIGHWAY", "starred_actors", "PATRICIA ARQUETTE" ], [ "LUST FOR LIFE", "has_tags", "BD-R" ], [ "LUST FOR LIFE", "written_by", "NORMAN CORWIN" ], [ "NIGHTWATCH", "has_genre", "THRILLER" ], [ "NIGHTWATCH", "release_year", "1997" ], [ "NIGHTWATCH", "starred_actors", "PATRICIA ARQUETTE" ], [ "THE MANCHURIAN CANDIDATE", "has_genre", "THRILLER" ], [ "THE MANCHURIAN CANDIDATE", "has_tags", "BD-R" ], [ "THE MANCHURIAN CANDIDATE", "has_tags", "THRILLER" ], [ "THE MANCHURIAN CANDIDATE", "written_by", "RICHARD CONDON" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39289, ACTION 34158, AMERICAN YAKUZA 39730, CHUCK LOGAN 9711, HOMEFRONT 5005, JAMES GARNER 36694, JOHN ALLEN NELSON 40018, SUNSET 10952, TANK src, edge_attr, dst 34158, has_genre, 39289 34158, written_by, 36694 9711, has_genre, 39289 9711, written_by, 39730 40018, has_genre, 39289 40018, starred_actors, 5005 10952, has_genre, 39289 10952, starred_actors, 5005 Question: For what reason are CHUCK LOGAN, JAMES GARNER, and JOHN ALLEN NELSON associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHUCK LOGAN", "JAMES GARNER", "JOHN ALLEN NELSON" ], "valid_edges": [ [ "AMERICAN YAKUZA", "has_genre", "ACTION" ], [ "AMERICAN YAKUZA", "written_by", "JOHN ALLEN NELSON" ], [ "HOMEFRONT", "has_genre", "ACTION" ], [ "HOMEFRONT", "written_by", "CHUCK LOGAN" ], [ "SUNSET", "has_genre", "ACTION" ], [ "SUNSET", "starred_actors", "JAMES GARNER" ], [ "TANK", "has_genre", "ACTION" ], [ "TANK", "starred_actors", "JAMES GARNER" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 28175, ANDRÉS MUSCHIETTI 19888, ANNA THOMAS 36403, EL NORTE 31648, FRIGHT NIGHT 5870, HORROR 29898, MAMA 37497, NATIONAL FILM REGISTRY 27643, PLANET OF THE APES 28729, REMAKE 18518, RODDY MCDOWALL 8623, THE LEGEND OF HELL HOUSE src, edge_attr, dst 36403, has_tags, 37497 36403, written_by, 19888 31648, has_genre, 5870 31648, has_tags, 28729 31648, has_tags, 18518 31648, starred_actors, 18518 29898, directed_by, 28175 29898, has_genre, 5870 29898, has_tags, 5870 29898, written_by, 28175 27643, has_tags, 37497 27643, has_tags, 28729 27643, starred_actors, 18518 8623, has_genre, 5870 8623, has_tags, 18518 8623, starred_actors, 18518 Question: How are ANDRÉS MUSCHIETTI, ANNA THOMAS, and RODDY MCDOWALL related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANDRÉS MUSCHIETTI", "ANNA THOMAS", "RODDY MCDOWALL" ], "valid_edges": [ [ "EL NORTE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "EL NORTE", "written_by", "ANNA THOMAS" ], [ "FRIGHT NIGHT", "has_genre", "HORROR" ], [ "FRIGHT NIGHT", "has_tags", "REMAKE" ], [ "FRIGHT NIGHT", "has_tags", "RODDY MCDOWALL" ], [ "FRIGHT NIGHT", "starred_actors", "RODDY MCDOWALL" ], [ "MAMA", "directed_by", "ANDRÉS MUSCHIETTI" ], [ "MAMA", "has_genre", "HORROR" ], [ "MAMA", "has_tags", "HORROR" ], [ "MAMA", "written_by", "ANDRÉS MUSCHIETTI" ], [ "PLANET OF THE APES", "has_tags", "NATIONAL FILM REGISTRY" ], [ "PLANET OF THE APES", "has_tags", "REMAKE" ], [ "PLANET OF THE APES", "starred_actors", "RODDY MCDOWALL" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "RODDY MCDOWALL" ], [ "THE LEGEND OF HELL HOUSE", "starred_actors", "RODDY MCDOWALL" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36212, DRAMA 29176, FOUR FRIENDS 26579, ISABEL JEWELL 15908, JODI THELEN 18688, MARKED WOMAN 37681, OMAR NAIM 19685, THE FINAL CUT src, edge_attr, dst 29176, has_genre, 36212 29176, starred_actors, 15908 18688, has_genre, 36212 18688, starred_actors, 26579 19685, directed_by, 37681 19685, has_genre, 36212 19685, written_by, 37681 Question: In what context are ISABEL JEWELL, JODI THELEN, and OMAR NAIM connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ISABEL JEWELL", "JODI THELEN", "OMAR NAIM" ], "valid_edges": [ [ "FOUR FRIENDS", "has_genre", "DRAMA" ], [ "FOUR FRIENDS", "starred_actors", "JODI THELEN" ], [ "MARKED WOMAN", "has_genre", "DRAMA" ], [ "MARKED WOMAN", "starred_actors", "ISABEL JEWELL" ], [ "THE FINAL CUT", "directed_by", "OMAR NAIM" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "written_by", "OMAR NAIM" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30463, COMEDY 27897, DOCTOR DOLITTLE 7982, PLASTIC 18159, SAMANTHA EGGAR 28213, SEBASTIAN DE SOUZA 10940, THE LOVE BUG 29169, VOLKSWAGEN src, edge_attr, dst 27897, has_genre, 30463 27897, starred_actors, 18159 7982, has_genre, 30463 7982, starred_actors, 28213 10940, has_genre, 30463 10940, has_tags, 29169 Question: For what reason are SAMANTHA EGGAR, SEBASTIAN DE SOUZA, and VOLKSWAGEN associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "SAMANTHA EGGAR", "SEBASTIAN DE SOUZA", "VOLKSWAGEN" ], "valid_edges": [ [ "DOCTOR DOLITTLE", "has_genre", "COMEDY" ], [ "DOCTOR DOLITTLE", "starred_actors", "SAMANTHA EGGAR" ], [ "PLASTIC", "has_genre", "COMEDY" ], [ "PLASTIC", "starred_actors", "SEBASTIAN DE SOUZA" ], [ "THE LOVE BUG", "has_genre", "COMEDY" ], [ "THE LOVE BUG", "has_tags", "VOLKSWAGEN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 27879, 8 MILE 37548, A COUNTESS FROM HONG KONG 23328, APPALOOSA 10516, BANG BANG YOU'RE DEAD 16969, BETWEEN STRANGERS 28723, BLOODY SUNDAY 16230, BROKEN WINGS 33360, CANDY 33362, CARLITO'S WAY 33387, CITY OF GOD 6116, CYPHER 9641, DIRTY PRETTY THINGS 12628, EASTERN PROMISES 14926, EQUILIBRIUM 11422, FAR FROM HEAVEN 17400, GANGS OF NEW YORK 33545, HART'S WAR 23081, HEAVEN 25271, IN THIS WORLD 978, INFERNAL AFFAIRS 18277, JOHN HILLCOAT 21474, MARLON BRANDO 25269, NINE LIVES 14744, PEOPLE I KNOW 13081, R 32512, RAISING VICTOR VARGAS 4523, RED DRAGON 1749, SOPHIA LOREN 33414, SWEET SIXTEEN 23906, TENSE 35551, THE GODFATHER 12614, THE PIANIST 22294, THE PROPHECY 27029, THE PROPOSITION 20850, THE QUIET AMERICAN 15562, THE ROAD 26916, VIGGO MORTENSEN src, edge_attr, dst 4310, has_tags, 13081 4310, release_year, 35935 9408, has_tags, 13081 9408, release_year, 35935 27879, has_tags, 13081 27879, release_year, 35935 37548, starred_actors, 21474 37548, starred_actors, 1749 23328, has_tags, 13081 23328, has_tags, 26916 10516, has_tags, 13081 10516, release_year, 35935 16969, release_year, 35935 16969, starred_actors, 1749 28723, has_tags, 13081 28723, release_year, 35935 16230, has_tags, 13081 16230, release_year, 35935 33360, has_tags, 13081 33360, starred_actors, 21474 33362, has_tags, 13081 33362, has_tags, 26916 33387, has_tags, 13081 33387, release_year, 35935 6116, has_tags, 13081 6116, release_year, 35935 9641, has_tags, 13081 9641, release_year, 35935 12628, has_tags, 13081 12628, has_tags, 23906 12628, has_tags, 26916 14926, has_tags, 13081 14926, release_year, 35935 11422, has_tags, 13081 11422, release_year, 35935 17400, has_tags, 13081 17400, release_year, 35935 33545, has_tags, 13081 33545, release_year, 35935 23081, has_tags, 13081 23081, release_year, 35935 25271, has_tags, 13081 25271, release_year, 35935 978, has_tags, 13081 978, release_year, 35935 25269, has_tags, 13081 25269, release_year, 35935 14744, has_tags, 13081 14744, release_year, 35935 32512, has_tags, 13081 32512, release_year, 35935 4523, has_tags, 13081 4523, release_year, 35935 33414, has_tags, 13081 33414, release_year, 35935 35551, has_tags, 21474 35551, has_tags, 13081 35551, starred_actors, 21474 12614, has_tags, 13081 12614, release_year, 35935 22294, has_tags, 13081 22294, has_tags, 26916 27029, directed_by, 18277 27029, has_tags, 18277 27029, has_tags, 13081 20850, has_tags, 13081 20850, release_year, 35935 15562, directed_by, 18277 15562, has_tags, 18277 15562, has_tags, 23906 15562, has_tags, 26916 15562, starred_actors, 26916 Question: How are A COUNTESS FROM HONG KONG, IN THIS WORLD, and THE ROAD related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A COUNTESS FROM HONG KONG", "IN THIS WORLD", "THE ROAD" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_tags", "R" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "R" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 MILE", "has_tags", "R" ], [ "8 MILE", "release_year", "2002" ], [ "A COUNTESS FROM HONG KONG", "starred_actors", "MARLON BRANDO" ], [ "A COUNTESS FROM HONG KONG", "starred_actors", "SOPHIA LOREN" ], [ "APPALOOSA", "has_tags", "R" ], [ "APPALOOSA", "has_tags", "VIGGO MORTENSEN" ], [ "BANG BANG YOU'RE DEAD", "has_tags", "R" ], [ "BANG BANG YOU'RE DEAD", "release_year", "2002" ], [ "BETWEEN STRANGERS", "release_year", "2002" ], [ "BETWEEN STRANGERS", "starred_actors", "SOPHIA LOREN" ], [ "BLOODY SUNDAY", "has_tags", "R" ], [ "BLOODY SUNDAY", "release_year", "2002" ], [ "BROKEN WINGS", "has_tags", "R" ], [ "BROKEN WINGS", "release_year", "2002" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "starred_actors", "MARLON BRANDO" ], [ "CARLITO'S WAY", "has_tags", "R" ], [ "CARLITO'S WAY", "has_tags", "VIGGO MORTENSEN" ], [ "CITY OF GOD", "has_tags", "R" ], [ "CITY OF GOD", "release_year", "2002" ], [ "CYPHER", "has_tags", "R" ], [ "CYPHER", "release_year", "2002" ], [ "DIRTY PRETTY THINGS", "has_tags", "R" ], [ "DIRTY PRETTY THINGS", "release_year", "2002" ], [ "EASTERN PROMISES", "has_tags", "R" ], [ "EASTERN PROMISES", "has_tags", "TENSE" ], [ "EASTERN PROMISES", "has_tags", "VIGGO MORTENSEN" ], [ "EQUILIBRIUM", "has_tags", "R" ], [ "EQUILIBRIUM", "release_year", "2002" ], [ "FAR FROM HEAVEN", "has_tags", "R" ], [ "FAR FROM HEAVEN", "release_year", "2002" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "HART'S WAR", "has_tags", "R" ], [ "HART'S WAR", "release_year", "2002" ], [ "HEAVEN", "has_tags", "R" ], [ "HEAVEN", "release_year", "2002" ], [ "IN THIS WORLD", "has_tags", "R" ], [ "IN THIS WORLD", "release_year", "2002" ], [ "INFERNAL AFFAIRS", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "release_year", "2002" ], [ "NINE LIVES", "has_tags", "R" ], [ "NINE LIVES", "release_year", "2002" ], [ "PEOPLE I KNOW", "has_tags", "R" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "RAISING VICTOR VARGAS", "has_tags", "R" ], [ "RAISING VICTOR VARGAS", "release_year", "2002" ], [ "RED DRAGON", "has_tags", "R" ], [ "RED DRAGON", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_tags", "R" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "THE GODFATHER", "has_tags", "MARLON BRANDO" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "starred_actors", "MARLON BRANDO" ], [ "THE PIANIST", "has_tags", "R" ], [ "THE PIANIST", "release_year", "2002" ], [ "THE PROPHECY", "has_tags", "R" ], [ "THE PROPHECY", "has_tags", "VIGGO MORTENSEN" ], [ "THE PROPOSITION", "directed_by", "JOHN HILLCOAT" ], [ "THE PROPOSITION", "has_tags", "JOHN HILLCOAT" ], [ "THE PROPOSITION", "has_tags", "R" ], [ "THE QUIET AMERICAN", "has_tags", "R" ], [ "THE QUIET AMERICAN", "release_year", "2002" ], [ "THE ROAD", "directed_by", "JOHN HILLCOAT" ], [ "THE ROAD", "has_tags", "JOHN HILLCOAT" ], [ "THE ROAD", "has_tags", "TENSE" ], [ "THE ROAD", "has_tags", "VIGGO MORTENSEN" ], [ "THE ROAD", "starred_actors", "VIGGO MORTENSEN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 7411, ATSUYA UKI 36031, CENCOROLL 36874, JAPANESE 14772, KING KONG ESCAPES 11279, MIE HAMA 6722, THE TEMPTATION OF ST. TONY 8683, VEIKO ÕUNPUU src, edge_attr, dst 36031, directed_by, 7411 36031, in_language, 36874 36031, release_year, 27261 36031, written_by, 7411 14772, has_tags, 36874 14772, in_language, 36874 14772, starred_actors, 11279 6722, directed_by, 8683 6722, release_year, 27261 6722, written_by, 8683 Question: In what context are ATSUYA UKI, MIE HAMA, and VEIKO ÕUNPUU connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ATSUYA UKI", "MIE HAMA", "VEIKO ÕUNPUU" ], "valid_edges": [ [ "CENCOROLL", "directed_by", "ATSUYA UKI" ], [ "CENCOROLL", "in_language", "JAPANESE" ], [ "CENCOROLL", "release_year", "2009" ], [ "CENCOROLL", "written_by", "ATSUYA UKI" ], [ "KING KONG ESCAPES", "has_tags", "JAPANESE" ], [ "KING KONG ESCAPES", "in_language", "JAPANESE" ], [ "KING KONG ESCAPES", "starred_actors", "MIE HAMA" ], [ "THE TEMPTATION OF ST. TONY", "directed_by", "VEIKO ÕUNPUU" ], [ "THE TEMPTATION OF ST. TONY", "release_year", "2009" ], [ "THE TEMPTATION OF ST. TONY", "written_by", "VEIKO ÕUNPUU" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 12501, A COMPLETE HISTORY OF MY SEXUAL FAILURES 37725, A FILM UNFINISHED 25969, ALIEN RAIDERS 15162, AMERICAN TEEN 10045, BD-R 21206, BETWEEN THE FOLDS 36248, BURDEN OF DREAMS 31264, CAVE OF FORGOTTEN DREAMS 1930, CHELSEA ON THE ROCKS 14657, CSNY/DÉJÀ VU 12841, DOCUMENTARY 17682, EXAMINED LIFE 21393, FIEND WITHOUT A FACE 36306, FOOD, INC. 17291, I.O.U.S.A. 12892, LET'S MAKE MONEY 14834, MAN ON WIRE 23408, OF TIME AND THE CITY 28248, PAGEANT 18482, PRIMARY 24066, REEL INJUN 26777, REMBRANDT'S J'ACCUSE 10160, STANLEY KUBRICK'S BOXES 20580, STONEWALL UPRISING 24721, THAT'S ENTERTAINMENT! III 31138, THAT'S ENTERTAINMENT, PART II 38592, THE BEACHES OF AGNÈS 10103, THE COOL SCHOOL 33467, THE END OF AMERICA 25520, THE END OF POVERTY? 34736, THE ENDLESS SUMMER 2448, THE FORGOTTEN WOMAN 19165, THE LAST PLAY AT SHEA 29471, THE QUEEN AND I 15823, THE RECRUITER 735, THE REVISIONARIES 22610, THE SOVIET STORY 9266, THE TIMES OF HARVEY MILK 28674, TREK NATION 12757, TYSON 10212, UNMISTAKEN CHILD 3016, WALTZ WITH BASHIR 31247, WHERE IN THE WORLD IS OSAMA BIN LADEN? 19574, WISHFUL DRINKING src, edge_attr, dst 12501, has_genre, 12841 12501, release_year, 26762 37725, has_genre, 12841 37725, has_tags, 10045 25969, release_year, 26762 15162, has_genre, 12841 15162, release_year, 26762 21206, has_genre, 12841 21206, release_year, 26762 36248, has_genre, 12841 36248, has_tags, 10045 31264, has_genre, 12841 31264, has_tags, 10045 31264, has_tags, 12841 1930, has_genre, 12841 1930, release_year, 26762 14657, has_genre, 12841 14657, release_year, 26762 17682, has_genre, 12841 17682, release_year, 26762 21393, has_tags, 10045 36306, has_genre, 12841 36306, has_tags, 12841 36306, release_year, 26762 17291, has_genre, 12841 17291, has_tags, 12841 17291, release_year, 26762 12892, has_genre, 12841 12892, has_tags, 12841 12892, release_year, 26762 14834, has_genre, 12841 14834, has_tags, 12841 14834, release_year, 26762 23408, has_genre, 12841 23408, release_year, 26762 28248, has_genre, 12841 28248, release_year, 26762 18482, has_genre, 12841 18482, has_tags, 10045 24066, has_genre, 12841 24066, has_tags, 10045 26777, has_genre, 12841 26777, release_year, 26762 10160, has_genre, 12841 10160, release_year, 26762 20580, has_genre, 12841 20580, has_tags, 10045 24721, has_genre, 12841 24721, has_tags, 10045 31138, has_genre, 12841 31138, has_tags, 10045 38592, has_genre, 12841 38592, release_year, 26762 10103, has_genre, 12841 10103, release_year, 26762 33467, has_genre, 12841 33467, release_year, 26762 25520, has_genre, 12841 25520, release_year, 26762 34736, has_genre, 12841 34736, has_tags, 10045 2448, has_genre, 12841 2448, release_year, 26762 19165, has_genre, 12841 19165, has_tags, 10045 29471, has_genre, 12841 29471, release_year, 26762 15823, has_genre, 12841 15823, release_year, 26762 735, has_genre, 12841 735, has_tags, 10045 22610, has_genre, 12841 22610, release_year, 26762 9266, has_genre, 12841 9266, has_tags, 10045 9266, has_tags, 12841 28674, has_genre, 12841 28674, has_tags, 10045 12757, has_genre, 12841 12757, release_year, 26762 10212, has_genre, 12841 10212, release_year, 26762 3016, has_genre, 12841 3016, has_tags, 12841 3016, release_year, 26762 31247, has_genre, 12841 31247, release_year, 26762 19574, has_genre, 12841 Question: For what reason are ALIEN RAIDERS, FIEND WITHOUT A FACE, and WISHFUL DRINKING associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALIEN RAIDERS", "FIEND WITHOUT A FACE", "WISHFUL DRINKING" ], "valid_edges": [ [ "A COMPLETE HISTORY OF MY SEXUAL FAILURES", "has_genre", "DOCUMENTARY" ], [ "A COMPLETE HISTORY OF MY SEXUAL FAILURES", "release_year", "2008" ], [ "A FILM UNFINISHED", "has_genre", "DOCUMENTARY" ], [ "A FILM UNFINISHED", "has_tags", "BD-R" ], [ "ALIEN RAIDERS", "release_year", "2008" ], [ "AMERICAN TEEN", "has_genre", "DOCUMENTARY" ], [ "AMERICAN TEEN", "release_year", "2008" ], [ "BETWEEN THE FOLDS", "has_genre", "DOCUMENTARY" ], [ "BETWEEN THE FOLDS", "release_year", "2008" ], [ "BURDEN OF DREAMS", "has_genre", "DOCUMENTARY" ], [ "BURDEN OF DREAMS", "has_tags", "BD-R" ], [ "CAVE OF FORGOTTEN DREAMS", "has_genre", "DOCUMENTARY" ], [ "CAVE OF FORGOTTEN DREAMS", "has_tags", "BD-R" ], [ "CAVE OF FORGOTTEN DREAMS", "has_tags", "DOCUMENTARY" ], [ "CHELSEA ON THE ROCKS", "has_genre", "DOCUMENTARY" ], [ "CHELSEA ON THE ROCKS", "release_year", "2008" ], [ "CSNY/DÉJÀ VU", "has_genre", "DOCUMENTARY" ], [ "CSNY/DÉJÀ VU", "release_year", "2008" ], [ "EXAMINED LIFE", "has_genre", "DOCUMENTARY" ], [ "EXAMINED LIFE", "release_year", "2008" ], [ "FIEND WITHOUT A FACE", "has_tags", "BD-R" ], [ "FOOD, INC.", "has_genre", "DOCUMENTARY" ], [ "FOOD, INC.", "has_tags", "DOCUMENTARY" ], [ "FOOD, INC.", "release_year", "2008" ], [ "I.O.U.S.A.", "has_genre", "DOCUMENTARY" ], [ "I.O.U.S.A.", "has_tags", "DOCUMENTARY" ], [ "I.O.U.S.A.", "release_year", "2008" ], [ "LET'S MAKE MONEY", "has_genre", "DOCUMENTARY" ], [ "LET'S MAKE MONEY", "has_tags", "DOCUMENTARY" ], [ "LET'S MAKE MONEY", "release_year", "2008" ], [ "MAN ON WIRE", "has_genre", "DOCUMENTARY" ], [ "MAN ON WIRE", "has_tags", "DOCUMENTARY" ], [ "MAN ON WIRE", "release_year", "2008" ], [ "OF TIME AND THE CITY", "has_genre", "DOCUMENTARY" ], [ "OF TIME AND THE CITY", "release_year", "2008" ], [ "PAGEANT", "has_genre", "DOCUMENTARY" ], [ "PAGEANT", "release_year", "2008" ], [ "PRIMARY", "has_genre", "DOCUMENTARY" ], [ "PRIMARY", "has_tags", "BD-R" ], [ "REEL INJUN", "has_genre", "DOCUMENTARY" ], [ "REEL INJUN", "has_tags", "BD-R" ], [ "REMBRANDT'S J'ACCUSE", "has_genre", "DOCUMENTARY" ], [ "REMBRANDT'S J'ACCUSE", "release_year", "2008" ], [ "STANLEY KUBRICK'S BOXES", "has_genre", "DOCUMENTARY" ], [ "STANLEY KUBRICK'S BOXES", "release_year", "2008" ], [ "STONEWALL UPRISING", "has_genre", "DOCUMENTARY" ], [ "STONEWALL UPRISING", "has_tags", "BD-R" ], [ "THAT'S ENTERTAINMENT! III", "has_genre", "DOCUMENTARY" ], [ "THAT'S ENTERTAINMENT! III", "has_tags", "BD-R" ], [ "THAT'S ENTERTAINMENT, PART II", "has_genre", "DOCUMENTARY" ], [ "THAT'S ENTERTAINMENT, PART II", "has_tags", "BD-R" ], [ "THE BEACHES OF AGNÈS", "has_genre", "DOCUMENTARY" ], [ "THE BEACHES OF AGNÈS", "release_year", "2008" ], [ "THE COOL SCHOOL", "has_genre", "DOCUMENTARY" ], [ "THE COOL SCHOOL", "release_year", "2008" ], [ "THE END OF AMERICA", "has_genre", "DOCUMENTARY" ], [ "THE END OF AMERICA", "release_year", "2008" ], [ "THE END OF POVERTY?", "has_genre", "DOCUMENTARY" ], [ "THE END OF POVERTY?", "release_year", "2008" ], [ "THE ENDLESS SUMMER", "has_genre", "DOCUMENTARY" ], [ "THE ENDLESS SUMMER", "has_tags", "BD-R" ], [ "THE FORGOTTEN WOMAN", "has_genre", "DOCUMENTARY" ], [ "THE FORGOTTEN WOMAN", "release_year", "2008" ], [ "THE LAST PLAY AT SHEA", "has_genre", "DOCUMENTARY" ], [ "THE LAST PLAY AT SHEA", "has_tags", "BD-R" ], [ "THE QUEEN AND I", "has_genre", "DOCUMENTARY" ], [ "THE QUEEN AND I", "release_year", "2008" ], [ "THE RECRUITER", "has_genre", "DOCUMENTARY" ], [ "THE RECRUITER", "release_year", "2008" ], [ "THE REVISIONARIES", "has_genre", "DOCUMENTARY" ], [ "THE REVISIONARIES", "has_tags", "BD-R" ], [ "THE SOVIET STORY", "has_genre", "DOCUMENTARY" ], [ "THE SOVIET STORY", "release_year", "2008" ], [ "THE TIMES OF HARVEY MILK", "has_genre", "DOCUMENTARY" ], [ "THE TIMES OF HARVEY MILK", "has_tags", "BD-R" ], [ "THE TIMES OF HARVEY MILK", "has_tags", "DOCUMENTARY" ], [ "TREK NATION", "has_genre", "DOCUMENTARY" ], [ "TREK NATION", "has_tags", "BD-R" ], [ "TYSON", "has_genre", "DOCUMENTARY" ], [ "TYSON", "release_year", "2008" ], [ "UNMISTAKEN CHILD", "has_genre", "DOCUMENTARY" ], [ "UNMISTAKEN CHILD", "release_year", "2008" ], [ "WALTZ WITH BASHIR", "has_genre", "DOCUMENTARY" ], [ "WALTZ WITH BASHIR", "has_tags", "DOCUMENTARY" ], [ "WALTZ WITH BASHIR", "release_year", "2008" ], [ "WHERE IN THE WORLD IS OSAMA BIN LADEN?", "has_genre", "DOCUMENTARY" ], [ "WHERE IN THE WORLD IS OSAMA BIN LADEN?", "release_year", "2008" ], [ "WISHFUL DRINKING", "has_genre", "DOCUMENTARY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 35845, 2006 39257, BARNYARD 19500, FIRST SNOW 6012, FRENCH 7930, GUY PEARCE 10034, L.A. CONFIDENTIAL 8530, MARTIN LASALLE 29071, MEMENTO 913, NOTHING TO LOSE 29693, PICKPOCKET 13081, R 18757, REVENGE 13567, STEVE OEDEKERK 16219, STORY 19351, THE COUNT OF MONTE CRISTO src, edge_attr, dst 39257, directed_by, 13567 39257, release_year, 35845 39257, written_by, 13567 19500, release_year, 35845 19500, starred_actors, 7930 10034, has_tags, 7930 10034, has_tags, 13081 10034, has_tags, 16219 10034, release_year, 14259 10034, starred_actors, 7930 29071, has_tags, 7930 29071, has_tags, 13081 29071, has_tags, 18757 29071, has_tags, 16219 29071, starred_actors, 7930 913, directed_by, 13567 913, has_tags, 13567 913, release_year, 14259 913, written_by, 13567 29693, in_language, 6012 29693, starred_actors, 8530 19351, has_tags, 7930 19351, has_tags, 18757 19351, has_tags, 16219 19351, in_language, 6012 19351, starred_actors, 7930 Question: How are GUY PEARCE, MARTIN LASALLE, and STEVE OEDEKERK related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GUY PEARCE", "MARTIN LASALLE", "STEVE OEDEKERK" ], "valid_edges": [ [ "BARNYARD", "directed_by", "STEVE OEDEKERK" ], [ "BARNYARD", "release_year", "2006" ], [ "BARNYARD", "written_by", "STEVE OEDEKERK" ], [ "FIRST SNOW", "release_year", "2006" ], [ "FIRST SNOW", "starred_actors", "GUY PEARCE" ], [ "L.A. CONFIDENTIAL", "has_tags", "GUY PEARCE" ], [ "L.A. CONFIDENTIAL", "has_tags", "R" ], [ "L.A. CONFIDENTIAL", "has_tags", "STORY" ], [ "L.A. CONFIDENTIAL", "release_year", "1997" ], [ "L.A. CONFIDENTIAL", "starred_actors", "GUY PEARCE" ], [ "MEMENTO", "has_tags", "GUY PEARCE" ], [ "MEMENTO", "has_tags", "R" ], [ "MEMENTO", "has_tags", "REVENGE" ], [ "MEMENTO", "has_tags", "STORY" ], [ "MEMENTO", "starred_actors", "GUY PEARCE" ], [ "NOTHING TO LOSE", "directed_by", "STEVE OEDEKERK" ], [ "NOTHING TO LOSE", "has_tags", "STEVE OEDEKERK" ], [ "NOTHING TO LOSE", "release_year", "1997" ], [ "NOTHING TO LOSE", "written_by", "STEVE OEDEKERK" ], [ "PICKPOCKET", "in_language", "FRENCH" ], [ "PICKPOCKET", "starred_actors", "MARTIN LASALLE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "GUY PEARCE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "REVENGE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "STORY" ], [ "THE COUNT OF MONTE CRISTO", "in_language", "FRENCH" ], [ "THE COUNT OF MONTE CRISTO", "starred_actors", "GUY PEARCE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36522, 1934 19407, 8½ 38636, A BRIEF VACATION 37315, A BRONX TALE 16090, A FIVE STAR LIFE 21572, ACCATTONE 21413, AMARCORD 34352, AN AVERAGE LITTLE MAN 39876, ANNIE 6309, BABY TAKE A BOW 12954, BEAR'S KISS 27226, BORN TO BE BAD 35916, BREAD AND CHOCOLATE 34243, BRIGHT EYES 13164, BROADWAY 8442, CABIRIA 33711, CAESAR MUST DIE 5140, CHRIS PRATT 33774, CINEMA PARADISO 19510, CLEOPATRA 30463, COMEDY 37882, DAYS AND CLOUDS 30126, DEATH IN VENICE 29309, DELIVERY MAN 31550, DILLINGER IS DEAD 36212, DRAMA 37267, DREAMGIRLS 5924, EROS 31799, EVA 23387, EVERYBODY'S FINE 23071, EVERYBODY'S WOMAN 409, FARINELLI 26507, FIORILE 32706, FIRST LOVE 15161, FORSAKING ALL OTHERS 34091, FROM THE CLOUDS TO THE RESISTANCE 15135, GINGER AND FRED 33338, I GIORNI CONTATI 17344, I VITELLONI 37734, IDENTIFICATION OF A WOMAN 33242, IL GRIDO 5921, IMITATION OF LIFE 38662, IN THE NAME OF THE LAW 31900, INCANTATO 24167, INFERNO 37110, INVESTIGATION OF A CITIZEN ABOVE SUSPICION 16200, ITALIAN 20654, JAMIE FOXX 15012, JARHEAD 38160, JOURNEY TO ITALY 7754, JULIA AND JULIA 18699, JULIET OF THE SPIRITS 38326, L'ECLISSE 25104, LA DOLCE VITA 32844, LA NOTTE 20913, LA STRADA 19966, LE PLAISIR 14601, LES MISÉRABLES 24419, LIFE IS BEAUTIFUL 28130, LITTLE MISS MARKER 34628, MALÈNA 4193, MANHATTAN MELODRAMA 32293, MAX OPHÜLS 34611, ME AND YOU 34359, MELISSA P. 19216, MID-AUGUST LUNCH 7050, MONEYBALL 22845, MUSIC 24593, MUSICAL 32993, MY BROTHER IS AN ONLY CHILD 39242, NOW AND FOREVER 4435, OF HUMAN BONDAGE 17528, ONCE UPON A TIME IN AMERICA 32186, ONE MAN UP 9036, PAISAN 1197, PASSION OF LOVE 3781, QUO VADIS, BABY? 35746, REALITY 21719, ROMANZO CRIMINALE 29931, ROME, OPEN CITY 35586, SAHARA 40001, SCENT OF A WOMAN 26687, SENSO 25009, SHUN LI AND THE POET 15777, STORY OF A LOVE AFFAIR 15312, STRANGER ON THE PROWL 37032, STROMBOLI 38027, SUNFLOWER 26790, SWEPT AWAY 23395, TERRAFERMA 36088, THAT NIGHT IN VARENNES 27310, THE AGE OF INNOCENCE 4157, THE BEST MAN 36932, THE CAIMAN 14219, THE CHILDREN ARE WATCHING US 39333, THE CLAIRVOYANT 2356, THE CONFORMIST 19351, THE COUNT OF MONTE CRISTO 10860, THE DAMNED 32637, THE EARRINGS OF MADAME DE... 27253, THE FIRST BEAUTIFUL THING 6723, THE FLOWER IN HIS MOUTH 11668, THE GOSPEL ACCORDING TO ST. MATTHEW 35165, THE ITALIAN 8435, THE KEYS TO THE HOUSE 28107, THE LAST KISS 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 19600, THE MISSING STAR 18105, THE MOMENT OF TRUTH 15155, THE NIGHT OF THE SHOOTING STARS 12999, THE ORGANIZER 3967, THE OVERCOAT 23084, THE PAINTED VEIL 242, THE PRIVATE LIFE OF DON JUAN 7592, THE RECKLESS MOMENT 18274, THE ROSE TATTOO 40069, THE SCARLET EMPRESS 7725, THE SOLITUDE OF PRIME NUMBERS 19294, THE SOLOIST 20293, THE WEDDING DIRECTOR 34649, THE WONDERS 19429, TONI 32079, ULYSSES 17093, UNFAIR COMPETITION 31942, VARIETY LIGHTS 28264, VESNA VA VELOCE 27749, WALKING, WALKING 4325, WE ALL LOVED EACH OTHER SO MUCH 35511, WE HAVE A POPE src, edge_attr, dst 19407, has_genre, 36212 19407, in_language, 16200 38636, has_genre, 36212 38636, in_language, 16200 37315, has_genre, 36212 37315, has_tags, 16200 37315, in_language, 16200 16090, has_genre, 36212 16090, in_language, 16200 21572, has_genre, 36212 21572, in_language, 16200 21413, has_genre, 36212 21413, in_language, 16200 34352, has_genre, 36212 34352, in_language, 16200 39876, has_genre, 30463 39876, has_genre, 36212 39876, has_tags, 13164 39876, has_tags, 24593 39876, starred_actors, 20654 6309, has_genre, 36212 6309, release_year, 36522 12954, has_genre, 36212 12954, in_language, 16200 27226, has_genre, 36212 27226, release_year, 36522 35916, has_genre, 36212 35916, in_language, 16200 34243, has_genre, 36212 34243, release_year, 36522 8442, has_genre, 36212 8442, in_language, 16200 33711, has_genre, 36212 33711, in_language, 16200 33774, has_genre, 36212 33774, has_tags, 16200 33774, in_language, 16200 19510, has_genre, 36212 19510, release_year, 36522 37882, has_genre, 36212 37882, in_language, 16200 30126, has_genre, 36212 30126, in_language, 16200 29309, has_genre, 30463 29309, has_genre, 36212 29309, has_tags, 36212 29309, starred_actors, 5140 31550, has_genre, 36212 31550, in_language, 16200 37267, has_genre, 36212 37267, has_genre, 22845 37267, has_genre, 24593 37267, has_tags, 13164 37267, has_tags, 20654 37267, has_tags, 24593 37267, starred_actors, 20654 5924, has_genre, 36212 5924, in_language, 16200 31799, has_genre, 36212 31799, in_language, 16200 23387, has_genre, 36212 23387, in_language, 16200 23071, directed_by, 32293 23071, has_genre, 36212 23071, in_language, 16200 23071, release_year, 36522 23071, written_by, 32293 409, has_genre, 36212 409, in_language, 16200 26507, has_genre, 36212 26507, in_language, 16200 32706, has_genre, 36212 32706, in_language, 16200 15161, has_genre, 36212 15161, release_year, 36522 34091, has_genre, 36212 34091, in_language, 16200 15135, has_genre, 36212 15135, in_language, 16200 33338, has_genre, 36212 33338, in_language, 16200 17344, has_genre, 36212 17344, has_tags, 16200 17344, in_language, 16200 37734, has_genre, 36212 37734, in_language, 16200 33242, has_genre, 36212 33242, in_language, 16200 5921, has_genre, 36212 5921, release_year, 36522 38662, has_genre, 36212 38662, in_language, 16200 31900, has_genre, 36212 31900, in_language, 16200 24167, has_genre, 36212 24167, in_language, 16200 37110, has_genre, 36212 37110, in_language, 16200 15012, has_genre, 36212 15012, has_tags, 20654 15012, starred_actors, 20654 38160, has_genre, 36212 38160, in_language, 16200 7754, has_genre, 36212 7754, in_language, 16200 18699, has_genre, 36212 18699, has_tags, 16200 18699, in_language, 16200 38326, has_genre, 36212 38326, in_language, 16200 25104, has_genre, 36212 25104, has_tags, 16200 25104, in_language, 16200 32844, has_genre, 36212 32844, in_language, 16200 20913, has_genre, 36212 20913, has_tags, 16200 20913, in_language, 16200 19966, directed_by, 32293 19966, has_genre, 36212 19966, has_tags, 32293 19966, written_by, 32293 14601, has_genre, 36212 14601, release_year, 36522 24419, has_genre, 36212 24419, has_tags, 16200 24419, in_language, 16200 28130, has_genre, 36212 28130, release_year, 36522 34628, has_genre, 36212 34628, has_tags, 36212 34628, has_tags, 16200 34628, in_language, 16200 4193, has_genre, 36212 4193, release_year, 36522 34611, has_genre, 36212 34611, in_language, 16200 34359, has_genre, 36212 34359, in_language, 16200 19216, has_genre, 36212 19216, in_language, 16200 7050, has_genre, 36212 7050, has_tags, 5140 7050, has_tags, 36212 32993, has_genre, 36212 32993, in_language, 16200 39242, has_genre, 36212 39242, release_year, 36522 4435, has_genre, 36212 4435, release_year, 36522 17528, has_genre, 36212 17528, in_language, 16200 32186, has_genre, 36212 32186, in_language, 16200 9036, has_genre, 36212 9036, in_language, 16200 1197, has_genre, 36212 1197, in_language, 16200 3781, has_genre, 36212 3781, in_language, 16200 35746, has_genre, 36212 35746, in_language, 16200 21719, has_genre, 36212 21719, in_language, 16200 29931, has_genre, 36212 29931, in_language, 16200 35586, has_genre, 36212 35586, in_language, 16200 40001, has_genre, 36212 40001, has_tags, 36212 40001, in_language, 16200 26687, has_genre, 36212 26687, in_language, 16200 25009, has_genre, 36212 25009, in_language, 16200 15777, has_genre, 36212 15777, in_language, 16200 15312, has_genre, 36212 15312, in_language, 16200 37032, has_genre, 36212 37032, in_language, 16200 38027, has_genre, 36212 38027, in_language, 16200 26790, has_genre, 36212 26790, in_language, 16200 23395, has_genre, 36212 23395, in_language, 16200 36088, has_genre, 36212 36088, in_language, 16200 27310, has_genre, 36212 27310, release_year, 36522 4157, has_genre, 36212 4157, in_language, 16200 36932, has_genre, 36212 36932, in_language, 16200 14219, has_genre, 36212 14219, in_language, 16200 39333, has_genre, 36212 39333, release_year, 36522 2356, has_genre, 36212 2356, in_language, 16200 19351, has_genre, 36212 19351, release_year, 36522 10860, has_genre, 36212 10860, in_language, 16200 32637, directed_by, 32293 32637, has_genre, 36212 32637, has_tags, 32293 32637, written_by, 32293 27253, has_genre, 36212 27253, in_language, 16200 6723, has_genre, 36212 6723, in_language, 16200 11668, has_genre, 36212 11668, in_language, 16200 35165, has_genre, 36212 35165, in_language, 16200 8435, has_genre, 36212 8435, in_language, 16200 28107, has_genre, 36212 28107, in_language, 16200 28217, has_genre, 36212 28217, in_language, 16200 19600, has_genre, 36212 19600, in_language, 16200 18105, has_genre, 36212 18105, in_language, 16200 15155, has_genre, 36212 15155, in_language, 16200 12999, has_genre, 36212 12999, in_language, 16200 3967, has_genre, 36212 3967, in_language, 16200 23084, has_genre, 36212 23084, release_year, 36522 242, has_genre, 36212 242, release_year, 36522 7592, directed_by, 32293 7592, has_genre, 36212 18274, has_genre, 36212 18274, in_language, 16200 40069, has_genre, 36212 40069, release_year, 36522 7725, has_genre, 36212 7725, in_language, 16200 19294, has_genre, 36212 19294, has_genre, 22845 19294, has_tags, 20654 19294, starred_actors, 20654 20293, has_genre, 36212 20293, in_language, 16200 34649, has_genre, 36212 34649, in_language, 16200 19429, has_genre, 36212 19429, in_language, 16200 32079, has_genre, 36212 32079, in_language, 16200 17093, has_genre, 36212 17093, in_language, 16200 31942, has_genre, 36212 31942, in_language, 16200 28264, has_genre, 36212 28264, has_tags, 36212 28264, has_tags, 16200 28264, in_language, 16200 27749, has_genre, 36212 27749, in_language, 16200 4325, has_genre, 36212 4325, in_language, 16200 35511, has_genre, 36212 35511, has_tags, 16200 35511, in_language, 16200 Question: In what context are CHRIS PRATT, EVERYBODY'S WOMAN, and JAMIE FOXX connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHRIS PRATT", "EVERYBODY'S WOMAN", "JAMIE FOXX" ], "valid_edges": [ [ "8½", "has_genre", "DRAMA" ], [ "8½", "in_language", "ITALIAN" ], [ "A BRIEF VACATION", "has_genre", "DRAMA" ], [ "A BRIEF VACATION", "in_language", "ITALIAN" ], [ "A BRONX TALE", "has_genre", "DRAMA" ], [ "A BRONX TALE", "has_tags", "ITALIAN" ], [ "A BRONX TALE", "in_language", "ITALIAN" ], [ "A FIVE STAR LIFE", "has_genre", "DRAMA" ], [ "A FIVE STAR LIFE", "in_language", "ITALIAN" ], [ "ACCATTONE", "has_genre", "DRAMA" ], [ "ACCATTONE", "in_language", "ITALIAN" ], [ "AMARCORD", "has_genre", "DRAMA" ], [ "AMARCORD", "in_language", "ITALIAN" ], [ "AN AVERAGE LITTLE MAN", "has_genre", "DRAMA" ], [ "AN AVERAGE LITTLE MAN", "in_language", "ITALIAN" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "has_tags", "BROADWAY" ], [ "ANNIE", "has_tags", "MUSICAL" ], [ "ANNIE", "starred_actors", "JAMIE FOXX" ], [ "BABY TAKE A BOW", "has_genre", "DRAMA" ], [ "BABY TAKE A BOW", "release_year", "1934" ], [ "BEAR'S KISS", "has_genre", "DRAMA" ], [ "BEAR'S KISS", "in_language", "ITALIAN" ], [ "BORN TO BE BAD", "has_genre", "DRAMA" ], [ "BORN TO BE BAD", "release_year", "1934" ], [ "BREAD AND CHOCOLATE", "has_genre", "DRAMA" ], [ "BREAD AND CHOCOLATE", "in_language", "ITALIAN" ], [ "BRIGHT EYES", "has_genre", "DRAMA" ], [ "BRIGHT EYES", "release_year", "1934" ], [ "CABIRIA", "has_genre", "DRAMA" ], [ "CABIRIA", "in_language", "ITALIAN" ], [ "CAESAR MUST DIE", "has_genre", "DRAMA" ], [ "CAESAR MUST DIE", "in_language", "ITALIAN" ], [ "CINEMA PARADISO", "has_genre", "DRAMA" ], [ "CINEMA PARADISO", "has_tags", "ITALIAN" ], [ "CINEMA PARADISO", "in_language", "ITALIAN" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "1934" ], [ "DAYS AND CLOUDS", "has_genre", "DRAMA" ], [ "DAYS AND CLOUDS", "in_language", "ITALIAN" ], [ "DEATH IN VENICE", "has_genre", "DRAMA" ], [ "DEATH IN VENICE", "in_language", "ITALIAN" ], [ "DELIVERY MAN", "has_genre", "COMEDY" ], [ "DELIVERY MAN", "has_genre", "DRAMA" ], [ "DELIVERY MAN", "has_tags", "DRAMA" ], [ "DELIVERY MAN", "starred_actors", "CHRIS PRATT" ], [ "DILLINGER IS DEAD", "has_genre", "DRAMA" ], [ "DILLINGER IS DEAD", "in_language", "ITALIAN" ], [ "DREAMGIRLS", "has_genre", "DRAMA" ], [ "DREAMGIRLS", "has_genre", "MUSIC" ], [ "DREAMGIRLS", "has_genre", "MUSICAL" ], [ "DREAMGIRLS", "has_tags", "BROADWAY" ], [ "DREAMGIRLS", "has_tags", "JAMIE FOXX" ], [ "DREAMGIRLS", "has_tags", "MUSICAL" ], [ "DREAMGIRLS", "starred_actors", "JAMIE FOXX" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "in_language", "ITALIAN" ], [ "EVA", "has_genre", "DRAMA" ], [ "EVA", "in_language", "ITALIAN" ], [ "EVERYBODY'S FINE", "has_genre", "DRAMA" ], [ "EVERYBODY'S FINE", "in_language", "ITALIAN" ], [ "EVERYBODY'S WOMAN", "directed_by", "MAX OPHÜLS" ], [ "EVERYBODY'S WOMAN", "has_genre", "DRAMA" ], [ "EVERYBODY'S WOMAN", "in_language", "ITALIAN" ], [ "EVERYBODY'S WOMAN", "release_year", "1934" ], [ "EVERYBODY'S WOMAN", "written_by", "MAX OPHÜLS" ], [ "FARINELLI", "has_genre", "DRAMA" ], [ "FARINELLI", "in_language", "ITALIAN" ], [ "FIORILE", "has_genre", "DRAMA" ], [ "FIORILE", "in_language", "ITALIAN" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "in_language", "ITALIAN" ], [ "FORSAKING ALL OTHERS", "has_genre", "DRAMA" ], [ "FORSAKING ALL OTHERS", "release_year", "1934" ], [ "FROM THE CLOUDS TO THE RESISTANCE", "has_genre", "DRAMA" ], [ "FROM THE CLOUDS TO THE RESISTANCE", "in_language", "ITALIAN" ], [ "GINGER AND FRED", "has_genre", "DRAMA" ], [ "GINGER AND FRED", "in_language", "ITALIAN" ], [ "I GIORNI CONTATI", "has_genre", "DRAMA" ], [ "I GIORNI CONTATI", "in_language", "ITALIAN" ], [ "I VITELLONI", "has_genre", "DRAMA" ], [ "I VITELLONI", "has_tags", "ITALIAN" ], [ "I VITELLONI", "in_language", "ITALIAN" ], [ "IDENTIFICATION OF A WOMAN", "has_genre", "DRAMA" ], [ "IDENTIFICATION OF A WOMAN", "in_language", "ITALIAN" ], [ "IL GRIDO", "has_genre", "DRAMA" ], [ "IL GRIDO", "in_language", "ITALIAN" ], [ "IMITATION OF LIFE", "has_genre", "DRAMA" ], [ "IMITATION OF LIFE", "release_year", "1934" ], [ "IN THE NAME OF THE LAW", "has_genre", "DRAMA" ], [ "IN THE NAME OF THE LAW", "in_language", "ITALIAN" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "in_language", "ITALIAN" ], [ "INFERNO", "has_genre", "DRAMA" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "INVESTIGATION OF A CITIZEN ABOVE SUSPICION", "has_genre", "DRAMA" ], [ "INVESTIGATION OF A CITIZEN ABOVE SUSPICION", "in_language", "ITALIAN" ], [ "JARHEAD", "has_genre", "DRAMA" ], [ "JARHEAD", "has_tags", "JAMIE FOXX" ], [ "JARHEAD", "starred_actors", "JAMIE FOXX" ], [ "JOURNEY TO ITALY", "has_genre", "DRAMA" ], [ "JOURNEY TO ITALY", "in_language", "ITALIAN" ], [ "JULIA AND JULIA", "has_genre", "DRAMA" ], [ "JULIA AND JULIA", "in_language", "ITALIAN" ], [ "JULIET OF THE SPIRITS", "has_genre", "DRAMA" ], [ "JULIET OF THE SPIRITS", "has_tags", "ITALIAN" ], [ "JULIET OF THE SPIRITS", "in_language", "ITALIAN" ], [ "L'ECLISSE", "has_genre", "DRAMA" ], [ "L'ECLISSE", "in_language", "ITALIAN" ], [ "LA DOLCE VITA", "has_genre", "DRAMA" ], [ "LA DOLCE VITA", "has_tags", "ITALIAN" ], [ "LA DOLCE VITA", "in_language", "ITALIAN" ], [ "LA NOTTE", "has_genre", "DRAMA" ], [ "LA NOTTE", "in_language", "ITALIAN" ], [ "LA STRADA", "has_genre", "DRAMA" ], [ "LA STRADA", "has_tags", "ITALIAN" ], [ "LA STRADA", "in_language", "ITALIAN" ], [ "LE PLAISIR", "directed_by", "MAX OPHÜLS" ], [ "LE PLAISIR", "has_genre", "DRAMA" ], [ "LE PLAISIR", "has_tags", "MAX OPHÜLS" ], [ "LE PLAISIR", "written_by", "MAX OPHÜLS" ], [ "LES MISÉRABLES", "has_genre", "DRAMA" ], [ "LES MISÉRABLES", "release_year", "1934" ], [ "LIFE IS BEAUTIFUL", "has_genre", "DRAMA" ], [ "LIFE IS BEAUTIFUL", "has_tags", "ITALIAN" ], [ "LIFE IS BEAUTIFUL", "in_language", "ITALIAN" ], [ "LITTLE MISS MARKER", "has_genre", "DRAMA" ], [ "LITTLE MISS MARKER", "release_year", "1934" ], [ "MALÈNA", "has_genre", "DRAMA" ], [ "MALÈNA", "has_tags", "DRAMA" ], [ "MALÈNA", "has_tags", "ITALIAN" ], [ "MALÈNA", "in_language", "ITALIAN" ], [ "MANHATTAN MELODRAMA", "has_genre", "DRAMA" ], [ "MANHATTAN MELODRAMA", "release_year", "1934" ], [ "ME AND YOU", "has_genre", "DRAMA" ], [ "ME AND YOU", "in_language", "ITALIAN" ], [ "MELISSA P.", "has_genre", "DRAMA" ], [ "MELISSA P.", "in_language", "ITALIAN" ], [ "MID-AUGUST LUNCH", "has_genre", "DRAMA" ], [ "MID-AUGUST LUNCH", "in_language", "ITALIAN" ], [ "MONEYBALL", "has_genre", "DRAMA" ], [ "MONEYBALL", "has_tags", "CHRIS PRATT" ], [ "MONEYBALL", "has_tags", "DRAMA" ], [ "MY BROTHER IS AN ONLY CHILD", "has_genre", "DRAMA" ], [ "MY BROTHER IS AN ONLY CHILD", "in_language", "ITALIAN" ], [ "NOW AND FOREVER", "has_genre", "DRAMA" ], [ "NOW AND FOREVER", "release_year", "1934" ], [ "OF HUMAN BONDAGE", "has_genre", "DRAMA" ], [ "OF HUMAN BONDAGE", "release_year", "1934" ], [ "ONCE UPON A TIME IN AMERICA", "has_genre", "DRAMA" ], [ "ONCE UPON A TIME IN AMERICA", "in_language", "ITALIAN" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "in_language", "ITALIAN" ], [ "PAISAN", "has_genre", "DRAMA" ], [ "PAISAN", "in_language", "ITALIAN" ], [ "PASSION OF LOVE", "has_genre", "DRAMA" ], [ "PASSION OF LOVE", "in_language", "ITALIAN" ], [ "QUO VADIS, BABY?", "has_genre", "DRAMA" ], [ "QUO VADIS, BABY?", "in_language", "ITALIAN" ], [ "REALITY", "has_genre", "DRAMA" ], [ "REALITY", "in_language", "ITALIAN" ], [ "ROMANZO CRIMINALE", "has_genre", "DRAMA" ], [ "ROMANZO CRIMINALE", "in_language", "ITALIAN" ], [ "ROME, OPEN CITY", "has_genre", "DRAMA" ], [ "ROME, OPEN CITY", "in_language", "ITALIAN" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "in_language", "ITALIAN" ], [ "SCENT OF A WOMAN", "has_genre", "DRAMA" ], [ "SCENT OF A WOMAN", "has_tags", "DRAMA" ], [ "SCENT OF A WOMAN", "in_language", "ITALIAN" ], [ "SENSO", "has_genre", "DRAMA" ], [ "SENSO", "in_language", "ITALIAN" ], [ "SHUN LI AND THE POET", "has_genre", "DRAMA" ], [ "SHUN LI AND THE POET", "in_language", "ITALIAN" ], [ "STORY OF A LOVE AFFAIR", "has_genre", "DRAMA" ], [ "STORY OF A LOVE AFFAIR", "in_language", "ITALIAN" ], [ "STRANGER ON THE PROWL", "has_genre", "DRAMA" ], [ "STRANGER ON THE PROWL", "in_language", "ITALIAN" ], [ "STROMBOLI", "has_genre", "DRAMA" ], [ "STROMBOLI", "in_language", "ITALIAN" ], [ "SUNFLOWER", "has_genre", "DRAMA" ], [ "SUNFLOWER", "in_language", "ITALIAN" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "in_language", "ITALIAN" ], [ "TERRAFERMA", "has_genre", "DRAMA" ], [ "TERRAFERMA", "in_language", "ITALIAN" ], [ "THAT NIGHT IN VARENNES", "has_genre", "DRAMA" ], [ "THAT NIGHT IN VARENNES", "in_language", "ITALIAN" ], [ "THE AGE OF INNOCENCE", "has_genre", "DRAMA" ], [ "THE AGE OF INNOCENCE", "release_year", "1934" ], [ "THE BEST MAN", "has_genre", "DRAMA" ], [ "THE BEST MAN", "in_language", "ITALIAN" ], [ "THE CAIMAN", "has_genre", "DRAMA" ], [ "THE CAIMAN", "in_language", "ITALIAN" ], [ "THE CHILDREN ARE WATCHING US", "has_genre", "DRAMA" ], [ "THE CHILDREN ARE WATCHING US", "in_language", "ITALIAN" ], [ "THE CLAIRVOYANT", "has_genre", "DRAMA" ], [ "THE CLAIRVOYANT", "release_year", "1934" ], [ "THE CONFORMIST", "has_genre", "DRAMA" ], [ "THE CONFORMIST", "in_language", "ITALIAN" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "1934" ], [ "THE DAMNED", "has_genre", "DRAMA" ], [ "THE DAMNED", "in_language", "ITALIAN" ], [ "THE EARRINGS OF MADAME DE...", "directed_by", "MAX OPHÜLS" ], [ "THE EARRINGS OF MADAME DE...", "has_genre", "DRAMA" ], [ "THE EARRINGS OF MADAME DE...", "has_tags", "MAX OPHÜLS" ], [ "THE EARRINGS OF MADAME DE...", "written_by", "MAX OPHÜLS" ], [ "THE FIRST BEAUTIFUL THING", "has_genre", "DRAMA" ], [ "THE FIRST BEAUTIFUL THING", "in_language", "ITALIAN" ], [ "THE FLOWER IN HIS MOUTH", "has_genre", "DRAMA" ], [ "THE FLOWER IN HIS MOUTH", "in_language", "ITALIAN" ], [ "THE GOSPEL ACCORDING TO ST. MATTHEW", "has_genre", "DRAMA" ], [ "THE GOSPEL ACCORDING TO ST. MATTHEW", "in_language", "ITALIAN" ], [ "THE ITALIAN", "has_genre", "DRAMA" ], [ "THE ITALIAN", "in_language", "ITALIAN" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "in_language", "ITALIAN" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "in_language", "ITALIAN" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "in_language", "ITALIAN" ], [ "THE MISSING STAR", "has_genre", "DRAMA" ], [ "THE MISSING STAR", "in_language", "ITALIAN" ], [ "THE MOMENT OF TRUTH", "has_genre", "DRAMA" ], [ "THE MOMENT OF TRUTH", "in_language", "ITALIAN" ], [ "THE NIGHT OF THE SHOOTING STARS", "has_genre", "DRAMA" ], [ "THE NIGHT OF THE SHOOTING STARS", "in_language", "ITALIAN" ], [ "THE ORGANIZER", "has_genre", "DRAMA" ], [ "THE ORGANIZER", "in_language", "ITALIAN" ], [ "THE OVERCOAT", "has_genre", "DRAMA" ], [ "THE OVERCOAT", "in_language", "ITALIAN" ], [ "THE PAINTED VEIL", "has_genre", "DRAMA" ], [ "THE PAINTED VEIL", "release_year", "1934" ], [ "THE PRIVATE LIFE OF DON JUAN", "has_genre", "DRAMA" ], [ "THE PRIVATE LIFE OF DON JUAN", "release_year", "1934" ], [ "THE RECKLESS MOMENT", "directed_by", "MAX OPHÜLS" ], [ "THE RECKLESS MOMENT", "has_genre", "DRAMA" ], [ "THE ROSE TATTOO", "has_genre", "DRAMA" ], [ "THE ROSE TATTOO", "in_language", "ITALIAN" ], [ "THE SCARLET EMPRESS", "has_genre", "DRAMA" ], [ "THE SCARLET EMPRESS", "release_year", "1934" ], [ "THE SOLITUDE OF PRIME NUMBERS", "has_genre", "DRAMA" ], [ "THE SOLITUDE OF PRIME NUMBERS", "in_language", "ITALIAN" ], [ "THE SOLOIST", "has_genre", "DRAMA" ], [ "THE SOLOIST", "has_genre", "MUSIC" ], [ "THE SOLOIST", "has_tags", "JAMIE FOXX" ], [ "THE SOLOIST", "starred_actors", "JAMIE FOXX" ], [ "THE WEDDING DIRECTOR", "has_genre", "DRAMA" ], [ "THE WEDDING DIRECTOR", "in_language", "ITALIAN" ], [ "THE WONDERS", "has_genre", "DRAMA" ], [ "THE WONDERS", "in_language", "ITALIAN" ], [ "TONI", "has_genre", "DRAMA" ], [ "TONI", "in_language", "ITALIAN" ], [ "ULYSSES", "has_genre", "DRAMA" ], [ "ULYSSES", "in_language", "ITALIAN" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "in_language", "ITALIAN" ], [ "VARIETY LIGHTS", "has_genre", "DRAMA" ], [ "VARIETY LIGHTS", "in_language", "ITALIAN" ], [ "VESNA VA VELOCE", "has_genre", "DRAMA" ], [ "VESNA VA VELOCE", "has_tags", "DRAMA" ], [ "VESNA VA VELOCE", "has_tags", "ITALIAN" ], [ "VESNA VA VELOCE", "in_language", "ITALIAN" ], [ "WALKING, WALKING", "has_genre", "DRAMA" ], [ "WALKING, WALKING", "in_language", "ITALIAN" ], [ "WE ALL LOVED EACH OTHER SO MUCH", "has_genre", "DRAMA" ], [ "WE ALL LOVED EACH OTHER SO MUCH", "in_language", "ITALIAN" ], [ "WE HAVE A POPE", "has_genre", "DRAMA" ], [ "WE HAVE A POPE", "has_tags", "ITALIAN" ], [ "WE HAVE A POPE", "in_language", "ITALIAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 14062, ALL THE BOYS LOVE MANDY LANE 6012, FRENCH 33456, HE LOVES ME... HE LOVES ME NOT 5870, HORROR 6894, JACK HANNAH 25761, JONATHAN LEVINE 8379, ROMANCE 6603, SEX IS COMEDY 19351, THE COUNT OF MONTE CRISTO 17409, TRICK OR TREAT 32933, WARM BODIES src, edge_attr, dst 14062, directed_by, 25761 14062, has_genre, 5870 14062, has_tags, 5870 33456, has_tags, 6012 33456, in_language, 6012 33456, release_year, 35935 8379, in_language, 6012 6603, in_language, 6012 6603, release_year, 35935 19351, in_language, 6012 19351, release_year, 35935 17409, directed_by, 6894 17409, has_genre, 5870 32933, directed_by, 25761 32933, has_genre, 8379 32933, has_tags, 25761 32933, has_tags, 8379 32933, written_by, 25761 Question: How are HE LOVES ME... HE LOVES ME NOT, JACK HANNAH, and JONATHAN LEVINE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HE LOVES ME... HE LOVES ME NOT", "JACK HANNAH", "JONATHAN LEVINE" ], "valid_edges": [ [ "ALL THE BOYS LOVE MANDY LANE", "directed_by", "JONATHAN LEVINE" ], [ "ALL THE BOYS LOVE MANDY LANE", "has_genre", "HORROR" ], [ "ALL THE BOYS LOVE MANDY LANE", "has_tags", "HORROR" ], [ "HE LOVES ME... HE LOVES ME NOT", "has_tags", "FRENCH" ], [ "HE LOVES ME... HE LOVES ME NOT", "in_language", "FRENCH" ], [ "HE LOVES ME... HE LOVES ME NOT", "release_year", "2002" ], [ "ROMANCE", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "THE COUNT OF MONTE CRISTO", "in_language", "FRENCH" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "2002" ], [ "TRICK OR TREAT", "directed_by", "JACK HANNAH" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "WARM BODIES", "directed_by", "JONATHAN LEVINE" ], [ "WARM BODIES", "has_genre", "ROMANCE" ], [ "WARM BODIES", "has_tags", "JONATHAN LEVINE" ], [ "WARM BODIES", "has_tags", "ROMANCE" ], [ "WARM BODIES", "written_by", "JONATHAN LEVINE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21950, 'R XMAS 2452, 13 ASSASSINS 13408, 2001 37484, 2004 33218, ABEL FERRARA 29800, ACE ATTORNEY 35189, ALL ABOUT LILY CHOU-CHOU 18598, APPLESEED 7908, AUDITION 2182, BLOOD AND BONES 5856, BLUE SPRING 6395, BLUES HARP 231, CASSHERN 38311, CHAOS 1930, CHELSEA ON THE ROCKS 26635, CROWS ZERO 5113, DEAD LEAVES 36380, DEAD OR ALIVE 5951, ELECTRIC DRAGON 80.000 V 12298, GOZU 2982, HALLOWEENTOWN HIGH 13409, HANA AND ALICE 12087, HOWL'S MOVING CASTLE 22330, HUSH! 4215, ICHI THE KILLER 13174, INFECTION 8164, IZO 36874, JAPANESE 15150, KAMIKAZE GIRLS 7892, LESSON OF THE EVIL 35621, MILLENNIUM ACTRESS 30532, MIND GAME 25709, NOBODY KNOWS 36326, ONE MISSED CALL 36532, OVER YOUR DEAD BODY 234, PEARL HARBOR 29748, PISTOL OPERA 13237, PULSE 29919, RAINY DOG 6260, SPIRITED AWAY 31842, SURVIVE STYLE 5+ 4651, TAKASHI MIIKE 38882, THE BIRD PEOPLE IN CHINA 23910, THE CITY OF LOST SOULS 24493, THE FUNERAL 11297, THE GREAT YOKAI WAR 786, THE GRUDGE 3644, THE PRINCESS BLADE 9554, THROW DOWN 28132, TONY TAKITANI 3137, VISITOR Q 12437, VITAL 29077, WASABI 25414, WATERBOYS 7762, YATTERMAN 34399, ZEBRAMAN src, edge_attr, dst 21950, directed_by, 33218 21950, release_year, 13408 21950, written_by, 33218 2452, directed_by, 4651 2452, has_tags, 4651 2452, in_language, 36874 29800, directed_by, 4651 29800, has_tags, 4651 29800, in_language, 36874 35189, in_language, 36874 35189, release_year, 13408 18598, in_language, 36874 18598, release_year, 37484 7908, directed_by, 4651 7908, has_tags, 4651 7908, in_language, 36874 2182, in_language, 36874 2182, release_year, 37484 5856, in_language, 36874 5856, release_year, 13408 6395, directed_by, 4651 6395, has_tags, 4651 6395, in_language, 36874 231, has_tags, 36874 231, in_language, 36874 231, release_year, 37484 38311, in_language, 36874 38311, release_year, 13408 1930, directed_by, 33218 1930, written_by, 33218 26635, directed_by, 4651 26635, has_tags, 4651 26635, in_language, 36874 5113, in_language, 36874 5113, release_year, 37484 36380, directed_by, 4651 36380, has_tags, 4651 36380, in_language, 36874 5951, in_language, 36874 5951, release_year, 13408 12298, directed_by, 4651 12298, has_tags, 4651 12298, in_language, 36874 2982, release_year, 37484 13409, in_language, 36874 13409, release_year, 37484 12087, in_language, 36874 12087, release_year, 37484 22330, in_language, 36874 22330, release_year, 13408 4215, directed_by, 4651 4215, has_tags, 4651 4215, in_language, 36874 4215, release_year, 13408 13174, in_language, 36874 13174, release_year, 37484 8164, directed_by, 4651 8164, has_tags, 4651 8164, in_language, 36874 8164, release_year, 37484 15150, has_tags, 36874 15150, in_language, 36874 15150, release_year, 37484 7892, directed_by, 4651 7892, in_language, 36874 7892, written_by, 4651 35621, in_language, 36874 35621, release_year, 13408 30532, in_language, 36874 30532, release_year, 37484 25709, in_language, 36874 25709, release_year, 37484 36326, directed_by, 4651 36326, in_language, 36874 36532, directed_by, 4651 36532, in_language, 36874 234, in_language, 36874 234, release_year, 13408 29748, in_language, 36874 29748, release_year, 13408 13237, has_tags, 36874 13237, in_language, 36874 13237, release_year, 13408 29919, directed_by, 4651 29919, has_tags, 4651 29919, in_language, 36874 6260, has_tags, 36874 6260, in_language, 36874 6260, release_year, 13408 31842, has_tags, 36874 31842, in_language, 36874 31842, release_year, 37484 38882, directed_by, 4651 38882, has_tags, 4651 38882, in_language, 36874 23910, directed_by, 4651 23910, has_tags, 4651 23910, in_language, 36874 24493, directed_by, 33218 24493, in_language, 36874 11297, directed_by, 4651 11297, has_tags, 4651 11297, in_language, 36874 11297, written_by, 4651 786, in_language, 36874 786, release_year, 37484 3644, in_language, 36874 3644, release_year, 13408 9554, in_language, 36874 9554, release_year, 37484 28132, in_language, 36874 28132, release_year, 37484 3137, directed_by, 4651 3137, has_tags, 4651 3137, in_language, 36874 3137, release_year, 13408 12437, in_language, 36874 12437, release_year, 37484 29077, in_language, 36874 29077, release_year, 13408 25414, in_language, 36874 25414, release_year, 13408 7762, directed_by, 4651 7762, in_language, 36874 34399, directed_by, 4651 34399, has_tags, 4651 34399, release_year, 37484 Question: For what reason are CHELSEA ON THE ROCKS, HALLOWEENTOWN HIGH, and ICHI THE KILLER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHELSEA ON THE ROCKS", "HALLOWEENTOWN HIGH", "ICHI THE KILLER" ], "valid_edges": [ [ "'R XMAS", "directed_by", "ABEL FERRARA" ], [ "'R XMAS", "release_year", "2001" ], [ "'R XMAS", "written_by", "ABEL FERRARA" ], [ "13 ASSASSINS", "directed_by", "TAKASHI MIIKE" ], [ "13 ASSASSINS", "has_tags", "TAKASHI MIIKE" ], [ "13 ASSASSINS", "in_language", "JAPANESE" ], [ "ACE ATTORNEY", "directed_by", "TAKASHI MIIKE" ], [ "ACE ATTORNEY", "has_tags", "TAKASHI MIIKE" ], [ "ACE ATTORNEY", "in_language", "JAPANESE" ], [ "ALL ABOUT LILY CHOU-CHOU", "in_language", "JAPANESE" ], [ "ALL ABOUT LILY CHOU-CHOU", "release_year", "2001" ], [ "APPLESEED", "in_language", "JAPANESE" ], [ "APPLESEED", "release_year", "2004" ], [ "AUDITION", "directed_by", "TAKASHI MIIKE" ], [ "AUDITION", "has_tags", "TAKASHI MIIKE" ], [ "AUDITION", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "release_year", "2004" ], [ "BLUE SPRING", "in_language", "JAPANESE" ], [ "BLUE SPRING", "release_year", "2001" ], [ "BLUES HARP", "directed_by", "TAKASHI MIIKE" ], [ "BLUES HARP", "has_tags", "TAKASHI MIIKE" ], [ "BLUES HARP", "in_language", "JAPANESE" ], [ "CASSHERN", "has_tags", "JAPANESE" ], [ "CASSHERN", "in_language", "JAPANESE" ], [ "CASSHERN", "release_year", "2004" ], [ "CHAOS", "in_language", "JAPANESE" ], [ "CHAOS", "release_year", "2001" ], [ "CHELSEA ON THE ROCKS", "directed_by", "ABEL FERRARA" ], [ "CHELSEA ON THE ROCKS", "written_by", "ABEL FERRARA" ], [ "CROWS ZERO", "directed_by", "TAKASHI MIIKE" ], [ "CROWS ZERO", "has_tags", "TAKASHI MIIKE" ], [ "CROWS ZERO", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "release_year", "2004" ], [ "DEAD OR ALIVE", "directed_by", "TAKASHI MIIKE" ], [ "DEAD OR ALIVE", "has_tags", "TAKASHI MIIKE" ], [ "DEAD OR ALIVE", "in_language", "JAPANESE" ], [ "ELECTRIC DRAGON 80.000 V", "in_language", "JAPANESE" ], [ "ELECTRIC DRAGON 80.000 V", "release_year", "2001" ], [ "GOZU", "directed_by", "TAKASHI MIIKE" ], [ "GOZU", "has_tags", "TAKASHI MIIKE" ], [ "GOZU", "in_language", "JAPANESE" ], [ "HALLOWEENTOWN HIGH", "release_year", "2004" ], [ "HANA AND ALICE", "in_language", "JAPANESE" ], [ "HANA AND ALICE", "release_year", "2004" ], [ "HOWL'S MOVING CASTLE", "in_language", "JAPANESE" ], [ "HOWL'S MOVING CASTLE", "release_year", "2004" ], [ "HUSH!", "in_language", "JAPANESE" ], [ "HUSH!", "release_year", "2001" ], [ "ICHI THE KILLER", "directed_by", "TAKASHI MIIKE" ], [ "ICHI THE KILLER", "has_tags", "TAKASHI MIIKE" ], [ "ICHI THE KILLER", "in_language", "JAPANESE" ], [ "ICHI THE KILLER", "release_year", "2001" ], [ "INFECTION", "in_language", "JAPANESE" ], [ "INFECTION", "release_year", "2004" ], [ "IZO", "directed_by", "TAKASHI MIIKE" ], [ "IZO", "has_tags", "TAKASHI MIIKE" ], [ "IZO", "in_language", "JAPANESE" ], [ "IZO", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "has_tags", "JAPANESE" ], [ "KAMIKAZE GIRLS", "in_language", "JAPANESE" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "LESSON OF THE EVIL", "directed_by", "TAKASHI MIIKE" ], [ "LESSON OF THE EVIL", "in_language", "JAPANESE" ], [ "LESSON OF THE EVIL", "written_by", "TAKASHI MIIKE" ], [ "MILLENNIUM ACTRESS", "in_language", "JAPANESE" ], [ "MILLENNIUM ACTRESS", "release_year", "2001" ], [ "MIND GAME", "in_language", "JAPANESE" ], [ "MIND GAME", "release_year", "2004" ], [ "NOBODY KNOWS", "in_language", "JAPANESE" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "ONE MISSED CALL", "directed_by", "TAKASHI MIIKE" ], [ "ONE MISSED CALL", "in_language", "JAPANESE" ], [ "OVER YOUR DEAD BODY", "directed_by", "TAKASHI MIIKE" ], [ "OVER YOUR DEAD BODY", "in_language", "JAPANESE" ], [ "PEARL HARBOR", "in_language", "JAPANESE" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PISTOL OPERA", "in_language", "JAPANESE" ], [ "PISTOL OPERA", "release_year", "2001" ], [ "PULSE", "has_tags", "JAPANESE" ], [ "PULSE", "in_language", "JAPANESE" ], [ "PULSE", "release_year", "2001" ], [ "RAINY DOG", "directed_by", "TAKASHI MIIKE" ], [ "RAINY DOG", "has_tags", "TAKASHI MIIKE" ], [ "RAINY DOG", "in_language", "JAPANESE" ], [ "SPIRITED AWAY", "has_tags", "JAPANESE" ], [ "SPIRITED AWAY", "in_language", "JAPANESE" ], [ "SPIRITED AWAY", "release_year", "2001" ], [ "SURVIVE STYLE 5+", "has_tags", "JAPANESE" ], [ "SURVIVE STYLE 5+", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "release_year", "2004" ], [ "THE BIRD PEOPLE IN CHINA", "directed_by", "TAKASHI MIIKE" ], [ "THE BIRD PEOPLE IN CHINA", "has_tags", "TAKASHI MIIKE" ], [ "THE BIRD PEOPLE IN CHINA", "in_language", "JAPANESE" ], [ "THE CITY OF LOST SOULS", "directed_by", "TAKASHI MIIKE" ], [ "THE CITY OF LOST SOULS", "has_tags", "TAKASHI MIIKE" ], [ "THE CITY OF LOST SOULS", "in_language", "JAPANESE" ], [ "THE FUNERAL", "directed_by", "ABEL FERRARA" ], [ "THE FUNERAL", "in_language", "JAPANESE" ], [ "THE GREAT YOKAI WAR", "directed_by", "TAKASHI MIIKE" ], [ "THE GREAT YOKAI WAR", "has_tags", "TAKASHI MIIKE" ], [ "THE GREAT YOKAI WAR", "in_language", "JAPANESE" ], [ "THE GREAT YOKAI WAR", "written_by", "TAKASHI MIIKE" ], [ "THE GRUDGE", "in_language", "JAPANESE" ], [ "THE GRUDGE", "release_year", "2004" ], [ "THE PRINCESS BLADE", "in_language", "JAPANESE" ], [ "THE PRINCESS BLADE", "release_year", "2001" ], [ "THROW DOWN", "in_language", "JAPANESE" ], [ "THROW DOWN", "release_year", "2004" ], [ "TONY TAKITANI", "in_language", "JAPANESE" ], [ "TONY TAKITANI", "release_year", "2004" ], [ "VISITOR Q", "directed_by", "TAKASHI MIIKE" ], [ "VISITOR Q", "has_tags", "TAKASHI MIIKE" ], [ "VISITOR Q", "in_language", "JAPANESE" ], [ "VISITOR Q", "release_year", "2001" ], [ "VITAL", "in_language", "JAPANESE" ], [ "VITAL", "release_year", "2004" ], [ "WASABI", "in_language", "JAPANESE" ], [ "WASABI", "release_year", "2001" ], [ "WATERBOYS", "in_language", "JAPANESE" ], [ "WATERBOYS", "release_year", "2001" ], [ "YATTERMAN", "directed_by", "TAKASHI MIIKE" ], [ "YATTERMAN", "in_language", "JAPANESE" ], [ "ZEBRAMAN", "directed_by", "TAKASHI MIIKE" ], [ "ZEBRAMAN", "has_tags", "TAKASHI MIIKE" ], [ "ZEBRAMAN", "release_year", "2004" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18616, AMY ADAMS 15948, CALLING DR. GILLESPIE 36212, DRAMA 18908, DROP DEAD GORGEOUS 20422, HAROLD S. BUCQUET 22867, MICHAEL PATRICK JANN 27316, ROBERT LORENZ 17451, TROUBLE WITH THE CURVE src, edge_attr, dst 15948, directed_by, 20422 15948, has_genre, 36212 18908, directed_by, 22867 18908, has_tags, 18616 17451, directed_by, 27316 17451, has_genre, 36212 17451, has_tags, 18616 Question: In what context are HAROLD S. BUCQUET, MICHAEL PATRICK JANN, and ROBERT LORENZ connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HAROLD S. BUCQUET", "MICHAEL PATRICK JANN", "ROBERT LORENZ" ], "valid_edges": [ [ "CALLING DR. GILLESPIE", "directed_by", "HAROLD S. BUCQUET" ], [ "CALLING DR. GILLESPIE", "has_genre", "DRAMA" ], [ "DROP DEAD GORGEOUS", "directed_by", "MICHAEL PATRICK JANN" ], [ "DROP DEAD GORGEOUS", "has_tags", "AMY ADAMS" ], [ "TROUBLE WITH THE CURVE", "directed_by", "ROBERT LORENZ" ], [ "TROUBLE WITH THE CURVE", "has_genre", "DRAMA" ], [ "TROUBLE WITH THE CURVE", "has_tags", "AMY ADAMS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 16150, A CHRISTMAS STORY 12827, ACQUA E SAPONE 12144, BAD BOYS 7761, CAT AND DOG 4608, CLASS 30463, COMEDY 33111, COPPER MOUNTAIN 30019, CROSSROADS 38648, CURSE OF THE PINK PANTHER 1284, D.C. CAB 10162, DARK HABITS 4737, DEAL OF THE CENTURY 21558, DOCTOR DETROIT 36212, DRAMA 25445, EASY MONEY 38216, EDUCATING RITA 28117, ERÉNDIRA 10648, EVEN COWGIRLS GET THE BLUES 29593, GET CRAZY 15135, GINGER AND FRED 9054, GO FOR IT 12555, GOING BERSERK 1937, HANNAH AND HER SISTERS 2625, JOYSTICKS 29879, LOCAL HERO 37927, LOSIN' IT 39468, LOVESICK 29318, MALA NOCHE 31940, MAX DUGAN RETURNS 5699, MR. MOM 38932, MY TUTOR 36027, NATIONAL LAMPOON'S VACATION 4398, NOBODY'S FOOL 2654, NOTHING IN COMMON 20473, PEGGY SUE GOT MARRIED 31652, PRETTY IN PINK 4332, PRIVATE SCHOOL 23617, PROJECT A 14786, REUBEN, REUBEN 31054, RISKY BUSINESS 10066, ROMANTIC COMEDY 35586, SAHARA 9270, SEEMS LIKE OLD TIMES 37803, SHADOWS IN PARADISE 34888, SOMETHING WILD 19149, SPRING BREAK 32032, STRANGE BREW 10577, STROKER ACE 1328, TERMS OF ENDEARMENT 6667, THE BIG CHILL 4694, THE CREATURE WASN'T NICE 13316, THE DECLINE OF THE AMERICAN EMPIRE 33513, THE MAN WHO LOVED WOMEN 17006, THE MAN WITH TWO BRAINS 13058, THE SEX AND VIOLENCE FAMILY HOUR 30092, THE SURVIVORS 3640, TO BE OR NOT TO BE 37331, TO DIE FOR 18863, TRADING PLACES 19528, TWO OF A KIND 20647, VALLEY GIRL 25043, WALT CURTIS 30387, YELLOWBEARD src, edge_attr, dst 16150, has_genre, 30463 16150, release_year, 16055 12827, has_genre, 30463 12827, release_year, 16055 12144, has_genre, 30463 12144, has_genre, 36212 12144, has_tags, 30463 12144, release_year, 16055 7761, has_genre, 30463 7761, release_year, 16055 4608, has_genre, 30463 4608, has_genre, 36212 4608, release_year, 16055 33111, has_genre, 30463 33111, release_year, 16055 30019, has_genre, 30463 30019, has_genre, 36212 38648, has_genre, 30463 38648, release_year, 16055 1284, has_genre, 30463 1284, release_year, 16055 10162, has_genre, 30463 10162, release_year, 16055 4737, has_genre, 30463 4737, release_year, 16055 21558, has_genre, 30463 21558, release_year, 16055 25445, has_genre, 30463 25445, release_year, 16055 38216, has_genre, 30463 38216, has_genre, 36212 38216, release_year, 16055 28117, has_genre, 36212 28117, release_year, 16055 10648, has_genre, 30463 10648, has_genre, 36212 29593, has_genre, 30463 29593, release_year, 16055 15135, has_genre, 30463 15135, has_genre, 36212 9054, has_genre, 30463 9054, release_year, 16055 12555, has_genre, 30463 12555, has_tags, 30463 12555, release_year, 16055 1937, has_genre, 30463 1937, has_genre, 36212 1937, has_tags, 30463 2625, has_genre, 30463 2625, release_year, 16055 29879, has_genre, 30463 29879, has_genre, 36212 29879, release_year, 16055 37927, has_genre, 30463 37927, release_year, 16055 39468, has_genre, 30463 39468, release_year, 16055 29318, has_genre, 36212 29318, written_by, 25043 31940, has_genre, 30463 31940, has_genre, 36212 31940, release_year, 16055 5699, has_genre, 30463 5699, release_year, 16055 38932, has_genre, 30463 38932, release_year, 16055 36027, has_genre, 30463 36027, has_tags, 30463 36027, release_year, 16055 4398, has_genre, 30463 4398, has_genre, 36212 2654, has_genre, 30463 2654, has_genre, 36212 20473, has_genre, 30463 20473, has_genre, 36212 20473, has_tags, 36212 31652, has_genre, 30463 31652, has_genre, 36212 31652, has_tags, 30463 4332, has_genre, 30463 4332, release_year, 16055 23617, has_genre, 30463 23617, release_year, 16055 14786, has_genre, 30463 14786, has_genre, 36212 14786, release_year, 16055 31054, has_genre, 30463 31054, has_genre, 36212 31054, release_year, 16055 10066, has_genre, 30463 10066, release_year, 16055 35586, has_genre, 30463 35586, has_genre, 36212 35586, release_year, 16055 9270, has_genre, 30463 37803, has_genre, 30463 37803, has_genre, 36212 34888, has_genre, 30463 34888, has_genre, 36212 19149, has_genre, 30463 19149, release_year, 16055 32032, has_genre, 30463 32032, release_year, 16055 10577, has_genre, 30463 10577, release_year, 16055 1328, has_genre, 30463 1328, has_genre, 36212 1328, release_year, 16055 6667, has_genre, 30463 6667, has_genre, 36212 6667, release_year, 16055 4694, has_genre, 30463 4694, release_year, 16055 13316, has_genre, 30463 13316, has_genre, 36212 33513, has_genre, 30463 33513, has_genre, 36212 33513, release_year, 16055 17006, has_genre, 30463 17006, release_year, 16055 13058, has_genre, 30463 13058, release_year, 16055 30092, has_genre, 30463 30092, release_year, 16055 3640, has_genre, 30463 3640, has_tags, 30463 3640, release_year, 16055 37331, has_genre, 30463 37331, has_genre, 36212 18863, has_genre, 30463 18863, has_tags, 30463 18863, release_year, 16055 19528, has_genre, 30463 19528, release_year, 16055 20647, has_genre, 30463 20647, release_year, 16055 30387, has_genre, 30463 30387, release_year, 16055 Question: How are ERÉNDIRA, SEEMS LIKE OLD TIMES, and WALT CURTIS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ERÉNDIRA", "SEEMS LIKE OLD TIMES", "WALT CURTIS" ], "valid_edges": [ [ "A CHRISTMAS STORY", "has_genre", "COMEDY" ], [ "A CHRISTMAS STORY", "release_year", "1983" ], [ "ACQUA E SAPONE", "has_genre", "COMEDY" ], [ "ACQUA E SAPONE", "release_year", "1983" ], [ "BAD BOYS", "has_genre", "COMEDY" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_tags", "COMEDY" ], [ "BAD BOYS", "release_year", "1983" ], [ "CAT AND DOG", "has_genre", "COMEDY" ], [ "CAT AND DOG", "release_year", "1983" ], [ "CLASS", "has_genre", "COMEDY" ], [ "CLASS", "has_genre", "DRAMA" ], [ "CLASS", "release_year", "1983" ], [ "COPPER MOUNTAIN", "has_genre", "COMEDY" ], [ "COPPER MOUNTAIN", "release_year", "1983" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "DRAMA" ], [ "CURSE OF THE PINK PANTHER", "has_genre", "COMEDY" ], [ "CURSE OF THE PINK PANTHER", "release_year", "1983" ], [ "D.C. CAB", "has_genre", "COMEDY" ], [ "D.C. CAB", "release_year", "1983" ], [ "DARK HABITS", "has_genre", "COMEDY" ], [ "DARK HABITS", "release_year", "1983" ], [ "DEAL OF THE CENTURY", "has_genre", "COMEDY" ], [ "DEAL OF THE CENTURY", "release_year", "1983" ], [ "DOCTOR DETROIT", "has_genre", "COMEDY" ], [ "DOCTOR DETROIT", "release_year", "1983" ], [ "EASY MONEY", "has_genre", "COMEDY" ], [ "EASY MONEY", "release_year", "1983" ], [ "EDUCATING RITA", "has_genre", "COMEDY" ], [ "EDUCATING RITA", "has_genre", "DRAMA" ], [ "EDUCATING RITA", "release_year", "1983" ], [ "ERÉNDIRA", "has_genre", "DRAMA" ], [ "ERÉNDIRA", "release_year", "1983" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "COMEDY" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "DRAMA" ], [ "GET CRAZY", "has_genre", "COMEDY" ], [ "GET CRAZY", "release_year", "1983" ], [ "GINGER AND FRED", "has_genre", "COMEDY" ], [ "GINGER AND FRED", "has_genre", "DRAMA" ], [ "GO FOR IT", "has_genre", "COMEDY" ], [ "GO FOR IT", "release_year", "1983" ], [ "GOING BERSERK", "has_genre", "COMEDY" ], [ "GOING BERSERK", "has_tags", "COMEDY" ], [ "GOING BERSERK", "release_year", "1983" ], [ "HANNAH AND HER SISTERS", "has_genre", "COMEDY" ], [ "HANNAH AND HER SISTERS", "has_genre", "DRAMA" ], [ "HANNAH AND HER SISTERS", "has_tags", "COMEDY" ], [ "JOYSTICKS", "has_genre", "COMEDY" ], [ "JOYSTICKS", "release_year", "1983" ], [ "LOCAL HERO", "has_genre", "COMEDY" ], [ "LOCAL HERO", "has_genre", "DRAMA" ], [ "LOCAL HERO", "release_year", "1983" ], [ "LOSIN' IT", "has_genre", "COMEDY" ], [ "LOSIN' IT", "release_year", "1983" ], [ "LOVESICK", "has_genre", "COMEDY" ], [ "LOVESICK", "release_year", "1983" ], [ "MALA NOCHE", "has_genre", "DRAMA" ], [ "MALA NOCHE", "written_by", "WALT CURTIS" ], [ "MAX DUGAN RETURNS", "has_genre", "COMEDY" ], [ "MAX DUGAN RETURNS", "has_genre", "DRAMA" ], [ "MAX DUGAN RETURNS", "release_year", "1983" ], [ "MR. MOM", "has_genre", "COMEDY" ], [ "MR. MOM", "release_year", "1983" ], [ "MY TUTOR", "has_genre", "COMEDY" ], [ "MY TUTOR", "release_year", "1983" ], [ "NATIONAL LAMPOON'S VACATION", "has_genre", "COMEDY" ], [ "NATIONAL LAMPOON'S VACATION", "has_tags", "COMEDY" ], [ "NATIONAL LAMPOON'S VACATION", "release_year", "1983" ], [ "NOBODY'S FOOL", "has_genre", "COMEDY" ], [ "NOBODY'S FOOL", "has_genre", "DRAMA" ], [ "NOTHING IN COMMON", "has_genre", "COMEDY" ], [ "NOTHING IN COMMON", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "COMEDY" ], [ "PEGGY SUE GOT MARRIED", "has_genre", "DRAMA" ], [ "PEGGY SUE GOT MARRIED", "has_tags", "DRAMA" ], [ "PRETTY IN PINK", "has_genre", "COMEDY" ], [ "PRETTY IN PINK", "has_genre", "DRAMA" ], [ "PRETTY IN PINK", "has_tags", "COMEDY" ], [ "PRIVATE SCHOOL", "has_genre", "COMEDY" ], [ "PRIVATE SCHOOL", "release_year", "1983" ], [ "PROJECT A", "has_genre", "COMEDY" ], [ "PROJECT A", "release_year", "1983" ], [ "REUBEN, REUBEN", "has_genre", "COMEDY" ], [ "REUBEN, REUBEN", "has_genre", "DRAMA" ], [ "REUBEN, REUBEN", "release_year", "1983" ], [ "RISKY BUSINESS", "has_genre", "COMEDY" ], [ "RISKY BUSINESS", "has_genre", "DRAMA" ], [ "RISKY BUSINESS", "release_year", "1983" ], [ "ROMANTIC COMEDY", "has_genre", "COMEDY" ], [ "ROMANTIC COMEDY", "release_year", "1983" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "release_year", "1983" ], [ "SEEMS LIKE OLD TIMES", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "DRAMA" ], [ "SOMETHING WILD", "has_genre", "COMEDY" ], [ "SOMETHING WILD", "has_genre", "DRAMA" ], [ "SPRING BREAK", "has_genre", "COMEDY" ], [ "SPRING BREAK", "release_year", "1983" ], [ "STRANGE BREW", "has_genre", "COMEDY" ], [ "STRANGE BREW", "release_year", "1983" ], [ "STROKER ACE", "has_genre", "COMEDY" ], [ "STROKER ACE", "release_year", "1983" ], [ "TERMS OF ENDEARMENT", "has_genre", "COMEDY" ], [ "TERMS OF ENDEARMENT", "has_genre", "DRAMA" ], [ "TERMS OF ENDEARMENT", "release_year", "1983" ], [ "THE BIG CHILL", "has_genre", "COMEDY" ], [ "THE BIG CHILL", "has_genre", "DRAMA" ], [ "THE BIG CHILL", "release_year", "1983" ], [ "THE CREATURE WASN'T NICE", "has_genre", "COMEDY" ], [ "THE CREATURE WASN'T NICE", "release_year", "1983" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "COMEDY" ], [ "THE DECLINE OF THE AMERICAN EMPIRE", "has_genre", "DRAMA" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "COMEDY" ], [ "THE MAN WHO LOVED WOMEN", "has_genre", "DRAMA" ], [ "THE MAN WHO LOVED WOMEN", "release_year", "1983" ], [ "THE MAN WITH TWO BRAINS", "has_genre", "COMEDY" ], [ "THE MAN WITH TWO BRAINS", "release_year", "1983" ], [ "THE SEX AND VIOLENCE FAMILY HOUR", "has_genre", "COMEDY" ], [ "THE SEX AND VIOLENCE FAMILY HOUR", "release_year", "1983" ], [ "THE SURVIVORS", "has_genre", "COMEDY" ], [ "THE SURVIVORS", "release_year", "1983" ], [ "TO BE OR NOT TO BE", "has_genre", "COMEDY" ], [ "TO BE OR NOT TO BE", "has_tags", "COMEDY" ], [ "TO BE OR NOT TO BE", "release_year", "1983" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TRADING PLACES", "has_genre", "COMEDY" ], [ "TRADING PLACES", "has_tags", "COMEDY" ], [ "TRADING PLACES", "release_year", "1983" ], [ "TWO OF A KIND", "has_genre", "COMEDY" ], [ "TWO OF A KIND", "release_year", "1983" ], [ "VALLEY GIRL", "has_genre", "COMEDY" ], [ "VALLEY GIRL", "release_year", "1983" ], [ "YELLOWBEARD", "has_genre", "COMEDY" ], [ "YELLOWBEARD", "release_year", "1983" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 11746, ANDREW BUJALSKI 18069, BEESWAX 25618, CHANNING TATUM 27633, FIGHTING 32615, THE TREASURE HUNTER 20619, TREASURE HUNT src, edge_attr, dst 18069, directed_by, 11746 18069, has_tags, 11746 18069, release_year, 27261 18069, written_by, 11746 27633, release_year, 27261 27633, starred_actors, 25618 32615, has_tags, 20619 32615, release_year, 27261 Question: In what context are ANDREW BUJALSKI, CHANNING TATUM, and TREASURE HUNT connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANDREW BUJALSKI", "CHANNING TATUM", "TREASURE HUNT" ], "valid_edges": [ [ "BEESWAX", "directed_by", "ANDREW BUJALSKI" ], [ "BEESWAX", "has_tags", "ANDREW BUJALSKI" ], [ "BEESWAX", "release_year", "2009" ], [ "BEESWAX", "written_by", "ANDREW BUJALSKI" ], [ "FIGHTING", "release_year", "2009" ], [ "FIGHTING", "starred_actors", "CHANNING TATUM" ], [ "THE TREASURE HUNTER", "has_tags", "TREASURE HUNT" ], [ "THE TREASURE HUNTER", "release_year", "2009" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 35935, 2002 37304, 21 JUMP STREET 26646, 3000 MILES TO GRACELAND 6094, A CLOCKWORK ORANGE 19635, A TRUE MOB STORY 6938, ALPHA DOG 20584, AMERICAN GANGSTER 551, AMERICAN GIGOLO 26048, AMERICAN HUSTLE 24342, AMY IRVING 19544, ANDY LAU 23328, APPALOOSA 23513, ASH WEDNESDAY 27270, ASSASSINATION TANGO 30795, ATLANTIC CITY 8402, BANGKOK DANGEROUS 23466, BEFORE THE DEVIL KNOWS YOU'RE DEAD 12228, BETTER LUCK TOMORROW 19633, BIRTHDAY GIRL 6837, BOSSA NOVA 33252, BROOKLYN'S FINEST 25849, BRUBAKER 15986, BUS 174 33362, CARLITO'S WAY 10790, CARRIED AWAY 27059, CATCH ME IF YOU CAN 33387, CITY OF GOD 13888, CITY OF THE LIVING DEAD 38098, CODE OF SILENCE 32049, CRASH 14724, CRIME 7393, CRIME AND PUNISHMENT 17819, DARK BLUE 14292, DEAD IN THE WATER 11826, DEEP COVER 9986, DELITTO A PORTA ROMANA 23027, DEUCES WILD 23396, DIAL M FOR MURDER 5795, DINNER RUSH 21021, DRIVE 12628, EASTERN PROMISES 26193, ELECTION 31254, ELITE SQUAD 8026, END OF THE GAME 31783, ENGLISH 19728, EVILENKO 11021, EYE IN THE SKY 21123, FARGO 16516, FIFTY DEAD MEN WALKING 18217, FIND ME GUILTY 4372, FORCE OF EXECUTION 29332, FOREIGN LANGUAGE 1033, FRACTURE 8690, FROZEN RIVER 17400, GANGS OF NEW YORK 23299, GET CARTER 35657, GLORIA 17938, HANNIBAL 36322, HARD BOILED 13846, HARSH TIMES 33673, HEAT 20659, HIGH AND LOW 26297, HIGH CRIMES 39349, HONEYSUCKLE ROSE 26001, HONG KONG 22006, I WANT YOU 34072, I'M NOT SCARED 978, INFERNAL AFFAIRS 7264, INSIDE MAN 24305, JCVD 13853, JUDGE DREDD 11346, KISS KISS BANG BANG 3854, LAYER CAKE 38120, LORD OF WAR 33950, LUCKY NUMBER SLEVIN 33561, MEAN STREETS 38677, MIAMI VICE 33280, MICHAEL BLACK 1454, MICKEY BLUE EYES 3487, MINORITY REPORT 13217, NARC 1922, NINE QUEENS 29893, NO GOOD DEED 22991, OUT OF THE BLUE 32999, PAID IN FULL 8509, PASSION 8869, PAYBACK 14744, PEOPLE I KNOW 29620, POLICE 26716, PRIDE AND GLORY 26174, PULP FICTION 38043, PUSHER 13081, R 2169, RANSOM 4523, RED DRAGON 31756, REMADE 32357, RESERVOIR DOGS 35872, RICH AND FAMOUS 25098, RICOCHET 5844, RIGHTEOUS KILL 1643, RISE OF THE FOOTSOLDIER 1507, ROAD TO PERDITION 8516, ROBOCOP 9206, ROCKNROLLA 31913, ROMEO IS BLEEDING 15500, ROMEO MUST DIE 33108, RUNNING SCARED 32607, RUSH HOUR 35808, SAFE 8020, SAFE MEN 32487, SAPPHIRE 6056, SCARFACE 5832, SCUM 22196, SERPICO 1472, SHOTTAS 12333, SMOKIN' ACES 7083, SONNY 35843, SPUN 4722, STATE PROPERTY 5170, STEALING HARVARD 16219, STORY 33414, SWEET SIXTEEN 30932, SWORDFISH 2512, THE BANK JOB 26674, THE BIG EASY 11948, THE BLACK DAHLIA 34875, THE COMPETITION 32597, THE DANCER UPSTAIRS 18997, THE DEPARTED 22234, THE ELEPHANT MAN 24501, THE EXTERMINATOR 38918, THE FAMILY 16151, THE FIENDISH PLOT OF DR. FU MANCHU 35551, THE GODFATHER 17518, THE GOOD THIEF 13052, THE HARD WORD 29952, THE INTERNATIONAL 28177, THE KRAYS 16288, THE LARAMIE PROJECT 11559, THE LOOKOUT 21696, THE MAN FROM LONDON 38433, THE MERCHANT OF VENICE 12887, THE MIRROR CRACK'D 37490, THE PERFECT MURDER 40086, THE PLACE BEYOND THE PINES 30014, THE RAID 2 13761, THE ROOKIE 14250, THE SALTON SEA 37148, THE SECRET IN THEIR EYES 19084, THE TOWN 22820, THE UNITED STATES OF LELAND 9390, THE UNTOUCHABLES 20880, THE USUAL SUSPECTS 19255, THE VALACHI PAPERS 14962, THE WATCHER IN THE WOODS 26758, THICK AS THIEVES 37331, TO DIE FOR 2879, TONY LEUNG 33836, TRAFFIC 17169, TRAINING DAY 27559, TRAINSPOTTING 24487, TRAPPED 10720, TRIGGERMEN 10238, UNDERWORLD 10133, UNKNOWN 22588, WANTED 6770, WE OWN THE NIGHT 37210, ZODIAC 17777, ZULU src, edge_attr, dst 37304, has_genre, 14724 37304, has_tags, 29620 26646, has_genre, 14724 26646, has_tags, 13081 6094, has_genre, 14724 6094, has_tags, 13081 6094, in_language, 31783 19635, has_genre, 14724 19635, starred_actors, 19544 6938, has_genre, 14724 6938, has_tags, 13081 20584, has_genre, 14724 20584, has_tags, 14724 20584, has_tags, 13081 551, has_genre, 14724 551, release_year, 36268 26048, has_genre, 14724 26048, has_tags, 13081 23328, has_genre, 14724 23328, has_tags, 13081 23513, has_genre, 14724 23513, release_year, 35935 27270, has_genre, 14724 27270, release_year, 35935 30795, has_genre, 14724 30795, release_year, 36268 8402, has_genre, 14724 8402, has_tags, 14724 8402, has_tags, 13081 23466, has_genre, 14724 23466, has_tags, 13081 12228, has_genre, 14724 12228, release_year, 35935 19633, has_genre, 14724 19633, in_language, 31783 6837, in_language, 31783 6837, starred_actors, 24342 33252, has_genre, 14724 33252, has_tags, 29620 25849, has_genre, 14724 25849, release_year, 36268 15986, has_tags, 29620 15986, release_year, 35935 33362, has_genre, 14724 33362, has_tags, 14724 33362, has_tags, 13081 10790, in_language, 31783 10790, starred_actors, 24342 27059, has_genre, 14724 27059, has_tags, 14724 27059, release_year, 35935 33387, has_genre, 14724 33387, has_tags, 14724 33387, has_tags, 13081 33387, release_year, 35935 13888, in_language, 31783 13888, release_year, 36268 38098, has_genre, 14724 38098, has_tags, 29620 32049, has_tags, 14724 32049, has_tags, 29620 32049, has_tags, 13081 7393, has_genre, 14724 7393, release_year, 35935 17819, has_genre, 14724 17819, release_year, 35935 14292, has_genre, 14724 14292, release_year, 35935 11826, has_genre, 14724 11826, has_tags, 13081 9986, has_genre, 14724 9986, release_year, 36268 23027, has_genre, 14724 23027, release_year, 35935 23396, has_genre, 14724 23396, in_language, 31783 5795, has_genre, 14724 5795, has_tags, 13081 21021, has_genre, 14724 21021, has_tags, 14724 21021, has_tags, 13081 12628, has_genre, 14724 12628, has_tags, 13081 26193, has_genre, 14724 26193, has_tags, 26001 31254, has_genre, 14724 31254, has_tags, 29620 8026, has_genre, 14724 8026, in_language, 31783 19728, has_genre, 14724 19728, in_language, 31783 11021, has_genre, 14724 11021, has_tags, 26001 21123, has_genre, 14724 21123, has_tags, 14724 21123, has_tags, 29620 21123, has_tags, 13081 16516, has_tags, 14724 16516, in_language, 31783 18217, has_genre, 14724 18217, has_tags, 13081 4372, has_genre, 14724 4372, written_by, 33280 1033, has_genre, 14724 1033, has_tags, 13081 8690, has_genre, 14724 8690, has_tags, 13081 17400, has_genre, 14724 17400, has_tags, 13081 17400, has_tags, 16219 17400, release_year, 35935 23299, has_genre, 14724 23299, has_tags, 31756 23299, has_tags, 16219 35657, has_genre, 14724 35657, release_year, 36268 17938, has_genre, 14724 17938, has_tags, 13081 36322, has_genre, 14724 36322, has_tags, 26001 36322, has_tags, 2879 13846, has_genre, 14724 13846, has_tags, 13081 33673, has_genre, 14724 33673, has_tags, 14724 33673, has_tags, 29620 33673, has_tags, 13081 20659, has_genre, 14724 20659, has_tags, 29620 26297, has_genre, 14724 26297, release_year, 35935 39349, release_year, 36268 39349, starred_actors, 24342 22006, has_genre, 14724 22006, in_language, 31783 34072, has_genre, 14724 34072, has_tags, 14724 34072, has_tags, 13081 978, has_genre, 14724 978, has_tags, 19544 978, has_tags, 29332 978, has_tags, 26001 978, has_tags, 29620 978, has_tags, 13081 978, has_tags, 31756 978, has_tags, 16219 978, has_tags, 2879 978, in_language, 31783 978, release_year, 35935 978, starred_actors, 19544 7264, has_genre, 14724 7264, has_tags, 13081 24305, has_genre, 14724 24305, has_tags, 13081 13853, has_genre, 14724 13853, has_tags, 29620 11346, has_genre, 14724 11346, has_tags, 13081 3854, has_genre, 14724 3854, has_tags, 13081 38120, has_genre, 14724 38120, has_tags, 14724 38120, has_tags, 13081 33950, has_genre, 14724 33950, has_tags, 14724 33950, has_tags, 13081 33561, has_genre, 14724 33561, has_tags, 13081 38677, has_genre, 14724 38677, has_tags, 13081 1454, has_genre, 14724 1454, in_language, 31783 3487, has_tags, 14724 3487, has_tags, 29620 3487, release_year, 35935 13217, has_genre, 14724 13217, has_tags, 29620 13217, release_year, 35935 1922, has_genre, 14724 1922, has_tags, 14724 1922, has_tags, 13081 29893, has_genre, 14724 29893, release_year, 35935 22991, release_year, 36268 22991, release_year, 35935 32999, has_genre, 14724 32999, release_year, 35935 8509, has_genre, 14724 8509, in_language, 31783 8869, has_genre, 14724 8869, has_tags, 13081 14744, has_genre, 14724 14744, has_tags, 13081 14744, release_year, 35935 29620, has_genre, 14724 26716, has_genre, 14724 26716, has_tags, 29620 26716, has_tags, 13081 26174, has_genre, 14724 26174, has_tags, 14724 26174, has_tags, 13081 38043, has_genre, 14724 38043, in_language, 31783 2169, has_genre, 14724 2169, has_tags, 13081 4523, has_genre, 14724 4523, has_tags, 13081 4523, release_year, 35935 32357, has_genre, 14724 32357, has_tags, 14724 32357, has_tags, 16219 35872, has_genre, 14724 35872, has_tags, 19544 35872, starred_actors, 19544 25098, has_genre, 14724 25098, has_tags, 13081 5844, has_genre, 14724 5844, has_tags, 13081 1643, has_genre, 14724 1643, has_tags, 14724 1643, in_language, 31783 1507, has_genre, 14724 1507, release_year, 35935 8516, has_tags, 14724 8516, has_tags, 29620 9206, has_genre, 14724 9206, has_tags, 14724 9206, has_tags, 13081 31913, has_genre, 14724 31913, has_tags, 13081 15500, has_tags, 13081 15500, in_language, 31783 33108, has_genre, 14724 33108, has_tags, 29620 33108, release_year, 36268 32607, has_tags, 14724 32607, has_tags, 26001 32607, has_tags, 29620 35808, has_genre, 14724 35808, has_tags, 29620 8020, has_genre, 14724 8020, has_tags, 13081 32487, has_genre, 14724 32487, in_language, 31783 6056, has_genre, 14724 6056, has_tags, 14724 6056, has_tags, 16219 5832, has_genre, 14724 5832, has_tags, 16219 22196, has_genre, 14724 22196, has_tags, 29620 1472, has_genre, 14724 1472, release_year, 35935 12333, has_genre, 14724 12333, has_tags, 13081 7083, has_genre, 14724 7083, release_year, 35935 35843, has_genre, 14724 35843, release_year, 35935 4722, has_genre, 14724 4722, release_year, 35935 5170, has_genre, 14724 5170, release_year, 35935 33414, has_genre, 14724 33414, has_tags, 13081 33414, in_language, 31783 33414, release_year, 35935 30932, has_genre, 14724 30932, has_tags, 13081 2512, has_genre, 14724 2512, has_tags, 13081 26674, has_genre, 14724 26674, has_tags, 13081 11948, has_genre, 14724 11948, has_tags, 13081 34875, release_year, 36268 34875, starred_actors, 24342 32597, has_genre, 14724 32597, release_year, 35935 18997, has_genre, 14724 18997, has_tags, 14724 18997, has_tags, 29620 18997, has_tags, 13081 22234, in_language, 31783 22234, release_year, 36268 24501, has_genre, 14724 24501, release_year, 36268 38918, has_genre, 14724 38918, in_language, 31783 16151, in_language, 31783 16151, release_year, 36268 35551, has_genre, 14724 35551, has_tags, 14724 35551, has_tags, 13081 35551, has_tags, 16219 17518, has_genre, 14724 17518, release_year, 35935 13052, has_genre, 14724 13052, release_year, 35935 29952, has_genre, 14724 29952, has_tags, 13081 28177, has_genre, 14724 28177, in_language, 31783 16288, has_genre, 14724 16288, release_year, 35935 11559, has_genre, 14724 11559, has_tags, 13081 21696, has_genre, 14724 21696, in_language, 31783 38433, has_tags, 13081 38433, in_language, 31783 38433, release_year, 36268 12887, has_genre, 14724 12887, release_year, 36268 37490, has_tags, 14724 37490, in_language, 31783 40086, has_genre, 14724 40086, in_language, 31783 30014, has_genre, 14724 30014, in_language, 31783 13761, has_genre, 14724 13761, release_year, 35935 14250, has_genre, 14724 14250, release_year, 35935 37148, has_tags, 14724 37148, has_tags, 29332 37148, has_tags, 13081 19084, has_genre, 14724 19084, has_tags, 14724 19084, has_tags, 13081 22820, has_genre, 14724 22820, has_tags, 13081 9390, has_genre, 14724 9390, has_tags, 14724 9390, has_tags, 13081 20880, has_genre, 14724 20880, has_tags, 14724 20880, has_tags, 13081 19255, has_genre, 14724 19255, in_language, 31783 14962, in_language, 31783 14962, release_year, 36268 26758, has_genre, 14724 26758, has_tags, 13081 37331, has_genre, 14724 37331, has_tags, 13081 33836, has_genre, 14724 33836, has_tags, 13081 17169, has_genre, 14724 17169, has_tags, 13081 27559, has_tags, 14724 27559, has_tags, 13081 24487, has_genre, 14724 24487, release_year, 35935 10720, has_genre, 14724 10720, has_tags, 14724 10720, release_year, 35935 10238, has_genre, 14724 10238, in_language, 31783 10133, has_genre, 14724 10133, in_language, 31783 22588, has_genre, 14724 22588, has_tags, 13081 6770, has_genre, 14724 6770, has_tags, 13081 37210, has_genre, 14724 37210, has_tags, 14724 37210, has_tags, 29620 37210, has_tags, 13081 17777, has_genre, 14724 17777, in_language, 31783 Question: In what context are HONEYSUCKLE ROSE, INFERNAL AFFAIRS, and MICHAEL BLACK connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HONEYSUCKLE ROSE", "INFERNAL AFFAIRS", "MICHAEL BLACK" ], "valid_edges": [ [ "21 JUMP STREET", "has_genre", "CRIME" ], [ "21 JUMP STREET", "has_tags", "POLICE" ], [ "3000 MILES TO GRACELAND", "has_genre", "CRIME" ], [ "3000 MILES TO GRACELAND", "has_tags", "R" ], [ "A CLOCKWORK ORANGE", "has_genre", "CRIME" ], [ "A CLOCKWORK ORANGE", "has_tags", "R" ], [ "A CLOCKWORK ORANGE", "in_language", "ENGLISH" ], [ "A TRUE MOB STORY", "has_genre", "CRIME" ], [ "A TRUE MOB STORY", "starred_actors", "ANDY LAU" ], [ "ALPHA DOG", "has_genre", "CRIME" ], [ "ALPHA DOG", "has_tags", "R" ], [ "AMERICAN GANGSTER", "has_genre", "CRIME" ], [ "AMERICAN GANGSTER", "has_tags", "CRIME" ], [ "AMERICAN GANGSTER", "has_tags", "R" ], [ "AMERICAN GIGOLO", "has_genre", "CRIME" ], [ "AMERICAN GIGOLO", "release_year", "1980" ], [ "AMERICAN HUSTLE", "has_genre", "CRIME" ], [ "AMERICAN HUSTLE", "has_tags", "R" ], [ "APPALOOSA", "has_genre", "CRIME" ], [ "APPALOOSA", "has_tags", "R" ], [ "ASH WEDNESDAY", "has_genre", "CRIME" ], [ "ASH WEDNESDAY", "release_year", "2002" ], [ "ASSASSINATION TANGO", "has_genre", "CRIME" ], [ "ASSASSINATION TANGO", "release_year", "2002" ], [ "ATLANTIC CITY", "has_genre", "CRIME" ], [ "ATLANTIC CITY", "release_year", "1980" ], [ "BANGKOK DANGEROUS", "has_genre", "CRIME" ], [ "BANGKOK DANGEROUS", "has_tags", "CRIME" ], [ "BANGKOK DANGEROUS", "has_tags", "R" ], [ "BEFORE THE DEVIL KNOWS YOU'RE DEAD", "has_genre", "CRIME" ], [ "BEFORE THE DEVIL KNOWS YOU'RE DEAD", "has_tags", "R" ], [ "BETTER LUCK TOMORROW", "has_genre", "CRIME" ], [ "BETTER LUCK TOMORROW", "release_year", "2002" ], [ "BIRTHDAY GIRL", "has_genre", "CRIME" ], [ "BIRTHDAY GIRL", "in_language", "ENGLISH" ], [ "BOSSA NOVA", "in_language", "ENGLISH" ], [ "BOSSA NOVA", "starred_actors", "AMY IRVING" ], [ "BROOKLYN'S FINEST", "has_genre", "CRIME" ], [ "BROOKLYN'S FINEST", "has_tags", "POLICE" ], [ "BRUBAKER", "has_genre", "CRIME" ], [ "BRUBAKER", "release_year", "1980" ], [ "BUS 174", "has_tags", "POLICE" ], [ "BUS 174", "release_year", "2002" ], [ "CARLITO'S WAY", "has_genre", "CRIME" ], [ "CARLITO'S WAY", "has_tags", "CRIME" ], [ "CARLITO'S WAY", "has_tags", "R" ], [ "CARRIED AWAY", "in_language", "ENGLISH" ], [ "CARRIED AWAY", "starred_actors", "AMY IRVING" ], [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "release_year", "2002" ], [ "CITY OF GOD", "has_genre", "CRIME" ], [ "CITY OF GOD", "has_tags", "CRIME" ], [ "CITY OF GOD", "has_tags", "R" ], [ "CITY OF GOD", "release_year", "2002" ], [ "CITY OF THE LIVING DEAD", "in_language", "ENGLISH" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CODE OF SILENCE", "has_genre", "CRIME" ], [ "CODE OF SILENCE", "has_tags", "POLICE" ], [ "CRASH", "has_tags", "CRIME" ], [ "CRASH", "has_tags", "POLICE" ], [ "CRASH", "has_tags", "R" ], [ "CRIME AND PUNISHMENT", "has_genre", "CRIME" ], [ "CRIME AND PUNISHMENT", "release_year", "2002" ], [ "DARK BLUE", "has_genre", "CRIME" ], [ "DARK BLUE", "release_year", "2002" ], [ "DEAD IN THE WATER", "has_genre", "CRIME" ], [ "DEAD IN THE WATER", "release_year", "2002" ], [ "DEEP COVER", "has_genre", "CRIME" ], [ "DEEP COVER", "has_tags", "R" ], [ "DELITTO A PORTA ROMANA", "has_genre", "CRIME" ], [ "DELITTO A PORTA ROMANA", "release_year", "1980" ], [ "DEUCES WILD", "has_genre", "CRIME" ], [ "DEUCES WILD", "release_year", "2002" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DINNER RUSH", "has_genre", "CRIME" ], [ "DINNER RUSH", "has_tags", "R" ], [ "DRIVE", "has_genre", "CRIME" ], [ "DRIVE", "has_tags", "CRIME" ], [ "DRIVE", "has_tags", "R" ], [ "EASTERN PROMISES", "has_genre", "CRIME" ], [ "EASTERN PROMISES", "has_tags", "R" ], [ "ELECTION", "has_genre", "CRIME" ], [ "ELECTION", "has_tags", "HONG KONG" ], [ "ELITE SQUAD", "has_genre", "CRIME" ], [ "ELITE SQUAD", "has_tags", "POLICE" ], [ "END OF THE GAME", "has_genre", "CRIME" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "EVILENKO", "has_genre", "CRIME" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "EYE IN THE SKY", "has_genre", "CRIME" ], [ "EYE IN THE SKY", "has_tags", "HONG KONG" ], [ "FARGO", "has_genre", "CRIME" ], [ "FARGO", "has_tags", "CRIME" ], [ "FARGO", "has_tags", "POLICE" ], [ "FARGO", "has_tags", "R" ], [ "FIFTY DEAD MEN WALKING", "has_tags", "CRIME" ], [ "FIFTY DEAD MEN WALKING", "in_language", "ENGLISH" ], [ "FIND ME GUILTY", "has_genre", "CRIME" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FORCE OF EXECUTION", "has_genre", "CRIME" ], [ "FORCE OF EXECUTION", "written_by", "MICHAEL BLACK" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_tags", "R" ], [ "FROZEN RIVER", "has_genre", "CRIME" ], [ "FROZEN RIVER", "has_tags", "R" ], [ "GANGS OF NEW YORK", "has_genre", "CRIME" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "has_tags", "STORY" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "GET CARTER", "has_genre", "CRIME" ], [ "GET CARTER", "has_tags", "REMADE" ], [ "GET CARTER", "has_tags", "STORY" ], [ "GLORIA", "has_genre", "CRIME" ], [ "GLORIA", "release_year", "1980" ], [ "HANNIBAL", "has_genre", "CRIME" ], [ "HANNIBAL", "has_tags", "R" ], [ "HARD BOILED", "has_genre", "CRIME" ], [ "HARD BOILED", "has_tags", "HONG KONG" ], [ "HARD BOILED", "has_tags", "TONY LEUNG" ], [ "HARSH TIMES", "has_genre", "CRIME" ], [ "HARSH TIMES", "has_tags", "R" ], [ "HEAT", "has_genre", "CRIME" ], [ "HEAT", "has_tags", "CRIME" ], [ "HEAT", "has_tags", "POLICE" ], [ "HEAT", "has_tags", "R" ], [ "HIGH AND LOW", "has_genre", "CRIME" ], [ "HIGH AND LOW", "has_tags", "POLICE" ], [ "HIGH CRIMES", "has_genre", "CRIME" ], [ "HIGH CRIMES", "release_year", "2002" ], [ "HONEYSUCKLE ROSE", "release_year", "1980" ], [ "HONEYSUCKLE ROSE", "starred_actors", "AMY IRVING" ], [ "I WANT YOU", "has_genre", "CRIME" ], [ "I WANT YOU", "in_language", "ENGLISH" ], [ "I'M NOT SCARED", "has_genre", "CRIME" ], [ "I'M NOT SCARED", "has_tags", "CRIME" ], [ "I'M NOT SCARED", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "has_genre", "CRIME" ], [ "INFERNAL AFFAIRS", "has_tags", "ANDY LAU" ], [ "INFERNAL AFFAIRS", "has_tags", "FOREIGN LANGUAGE" ], [ "INFERNAL AFFAIRS", "has_tags", "HONG KONG" ], [ "INFERNAL AFFAIRS", "has_tags", "POLICE" ], [ "INFERNAL AFFAIRS", "has_tags", "R" ], [ "INFERNAL AFFAIRS", "has_tags", "REMADE" ], [ "INFERNAL AFFAIRS", "has_tags", "STORY" ], [ "INFERNAL AFFAIRS", "has_tags", "TONY LEUNG" ], [ "INFERNAL AFFAIRS", "in_language", "ENGLISH" ], [ "INFERNAL AFFAIRS", "release_year", "2002" ], [ "INFERNAL AFFAIRS", "starred_actors", "ANDY LAU" ], [ "INSIDE MAN", "has_genre", "CRIME" ], [ "INSIDE MAN", "has_tags", "R" ], [ "JCVD", "has_genre", "CRIME" ], [ "JCVD", "has_tags", "R" ], [ "JUDGE DREDD", "has_genre", "CRIME" ], [ "JUDGE DREDD", "has_tags", "POLICE" ], [ "KISS KISS BANG BANG", "has_genre", "CRIME" ], [ "KISS KISS BANG BANG", "has_tags", "R" ], [ "LAYER CAKE", "has_genre", "CRIME" ], [ "LAYER CAKE", "has_tags", "R" ], [ "LORD OF WAR", "has_genre", "CRIME" ], [ "LORD OF WAR", "has_tags", "CRIME" ], [ "LORD OF WAR", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "has_genre", "CRIME" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "CRIME" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "MEAN STREETS", "has_genre", "CRIME" ], [ "MEAN STREETS", "has_tags", "R" ], [ "MIAMI VICE", "has_genre", "CRIME" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MICKEY BLUE EYES", "has_genre", "CRIME" ], [ "MICKEY BLUE EYES", "in_language", "ENGLISH" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "POLICE" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "NARC", "has_genre", "CRIME" ], [ "NARC", "has_tags", "POLICE" ], [ "NARC", "release_year", "2002" ], [ "NINE QUEENS", "has_genre", "CRIME" ], [ "NINE QUEENS", "has_tags", "CRIME" ], [ "NINE QUEENS", "has_tags", "R" ], [ "NO GOOD DEED", "has_genre", "CRIME" ], [ "NO GOOD DEED", "release_year", "2002" ], [ "OUT OF THE BLUE", "release_year", "1980" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PAID IN FULL", "has_genre", "CRIME" ], [ "PAID IN FULL", "release_year", "2002" ], [ "PASSION", "has_genre", "CRIME" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PAYBACK", "has_genre", "CRIME" ], [ "PAYBACK", "has_tags", "R" ], [ "PEOPLE I KNOW", "has_genre", "CRIME" ], [ "PEOPLE I KNOW", "has_tags", "R" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "POLICE", "has_genre", "CRIME" ], [ "PRIDE AND GLORY", "has_genre", "CRIME" ], [ "PRIDE AND GLORY", "has_tags", "POLICE" ], [ "PRIDE AND GLORY", "has_tags", "R" ], [ "PULP FICTION", "has_genre", "CRIME" ], [ "PULP FICTION", "has_tags", "CRIME" ], [ "PULP FICTION", "has_tags", "R" ], [ "PUSHER", "has_genre", "CRIME" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "RANSOM", "has_genre", "CRIME" ], [ "RANSOM", "has_tags", "R" ], [ "RED DRAGON", "has_genre", "CRIME" ], [ "RED DRAGON", "has_tags", "R" ], [ "RED DRAGON", "release_year", "2002" ], [ "RESERVOIR DOGS", "has_genre", "CRIME" ], [ "RESERVOIR DOGS", "has_tags", "CRIME" ], [ "RESERVOIR DOGS", "has_tags", "STORY" ], [ "RICH AND FAMOUS", "has_genre", "CRIME" ], [ "RICH AND FAMOUS", "has_tags", "ANDY LAU" ], [ "RICH AND FAMOUS", "starred_actors", "ANDY LAU" ], [ "RICOCHET", "has_genre", "CRIME" ], [ "RICOCHET", "has_tags", "R" ], [ "RIGHTEOUS KILL", "has_genre", "CRIME" ], [ "RIGHTEOUS KILL", "has_tags", "R" ], [ "RISE OF THE FOOTSOLDIER", "has_genre", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "has_tags", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "ROAD TO PERDITION", "has_genre", "CRIME" ], [ "ROAD TO PERDITION", "release_year", "2002" ], [ "ROBOCOP", "has_tags", "CRIME" ], [ "ROBOCOP", "has_tags", "POLICE" ], [ "ROCKNROLLA", "has_genre", "CRIME" ], [ "ROCKNROLLA", "has_tags", "CRIME" ], [ "ROCKNROLLA", "has_tags", "R" ], [ "ROMEO IS BLEEDING", "has_genre", "CRIME" ], [ "ROMEO IS BLEEDING", "has_tags", "R" ], [ "ROMEO MUST DIE", "has_tags", "R" ], [ "ROMEO MUST DIE", "in_language", "ENGLISH" ], [ "RUNNING SCARED", "has_genre", "CRIME" ], [ "RUNNING SCARED", "has_tags", "POLICE" ], [ "RUNNING SCARED", "release_year", "1980" ], [ "RUSH HOUR", "has_tags", "CRIME" ], [ "RUSH HOUR", "has_tags", "HONG KONG" ], [ "RUSH HOUR", "has_tags", "POLICE" ], [ "SAFE", "has_genre", "CRIME" ], [ "SAFE", "has_tags", "POLICE" ], [ "SAFE MEN", "has_genre", "CRIME" ], [ "SAFE MEN", "has_tags", "R" ], [ "SAPPHIRE", "has_genre", "CRIME" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SCARFACE", "has_genre", "CRIME" ], [ "SCARFACE", "has_tags", "CRIME" ], [ "SCARFACE", "has_tags", "STORY" ], [ "SCUM", "has_genre", "CRIME" ], [ "SCUM", "has_tags", "STORY" ], [ "SERPICO", "has_genre", "CRIME" ], [ "SERPICO", "has_tags", "POLICE" ], [ "SHOTTAS", "has_genre", "CRIME" ], [ "SHOTTAS", "release_year", "2002" ], [ "SMOKIN' ACES", "has_genre", "CRIME" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SONNY", "has_genre", "CRIME" ], [ "SONNY", "release_year", "2002" ], [ "SPUN", "has_genre", "CRIME" ], [ "SPUN", "release_year", "2002" ], [ "STATE PROPERTY", "has_genre", "CRIME" ], [ "STATE PROPERTY", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "CRIME" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_genre", "CRIME" ], [ "SWEET SIXTEEN", "has_tags", "R" ], [ "SWEET SIXTEEN", "in_language", "ENGLISH" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "SWORDFISH", "has_genre", "CRIME" ], [ "SWORDFISH", "has_tags", "R" ], [ "THE BANK JOB", "has_genre", "CRIME" ], [ "THE BANK JOB", "has_tags", "R" ], [ "THE BIG EASY", "has_genre", "CRIME" ], [ "THE BIG EASY", "has_tags", "R" ], [ "THE BLACK DAHLIA", "has_genre", "CRIME" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE COMPETITION", "release_year", "1980" ], [ "THE COMPETITION", "starred_actors", "AMY IRVING" ], [ "THE DANCER UPSTAIRS", "has_genre", "CRIME" ], [ "THE DANCER UPSTAIRS", "release_year", "2002" ], [ "THE DEPARTED", "has_genre", "CRIME" ], [ "THE DEPARTED", "has_tags", "CRIME" ], [ "THE DEPARTED", "has_tags", "POLICE" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE ELEPHANT MAN", "in_language", "ENGLISH" ], [ "THE ELEPHANT MAN", "release_year", "1980" ], [ "THE EXTERMINATOR", "has_genre", "CRIME" ], [ "THE EXTERMINATOR", "release_year", "1980" ], [ "THE FAMILY", "has_genre", "CRIME" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FIENDISH PLOT OF DR. FU MANCHU", "in_language", "ENGLISH" ], [ "THE FIENDISH PLOT OF DR. FU MANCHU", "release_year", "1980" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "CRIME" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "has_tags", "STORY" ], [ "THE GOOD THIEF", "has_genre", "CRIME" ], [ "THE GOOD THIEF", "release_year", "2002" ], [ "THE HARD WORD", "has_genre", "CRIME" ], [ "THE HARD WORD", "release_year", "2002" ], [ "THE INTERNATIONAL", "has_genre", "CRIME" ], [ "THE INTERNATIONAL", "has_tags", "R" ], [ "THE KRAYS", "has_genre", "CRIME" ], [ "THE KRAYS", "in_language", "ENGLISH" ], [ "THE LARAMIE PROJECT", "has_genre", "CRIME" ], [ "THE LARAMIE PROJECT", "release_year", "2002" ], [ "THE LOOKOUT", "has_genre", "CRIME" ], [ "THE LOOKOUT", "has_tags", "R" ], [ "THE MAN FROM LONDON", "has_genre", "CRIME" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "has_tags", "R" ], [ "THE MERCHANT OF VENICE", "in_language", "ENGLISH" ], [ "THE MERCHANT OF VENICE", "release_year", "1980" ], [ "THE MIRROR CRACK'D", "has_genre", "CRIME" ], [ "THE MIRROR CRACK'D", "release_year", "1980" ], [ "THE PERFECT MURDER", "has_tags", "CRIME" ], [ "THE PERFECT MURDER", "in_language", "ENGLISH" ], [ "THE PLACE BEYOND THE PINES", "has_genre", "CRIME" ], [ "THE PLACE BEYOND THE PINES", "in_language", "ENGLISH" ], [ "THE RAID 2", "has_genre", "CRIME" ], [ "THE RAID 2", "in_language", "ENGLISH" ], [ "THE ROOKIE", "has_genre", "CRIME" ], [ "THE ROOKIE", "release_year", "2002" ], [ "THE SALTON SEA", "has_genre", "CRIME" ], [ "THE SALTON SEA", "release_year", "2002" ], [ "THE SECRET IN THEIR EYES", "has_tags", "CRIME" ], [ "THE SECRET IN THEIR EYES", "has_tags", "FOREIGN LANGUAGE" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE TOWN", "has_genre", "CRIME" ], [ "THE TOWN", "has_tags", "CRIME" ], [ "THE TOWN", "has_tags", "R" ], [ "THE UNITED STATES OF LELAND", "has_genre", "CRIME" ], [ "THE UNITED STATES OF LELAND", "has_tags", "R" ], [ "THE UNTOUCHABLES", "has_genre", "CRIME" ], [ "THE UNTOUCHABLES", "has_tags", "CRIME" ], [ "THE UNTOUCHABLES", "has_tags", "R" ], [ "THE USUAL SUSPECTS", "has_genre", "CRIME" ], [ "THE USUAL SUSPECTS", "has_tags", "CRIME" ], [ "THE USUAL SUSPECTS", "has_tags", "R" ], [ "THE VALACHI PAPERS", "has_genre", "CRIME" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "THICK AS THIEVES", "has_genre", "CRIME" ], [ "THICK AS THIEVES", "has_tags", "R" ], [ "TO DIE FOR", "has_genre", "CRIME" ], [ "TO DIE FOR", "has_tags", "R" ], [ "TRAFFIC", "has_genre", "CRIME" ], [ "TRAFFIC", "has_tags", "R" ], [ "TRAINING DAY", "has_genre", "CRIME" ], [ "TRAINING DAY", "has_tags", "R" ], [ "TRAINSPOTTING", "has_tags", "CRIME" ], [ "TRAINSPOTTING", "has_tags", "R" ], [ "TRAPPED", "has_genre", "CRIME" ], [ "TRAPPED", "release_year", "2002" ], [ "TRIGGERMEN", "has_genre", "CRIME" ], [ "TRIGGERMEN", "has_tags", "CRIME" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "UNDERWORLD", "has_genre", "CRIME" ], [ "UNDERWORLD", "in_language", "ENGLISH" ], [ "UNKNOWN", "has_genre", "CRIME" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "WANTED", "has_genre", "CRIME" ], [ "WANTED", "has_tags", "R" ], [ "WE OWN THE NIGHT", "has_genre", "CRIME" ], [ "WE OWN THE NIGHT", "has_tags", "R" ], [ "ZODIAC", "has_genre", "CRIME" ], [ "ZODIAC", "has_tags", "CRIME" ], [ "ZODIAC", "has_tags", "POLICE" ], [ "ZODIAC", "has_tags", "R" ], [ "ZULU", "has_genre", "CRIME" ], [ "ZULU", "in_language", "ENGLISH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3458, 1951 3702, 1995 38344, A STREETCAR NAMED DESIRE 38907, ABBOTT AND COSTELLO MEET THE INVISIBLE MAN 31987, ACROSS THE SEA OF TIME 4763, ADVENTURE 29638, ALICE IN WONDERLAND 17157, ARABIAN NIGHTS 18666, BALTO 38657, BEAT THE DEVIL 14207, BEYOND THE CLOUDS 1587, BUSHWHACKED 16220, CAPTAIN HORATIO HORNBLOWER R.N. 16, CONGO 10386, CRY, THE BELOVED COUNTRY 8438, CUT AND RUN 30802, CUTTHROAT ISLAND 12903, DISNEY 16200, ITALIAN 14980, JUMANJI 20149, LAST OF THE DOGMEN 4386, MIRACLE IN MILAN 39027, MORTAL KOMBAT 11078, MOUSE 12215, ROB ROY 35586, SAHARA 29427, STARCRASH 26790, SWEPT AWAY 29639, TALL TALE 38627, TEN TALL MEN 29634, THE AFRICAN QUEEN 4001, THE AMAZING PANDA ADVENTURE 30259, THE GREAT MOUSE DETECTIVE 32270, THE HORSEMAN ON THE ROOF 18787, THE INDIAN IN THE CUPBOARD 39975, THE RESCUERS 27481, THE STAR MAKER 32074, TOM AND HUCK 9450, TOY STORY 32079, ULYSSES 29631, WHITE FANG src, edge_attr, dst 38344, release_year, 3458 38344, release_year, 3702 38907, release_year, 3458 31987, has_genre, 4763 31987, release_year, 3702 29638, has_genre, 4763 29638, release_year, 3458 17157, has_genre, 4763 17157, in_language, 16200 18666, has_genre, 4763 18666, release_year, 3702 38657, has_genre, 4763 38657, in_language, 16200 14207, in_language, 16200 14207, release_year, 3702 1587, has_genre, 4763 1587, release_year, 3702 16220, has_genre, 4763 16220, release_year, 3458 16, has_genre, 4763 16, release_year, 3702 10386, release_year, 3458 10386, release_year, 3702 8438, has_genre, 4763 8438, in_language, 16200 30802, has_genre, 4763 30802, has_tags, 4763 30802, release_year, 3702 14980, has_genre, 4763 14980, has_tags, 4763 14980, release_year, 3702 20149, has_genre, 4763 20149, release_year, 3702 4386, in_language, 16200 4386, release_year, 3458 39027, has_genre, 4763 39027, release_year, 3702 12215, has_genre, 4763 12215, release_year, 3702 35586, has_genre, 4763 35586, in_language, 16200 29427, has_genre, 4763 29427, in_language, 16200 26790, has_genre, 4763 26790, in_language, 16200 29639, has_genre, 4763 29639, release_year, 3702 38627, has_genre, 4763 38627, release_year, 3458 29634, has_genre, 4763 29634, has_tags, 4763 29634, release_year, 3458 4001, has_genre, 4763 4001, release_year, 3702 30259, has_genre, 4763 30259, has_tags, 12903 30259, has_tags, 11078 32270, has_genre, 4763 32270, in_language, 16200 32270, release_year, 3702 18787, has_genre, 4763 18787, release_year, 3702 39975, has_genre, 4763 39975, has_tags, 12903 39975, has_tags, 11078 27481, in_language, 16200 27481, release_year, 3702 32074, has_genre, 4763 32074, release_year, 3702 9450, has_genre, 4763 9450, has_tags, 4763 9450, release_year, 3702 32079, has_genre, 4763 32079, in_language, 16200 29631, has_genre, 4763 29631, in_language, 16200 Question: How are ABBOTT AND COSTELLO MEET THE INVISIBLE MAN, MOUSE, and THE HORSEMAN ON THE ROOF related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ABBOTT AND COSTELLO MEET THE INVISIBLE MAN", "MOUSE", "THE HORSEMAN ON THE ROOF" ], "valid_edges": [ [ "A STREETCAR NAMED DESIRE", "release_year", "1951" ], [ "A STREETCAR NAMED DESIRE", "release_year", "1995" ], [ "ABBOTT AND COSTELLO MEET THE INVISIBLE MAN", "release_year", "1951" ], [ "ACROSS THE SEA OF TIME", "has_genre", "ADVENTURE" ], [ "ACROSS THE SEA OF TIME", "release_year", "1995" ], [ "ALICE IN WONDERLAND", "has_genre", "ADVENTURE" ], [ "ALICE IN WONDERLAND", "release_year", "1951" ], [ "ARABIAN NIGHTS", "has_genre", "ADVENTURE" ], [ "ARABIAN NIGHTS", "in_language", "ITALIAN" ], [ "BALTO", "has_genre", "ADVENTURE" ], [ "BALTO", "release_year", "1995" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "in_language", "ITALIAN" ], [ "BEYOND THE CLOUDS", "in_language", "ITALIAN" ], [ "BEYOND THE CLOUDS", "release_year", "1995" ], [ "BUSHWHACKED", "has_genre", "ADVENTURE" ], [ "BUSHWHACKED", "release_year", "1995" ], [ "CAPTAIN HORATIO HORNBLOWER R.N.", "has_genre", "ADVENTURE" ], [ "CAPTAIN HORATIO HORNBLOWER R.N.", "release_year", "1951" ], [ "CONGO", "has_genre", "ADVENTURE" ], [ "CONGO", "release_year", "1995" ], [ "CRY, THE BELOVED COUNTRY", "release_year", "1951" ], [ "CRY, THE BELOVED COUNTRY", "release_year", "1995" ], [ "CUT AND RUN", "has_genre", "ADVENTURE" ], [ "CUT AND RUN", "in_language", "ITALIAN" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "release_year", "1995" ], [ "JUMANJI", "has_genre", "ADVENTURE" ], [ "JUMANJI", "has_tags", "ADVENTURE" ], [ "JUMANJI", "release_year", "1995" ], [ "LAST OF THE DOGMEN", "has_genre", "ADVENTURE" ], [ "LAST OF THE DOGMEN", "release_year", "1995" ], [ "MIRACLE IN MILAN", "in_language", "ITALIAN" ], [ "MIRACLE IN MILAN", "release_year", "1951" ], [ "MORTAL KOMBAT", "has_genre", "ADVENTURE" ], [ "MORTAL KOMBAT", "release_year", "1995" ], [ "ROB ROY", "has_genre", "ADVENTURE" ], [ "ROB ROY", "release_year", "1995" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "in_language", "ITALIAN" ], [ "STARCRASH", "has_genre", "ADVENTURE" ], [ "STARCRASH", "in_language", "ITALIAN" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "in_language", "ITALIAN" ], [ "TALL TALE", "has_genre", "ADVENTURE" ], [ "TALL TALE", "release_year", "1995" ], [ "TEN TALL MEN", "has_genre", "ADVENTURE" ], [ "TEN TALL MEN", "release_year", "1951" ], [ "THE AFRICAN QUEEN", "has_genre", "ADVENTURE" ], [ "THE AFRICAN QUEEN", "has_tags", "ADVENTURE" ], [ "THE AFRICAN QUEEN", "release_year", "1951" ], [ "THE AMAZING PANDA ADVENTURE", "has_genre", "ADVENTURE" ], [ "THE AMAZING PANDA ADVENTURE", "release_year", "1995" ], [ "THE GREAT MOUSE DETECTIVE", "has_genre", "ADVENTURE" ], [ "THE GREAT MOUSE DETECTIVE", "has_tags", "DISNEY" ], [ "THE GREAT MOUSE DETECTIVE", "has_tags", "MOUSE" ], [ "THE HORSEMAN ON THE ROOF", "has_genre", "ADVENTURE" ], [ "THE HORSEMAN ON THE ROOF", "in_language", "ITALIAN" ], [ "THE HORSEMAN ON THE ROOF", "release_year", "1995" ], [ "THE INDIAN IN THE CUPBOARD", "has_genre", "ADVENTURE" ], [ "THE INDIAN IN THE CUPBOARD", "release_year", "1995" ], [ "THE RESCUERS", "has_genre", "ADVENTURE" ], [ "THE RESCUERS", "has_tags", "DISNEY" ], [ "THE RESCUERS", "has_tags", "MOUSE" ], [ "THE STAR MAKER", "in_language", "ITALIAN" ], [ "THE STAR MAKER", "release_year", "1995" ], [ "TOM AND HUCK", "has_genre", "ADVENTURE" ], [ "TOM AND HUCK", "release_year", "1995" ], [ "TOY STORY", "has_genre", "ADVENTURE" ], [ "TOY STORY", "has_tags", "ADVENTURE" ], [ "TOY STORY", "release_year", "1995" ], [ "ULYSSES", "has_genre", "ADVENTURE" ], [ "ULYSSES", "in_language", "ITALIAN" ], [ "WHITE FANG", "has_genre", "ADVENTURE" ], [ "WHITE FANG", "in_language", "ITALIAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7158, 1958 35935, 2002 36647, 8 WOMEN 14372, 9/11 20458, AFTER TILLER 7292, BOND GIRLS ARE FOREVER 17464, BOWLING FOR COLUMBINE 15986, BUS 174 10349, CHICAGO 20977, DAHMER 12841, DOCUMENTARY 22198, I WANT TO LIVE! 13825, INSOMNIA 3487, MINORITY REPORT 28476, MURDER 1128, NICOLAS CAGE 22991, OUT OF THE BLUE 13701, PRISONER OF PARADISE 21740, SEARCHING FOR DEBRA WINGER 7083, SONNY 8600, STANDING IN THE SHADOWS OF MOTOWN 20901, THE BACKYARD 30121, THE FROZEN GROUND 20850, THE QUIET AMERICAN 39950, THE TRIALS OF HENRY KISSINGER 25405, WINDTALKERS src, edge_attr, dst 36647, has_tags, 28476 36647, release_year, 35935 14372, has_genre, 12841 14372, release_year, 35935 20458, has_genre, 12841 7292, has_genre, 12841 7292, release_year, 35935 17464, has_genre, 12841 17464, has_tags, 12841 17464, release_year, 35935 15986, has_genre, 12841 15986, has_tags, 12841 15986, release_year, 35935 10349, has_tags, 28476 10349, release_year, 35935 20977, has_tags, 28476 20977, release_year, 35935 22198, has_tags, 28476 22198, release_year, 7158 13825, has_tags, 28476 13825, release_year, 35935 3487, has_tags, 28476 3487, release_year, 35935 22991, has_genre, 12841 22991, release_year, 35935 13701, has_genre, 12841 13701, release_year, 35935 21740, has_genre, 12841 21740, release_year, 35935 7083, directed_by, 1128 7083, has_tags, 1128 7083, release_year, 35935 8600, has_genre, 12841 8600, release_year, 35935 20901, has_genre, 12841 20901, release_year, 35935 30121, has_tags, 28476 30121, starred_actors, 1128 20850, release_year, 7158 20850, release_year, 35935 39950, has_genre, 12841 39950, has_tags, 12841 39950, release_year, 35935 25405, has_tags, 1128 25405, release_year, 35935 25405, starred_actors, 1128 Question: In what context are AFTER TILLER, I WANT TO LIVE!, and SONNY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AFTER TILLER", "I WANT TO LIVE!", "SONNY" ], "valid_edges": [ [ "8 WOMEN", "has_tags", "MURDER" ], [ "8 WOMEN", "release_year", "2002" ], [ "9/11", "has_genre", "DOCUMENTARY" ], [ "9/11", "release_year", "2002" ], [ "AFTER TILLER", "has_genre", "DOCUMENTARY" ], [ "BOND GIRLS ARE FOREVER", "has_genre", "DOCUMENTARY" ], [ "BOND GIRLS ARE FOREVER", "release_year", "2002" ], [ "BOWLING FOR COLUMBINE", "has_genre", "DOCUMENTARY" ], [ "BOWLING FOR COLUMBINE", "has_tags", "DOCUMENTARY" ], [ "BOWLING FOR COLUMBINE", "release_year", "2002" ], [ "BUS 174", "has_genre", "DOCUMENTARY" ], [ "BUS 174", "has_tags", "DOCUMENTARY" ], [ "BUS 174", "release_year", "2002" ], [ "CHICAGO", "has_tags", "MURDER" ], [ "CHICAGO", "release_year", "2002" ], [ "DAHMER", "has_tags", "MURDER" ], [ "DAHMER", "release_year", "2002" ], [ "I WANT TO LIVE!", "has_tags", "MURDER" ], [ "I WANT TO LIVE!", "release_year", "1958" ], [ "INSOMNIA", "has_tags", "MURDER" ], [ "INSOMNIA", "release_year", "2002" ], [ "MINORITY REPORT", "has_tags", "MURDER" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "OUT OF THE BLUE", "has_genre", "DOCUMENTARY" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PRISONER OF PARADISE", "has_genre", "DOCUMENTARY" ], [ "PRISONER OF PARADISE", "release_year", "2002" ], [ "SEARCHING FOR DEBRA WINGER", "has_genre", "DOCUMENTARY" ], [ "SEARCHING FOR DEBRA WINGER", "release_year", "2002" ], [ "SONNY", "directed_by", "NICOLAS CAGE" ], [ "SONNY", "has_tags", "NICOLAS CAGE" ], [ "SONNY", "release_year", "2002" ], [ "STANDING IN THE SHADOWS OF MOTOWN", "has_genre", "DOCUMENTARY" ], [ "STANDING IN THE SHADOWS OF MOTOWN", "release_year", "2002" ], [ "THE BACKYARD", "has_genre", "DOCUMENTARY" ], [ "THE BACKYARD", "release_year", "2002" ], [ "THE FROZEN GROUND", "has_tags", "MURDER" ], [ "THE FROZEN GROUND", "starred_actors", "NICOLAS CAGE" ], [ "THE QUIET AMERICAN", "release_year", "1958" ], [ "THE QUIET AMERICAN", "release_year", "2002" ], [ "THE TRIALS OF HENRY KISSINGER", "has_genre", "DOCUMENTARY" ], [ "THE TRIALS OF HENRY KISSINGER", "has_tags", "DOCUMENTARY" ], [ "THE TRIALS OF HENRY KISSINGER", "release_year", "2002" ], [ "WINDTALKERS", "has_tags", "NICOLAS CAGE" ], [ "WINDTALKERS", "release_year", "2002" ], [ "WINDTALKERS", "starred_actors", "NICOLAS CAGE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14259, 1997 27261, 2009 30146, A CHRISTMAS CAROL 4681, A SIMPLE WISH 25570, BEAUTY AND THE BEAST 4197, BLUEBEARD 29177, BOOTY CALL 39861, CINDERELLA 35896, CORALINE 30123, DORIAN GRAY 24303, DRAGONQUEST 36066, FANTASY 4796, HARRY POTTER AND THE HALF-BLOOD PRINCE 35174, INK 26171, KULL THE CONQUEROR 8536, MALICE IN WONDERLAND 21686, MOONLIGHT SERENADE 18584, PRINCESS MONONOKE 16482, RICKY 4314, SOLOMON KANE 13858, SOPHIE'S REVENGE 2584, THE ADVENTURES OF BARON MUNCHAUSEN 8387, THE BLACK WATERS OF ECHO'S POND 23333, THE HOLE 5081, THE IMAGINARIUM OF DOCTOR PARNASSUS 2336, THE INVENTION OF LYING 25924, THE PRINCESS AND THE FROG 11925, TWILIGHT OF THE ICE NYMPHS 4814, WARRIORS OF VIRTUE src, edge_attr, dst 30146, has_genre, 36066 30146, release_year, 14259 30146, release_year, 27261 4681, has_genre, 36066 4681, has_tags, 36066 4681, release_year, 14259 25570, has_genre, 36066 25570, has_tags, 36066 25570, release_year, 27261 4197, has_genre, 36066 4197, release_year, 27261 29177, release_year, 14259 39861, has_genre, 36066 39861, release_year, 14259 35896, has_genre, 36066 35896, has_tags, 36066 35896, release_year, 27261 30123, has_genre, 36066 30123, release_year, 27261 24303, has_genre, 36066 24303, has_tags, 36066 24303, release_year, 27261 4796, has_genre, 36066 4796, has_tags, 36066 4796, release_year, 27261 35174, has_genre, 36066 35174, release_year, 27261 26171, has_genre, 36066 26171, release_year, 14259 8536, has_genre, 36066 8536, release_year, 27261 21686, release_year, 14259 21686, release_year, 27261 18584, has_genre, 36066 18584, has_tags, 36066 18584, release_year, 14259 16482, has_genre, 36066 16482, release_year, 27261 4314, has_genre, 36066 4314, has_tags, 36066 4314, release_year, 27261 13858, release_year, 27261 2584, has_genre, 36066 2584, has_tags, 36066 8387, has_genre, 36066 8387, release_year, 27261 23333, has_genre, 36066 23333, release_year, 27261 5081, has_genre, 36066 5081, has_tags, 36066 5081, release_year, 27261 2336, has_genre, 36066 2336, release_year, 27261 25924, has_genre, 36066 25924, release_year, 27261 11925, has_genre, 36066 11925, release_year, 14259 4814, has_genre, 36066 4814, release_year, 14259 Question: For what reason are BOOTY CALL, SOPHIE'S REVENGE, and THE ADVENTURES OF BARON MUNCHAUSEN associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BOOTY CALL", "SOPHIE'S REVENGE", "THE ADVENTURES OF BARON MUNCHAUSEN" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "FANTASY" ], [ "A CHRISTMAS CAROL", "release_year", "1997" ], [ "A CHRISTMAS CAROL", "release_year", "2009" ], [ "A SIMPLE WISH", "has_genre", "FANTASY" ], [ "A SIMPLE WISH", "has_tags", "FANTASY" ], [ "A SIMPLE WISH", "release_year", "1997" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "release_year", "2009" ], [ "BLUEBEARD", "has_genre", "FANTASY" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BOOTY CALL", "release_year", "1997" ], [ "CINDERELLA", "has_genre", "FANTASY" ], [ "CINDERELLA", "release_year", "1997" ], [ "CORALINE", "has_genre", "FANTASY" ], [ "CORALINE", "has_tags", "FANTASY" ], [ "CORALINE", "release_year", "2009" ], [ "DORIAN GRAY", "has_genre", "FANTASY" ], [ "DORIAN GRAY", "release_year", "2009" ], [ "DRAGONQUEST", "has_genre", "FANTASY" ], [ "DRAGONQUEST", "has_tags", "FANTASY" ], [ "DRAGONQUEST", "release_year", "2009" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "has_genre", "FANTASY" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "has_tags", "FANTASY" ], [ "HARRY POTTER AND THE HALF-BLOOD PRINCE", "release_year", "2009" ], [ "INK", "has_genre", "FANTASY" ], [ "INK", "release_year", "2009" ], [ "KULL THE CONQUEROR", "has_genre", "FANTASY" ], [ "KULL THE CONQUEROR", "release_year", "1997" ], [ "MALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "MALICE IN WONDERLAND", "release_year", "2009" ], [ "MOONLIGHT SERENADE", "release_year", "1997" ], [ "MOONLIGHT SERENADE", "release_year", "2009" ], [ "PRINCESS MONONOKE", "has_genre", "FANTASY" ], [ "PRINCESS MONONOKE", "has_tags", "FANTASY" ], [ "PRINCESS MONONOKE", "release_year", "1997" ], [ "RICKY", "has_genre", "FANTASY" ], [ "RICKY", "release_year", "2009" ], [ "SOLOMON KANE", "has_genre", "FANTASY" ], [ "SOLOMON KANE", "has_tags", "FANTASY" ], [ "SOLOMON KANE", "release_year", "2009" ], [ "SOPHIE'S REVENGE", "release_year", "2009" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_genre", "FANTASY" ], [ "THE ADVENTURES OF BARON MUNCHAUSEN", "has_tags", "FANTASY" ], [ "THE BLACK WATERS OF ECHO'S POND", "has_genre", "FANTASY" ], [ "THE BLACK WATERS OF ECHO'S POND", "release_year", "2009" ], [ "THE HOLE", "has_genre", "FANTASY" ], [ "THE HOLE", "release_year", "2009" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "has_genre", "FANTASY" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "has_tags", "FANTASY" ], [ "THE IMAGINARIUM OF DOCTOR PARNASSUS", "release_year", "2009" ], [ "THE INVENTION OF LYING", "has_genre", "FANTASY" ], [ "THE INVENTION OF LYING", "release_year", "2009" ], [ "THE PRINCESS AND THE FROG", "has_genre", "FANTASY" ], [ "THE PRINCESS AND THE FROG", "release_year", "2009" ], [ "TWILIGHT OF THE ICE NYMPHS", "has_genre", "FANTASY" ], [ "TWILIGHT OF THE ICE NYMPHS", "release_year", "1997" ], [ "WARRIORS OF VIRTUE", "has_genre", "FANTASY" ], [ "WARRIORS OF VIRTUE", "release_year", "1997" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 5423, A LATE QUARTET 32632, A ROYAL AFFAIR 20562, A THOUSAND WORDS 21800, ABOUT CHERRY 29800, ACE ATTORNEY 30332, AMOUR 36963, ANNA KARENINA 24708, ANY DAY NOW 22078, ARBITRAGE 10277, ARGO 13686, ARTHUR NEWMAN 7302, AS COOL AS I AM 9695, AT ANY PRICE 31449, BARABBAS 38263, BARBARA 23994, BARFI! 26783, BE KIND REWIND 30581, BEASTS OF THE SOUTHERN WILD 37191, BEING FLYNN 28199, BEL AMI 32770, BEST MAN DOWN 14594, BEYOND THE HILLS 890, BIG MIRACLE 36071, BLACKBIRD 39848, BLUE LIKE JAZZ 22284, BOY EATING THE BIRD'S FOOD 27030, BROKEN 33711, CAESAR MUST DIE 32831, CALL GIRL 24707, CAMILLE REWINDS 12735, CHASING MAVERICKS 32450, CHEERFUL WEATHER FOR THE WEDDING 27338, CLIP 38925, CLOUD ATLAS 21016, COMPLIANCE 24757, CONSUMING SPIRITS 37589, COSMOPOLIS 19894, CRAVE 32797, DANGEROUS LIAISONS 10643, DARLING COMPANION 31694, DEADFALL 38977, DISCONNECT 36212, DRAMA 7480, EDEN 26106, END OF WATCH 32892, ENGLISH VINGLISH 6394, EXCISION 19570, FAREWELL, MY QUEEN 39636, FILL THE VOID 5563, FLIGHT 12314, FOR ELLEN 7740, FOREIGN LETTERS 11672, FOREVER AMBER 15473, FORGETTING THE GIRL 6076, FRANCES HA 24535, GAME CHANGE 2427, GIRL IN PROGRESS 32380, GOSSIP 5647, HANNAH ARENDT 3917, HELLO HERMAN 22793, HEROINE 27350, HITCHCOCK 3030, HOLY MOTORS 35319, HOPE SPRINGS 35625, HUMAN NATURE 37844, HYDE PARK ON HUDSON 19154, I BELONG 38589, I DO 32376, IMAGINE 26911, IN THE FOG 24025, INESCAPABLE 39536, JAMES MARSDEN 6301, JAYNE MANSFIELD'S CAR 22087, JEROME CADY 5418, K-11 12835, KAUWBOY 26232, KEEP THE LIGHTS ON 3103, LAURENCE ANYWAYS 1418, LAWLESS 14601, LES MISÉRABLES 14931, LIBERAL ARTS 39727, LIFE OF PI 36020, LIKE SOMEONE IN LOVE 47, LINCOLN 17372, LOL 34517, LUV 35871, MAGIC MIKE 13801, MARFA GIRL 34611, ME AND YOU 37973, MICHEL GONDRY 31735, MIDDLE OF NOWHERE 39165, MUD 19118, MUSEUM HOURS 24915, MY WAY 26089, NAKED HARBOUR 25504, NEIGHBORING SOUNDS 8107, NO 20503, NOBODY WALKS 17532, NOT FADE AWAY 17263, NOW IS GOOD 21677, ON THE ROAD 38602, OUR CHILDREN 8523, OUT IN THE DARK 31312, PEOPLE LIKE US 15815, POST TENEBRAS LUX 11253, PROMISED LAND 11237, PURGE 25023, QUARTET 35746, REALITY 33501, RENOIR 11839, REVENGE FOR JOLLY! 12597, RUBY SPARKS 30316, RUST AND BONE 35808, SAFE 17168, SEEKING A FRIEND FOR THE END OF THE WORLD 25060, SEXUAL CHRONICLES OF A FRENCH FAMILY 28583, SHADOW DANCER 34584, SILVER LININGS PLAYBOOK 7174, SISTER 39426, SMASHED 28026, SOMEBODY UP THERE LIKES ME 33759, SOMETHING IN THE AIR 17346, SPRING BREAKERS 17608, STARLET 39286, STILL MINE 40067, STOLEN 25002, STRUCK BY LIGHTNING 3038, STUCK IN LOVE 18335, TABU 19501, THANKS FOR SHARING 3885, THE ARTIST AND THE MODEL 19623, THE BATTERY 29460, THE BEST OF ME 24441, THE BROKEN CIRCLE BREAKDOWN 38175, THE CITIZEN 6644, THE COMEDY 2399, THE DEEP 10295, THE END OF LOVE 27103, THE FITZGERALD FAMILY CHRISTMAS 14688, THE FLOATING CASTLE 35267, THE FORGER 16929, THE GIRL 15980, THE GUILT TRIP 9328, THE HUNT 38614, THE IMPOSSIBLE 22800, THE LESSER BLESSED 33948, THE LETTER 4984, THE LUCKY ONE 23191, THE MAGIC OF BELLE ISLE 24652, THE MAN WHO LAUGHS 17964, THE MASTER 15798, THE ODD LIFE OF TIMOTHY GREEN 28735, THE OTHER SON 1195, THE PATIENCE STONE 7673, THE PERKS OF BEING A WALLFLOWER 2739, THE SAPPHIRES 27064, THE SCAPEGOAT 8650, THE SESSIONS 37915, THE STORY OF LUKE 14524, THE SWEENEY 12086, THE VOW 26797, THE WALL 4614, THE WE AND THE I 3437, THE WOMAN IN BLACK 15504, THE WORDS 266, THREE WORLDS 5352, THY WOMB 9918, TO THE WONDER 17451, TROUBLE WITH THE CURVE 13359, TWO LIVES 10305, UNCONDITIONAL 30056, WAR WITCH 7030, WHAT IF... 24333, WHAT MAISIE KNEW 34118, WHAT TO EXPECT WHEN YOU'RE EXPECTING 21183, WHITE ELEPHANT 18608, WHITE FROG 36174, WINNING STREAK 26337, WON'T BACK DOWN 31040, XINGU 9052, YOSSI 16849, ZERO DARK THIRTY src, edge_attr, dst 5423, has_genre, 36212 5423, has_tags, 36212 5423, release_year, 658 32632, has_genre, 36212 32632, release_year, 658 20562, has_genre, 36212 20562, release_year, 658 21800, has_genre, 36212 21800, release_year, 658 29800, has_genre, 36212 29800, release_year, 658 30332, has_genre, 36212 30332, release_year, 658 36963, has_genre, 36212 36963, has_tags, 36212 36963, release_year, 658 24708, has_genre, 36212 24708, release_year, 658 22078, has_genre, 36212 22078, release_year, 658 10277, has_genre, 36212 10277, has_tags, 36212 10277, release_year, 658 13686, has_genre, 36212 13686, release_year, 658 7302, has_genre, 36212 7302, starred_actors, 39536 9695, has_genre, 36212 9695, release_year, 658 31449, has_genre, 36212 31449, release_year, 658 38263, has_genre, 36212 38263, release_year, 658 23994, has_genre, 36212 23994, release_year, 658 26783, directed_by, 37973 26783, has_genre, 36212 26783, has_tags, 37973 26783, written_by, 37973 30581, has_genre, 36212 30581, release_year, 658 37191, has_genre, 36212 37191, release_year, 658 28199, has_genre, 36212 28199, release_year, 658 32770, has_genre, 36212 32770, release_year, 658 14594, has_genre, 36212 14594, release_year, 658 890, has_genre, 36212 890, release_year, 658 36071, has_genre, 36212 36071, release_year, 658 39848, has_genre, 36212 39848, release_year, 658 22284, has_genre, 36212 22284, release_year, 658 27030, has_genre, 36212 27030, release_year, 658 33711, has_genre, 36212 33711, release_year, 658 32831, has_genre, 36212 32831, release_year, 658 24707, has_genre, 36212 24707, release_year, 658 12735, has_genre, 36212 12735, release_year, 658 32450, has_genre, 36212 32450, release_year, 658 27338, has_genre, 36212 27338, release_year, 658 38925, has_genre, 36212 38925, has_tags, 36212 38925, release_year, 658 21016, has_genre, 36212 21016, release_year, 658 24757, has_genre, 36212 24757, release_year, 658 37589, has_genre, 36212 37589, release_year, 658 19894, has_genre, 36212 19894, release_year, 658 32797, has_genre, 36212 32797, release_year, 658 10643, has_genre, 36212 10643, release_year, 658 31694, has_genre, 36212 31694, release_year, 658 38977, has_genre, 36212 38977, has_tags, 36212 38977, release_year, 658 7480, has_genre, 36212 7480, release_year, 658 26106, has_genre, 36212 26106, release_year, 658 32892, has_genre, 36212 32892, release_year, 658 6394, has_genre, 36212 6394, release_year, 658 19570, has_genre, 36212 19570, release_year, 658 39636, has_genre, 36212 39636, release_year, 658 5563, has_genre, 36212 5563, release_year, 658 12314, has_genre, 36212 12314, release_year, 658 7740, has_genre, 36212 7740, release_year, 658 11672, has_genre, 36212 11672, written_by, 22087 15473, has_genre, 36212 15473, release_year, 658 6076, has_genre, 36212 6076, release_year, 658 24535, has_genre, 36212 24535, release_year, 658 2427, has_genre, 36212 2427, release_year, 658 32380, has_genre, 36212 32380, has_tags, 32380 32380, starred_actors, 39536 5647, has_genre, 36212 5647, release_year, 658 3917, has_genre, 36212 3917, release_year, 658 22793, has_genre, 36212 22793, release_year, 658 27350, has_genre, 36212 27350, release_year, 658 3030, has_genre, 36212 3030, release_year, 658 35319, has_genre, 36212 35319, release_year, 658 35625, directed_by, 37973 35625, has_genre, 36212 35625, has_tags, 37973 37844, has_genre, 36212 37844, release_year, 658 19154, has_genre, 36212 19154, release_year, 658 38589, has_genre, 36212 38589, release_year, 658 32376, has_genre, 36212 32376, release_year, 658 26911, has_genre, 36212 26911, release_year, 658 24025, has_genre, 36212 24025, release_year, 658 6301, has_genre, 36212 6301, release_year, 658 5418, has_genre, 36212 5418, release_year, 658 12835, has_genre, 36212 12835, release_year, 658 26232, has_genre, 36212 26232, release_year, 658 3103, has_genre, 36212 3103, release_year, 658 1418, has_genre, 36212 1418, has_tags, 36212 1418, release_year, 658 14601, has_genre, 36212 14601, release_year, 658 14931, has_genre, 36212 14931, release_year, 658 39727, has_genre, 36212 39727, release_year, 658 36020, has_genre, 36212 36020, release_year, 658 47, has_genre, 36212 47, has_tags, 36212 47, release_year, 658 17372, has_genre, 36212 17372, release_year, 658 34517, has_genre, 36212 34517, release_year, 658 35871, has_genre, 36212 35871, release_year, 658 13801, has_genre, 36212 13801, release_year, 658 34611, has_genre, 36212 34611, release_year, 658 31735, has_genre, 36212 31735, release_year, 658 39165, has_genre, 36212 39165, release_year, 658 19118, has_genre, 36212 19118, release_year, 658 24915, has_genre, 36212 24915, release_year, 658 26089, has_genre, 36212 26089, release_year, 658 25504, has_genre, 36212 25504, release_year, 658 8107, has_genre, 36212 8107, release_year, 658 20503, has_genre, 36212 20503, release_year, 658 17532, has_genre, 36212 17532, release_year, 658 17263, has_genre, 36212 17263, release_year, 658 21677, has_genre, 36212 21677, release_year, 658 38602, has_genre, 36212 38602, release_year, 658 8523, has_genre, 36212 8523, release_year, 658 31312, has_genre, 36212 31312, has_tags, 36212 31312, release_year, 658 15815, has_genre, 36212 15815, release_year, 658 11253, has_genre, 36212 11253, release_year, 658 11237, has_genre, 36212 11237, release_year, 658 25023, has_genre, 36212 25023, release_year, 658 35746, has_genre, 36212 35746, release_year, 658 33501, has_genre, 36212 33501, release_year, 658 11839, has_genre, 36212 11839, release_year, 658 12597, has_genre, 36212 12597, release_year, 658 30316, has_genre, 36212 30316, release_year, 658 35808, has_genre, 36212 35808, release_year, 658 17168, has_genre, 36212 17168, release_year, 658 25060, has_genre, 36212 25060, release_year, 658 28583, has_genre, 36212 28583, release_year, 658 34584, has_genre, 36212 34584, has_tags, 36212 34584, release_year, 658 7174, has_genre, 36212 7174, release_year, 658 39426, has_genre, 36212 39426, release_year, 658 28026, has_genre, 36212 28026, release_year, 658 33759, has_genre, 36212 33759, release_year, 658 17346, has_genre, 36212 17346, release_year, 658 17608, has_genre, 36212 17608, release_year, 658 39286, has_genre, 36212 39286, release_year, 658 40067, has_genre, 36212 40067, release_year, 658 25002, has_genre, 36212 25002, release_year, 658 3038, has_genre, 36212 3038, release_year, 658 18335, has_genre, 36212 18335, release_year, 658 19501, has_genre, 36212 19501, release_year, 658 3885, has_genre, 36212 3885, release_year, 658 19623, has_genre, 36212 19623, release_year, 658 29460, has_genre, 36212 29460, starred_actors, 39536 24441, has_genre, 36212 24441, has_tags, 36212 24441, release_year, 658 38175, has_genre, 36212 38175, release_year, 658 6644, has_genre, 36212 6644, release_year, 658 2399, has_genre, 36212 2399, release_year, 658 10295, has_genre, 36212 10295, release_year, 658 27103, has_genre, 36212 27103, release_year, 658 14688, has_genre, 36212 14688, release_year, 658 35267, has_genre, 36212 35267, release_year, 658 16929, has_genre, 36212 16929, release_year, 658 15980, has_genre, 36212 15980, release_year, 658 9328, has_genre, 36212 9328, has_tags, 36212 9328, release_year, 658 38614, has_genre, 36212 38614, has_tags, 36212 38614, release_year, 658 22800, has_genre, 36212 22800, release_year, 658 33948, has_genre, 36212 33948, release_year, 658 4984, has_genre, 36212 4984, release_year, 658 23191, has_genre, 36212 23191, release_year, 658 24652, has_genre, 36212 24652, release_year, 658 17964, has_genre, 36212 17964, release_year, 658 15798, has_genre, 36212 15798, release_year, 658 28735, has_genre, 36212 28735, release_year, 658 1195, has_genre, 36212 1195, release_year, 658 7673, has_genre, 36212 7673, has_tags, 36212 7673, release_year, 658 2739, has_genre, 36212 2739, release_year, 658 27064, has_genre, 36212 27064, release_year, 658 8650, has_genre, 36212 8650, has_tags, 36212 8650, release_year, 658 37915, has_genre, 36212 37915, release_year, 658 14524, has_genre, 36212 14524, release_year, 658 12086, has_genre, 36212 12086, release_year, 658 26797, has_genre, 36212 26797, release_year, 658 4614, directed_by, 37973 4614, has_genre, 36212 4614, release_year, 658 4614, written_by, 37973 3437, has_genre, 36212 3437, release_year, 658 15504, has_genre, 36212 15504, release_year, 658 266, has_genre, 36212 266, release_year, 658 5352, has_genre, 36212 5352, release_year, 658 9918, has_genre, 36212 9918, release_year, 658 17451, has_genre, 36212 17451, release_year, 658 13359, has_genre, 36212 13359, release_year, 658 10305, has_genre, 36212 10305, release_year, 658 30056, has_genre, 36212 30056, release_year, 658 7030, has_genre, 36212 7030, release_year, 658 24333, has_genre, 36212 24333, release_year, 658 34118, has_genre, 36212 34118, release_year, 658 21183, has_genre, 36212 21183, release_year, 658 18608, has_genre, 36212 18608, release_year, 658 36174, has_genre, 36212 36174, release_year, 658 26337, has_genre, 36212 26337, release_year, 658 31040, has_genre, 36212 31040, release_year, 658 9052, has_genre, 36212 9052, release_year, 658 16849, has_genre, 36212 16849, release_year, 658 Question: In what context are JAMES MARSDEN, JEROME CADY, and THE WE AND THE I connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JAMES MARSDEN", "JEROME CADY", "THE WE AND THE I" ], "valid_edges": [ [ "A LATE QUARTET", "has_genre", "DRAMA" ], [ "A LATE QUARTET", "has_tags", "DRAMA" ], [ "A LATE QUARTET", "release_year", "2012" ], [ "A ROYAL AFFAIR", "has_genre", "DRAMA" ], [ "A ROYAL AFFAIR", "release_year", "2012" ], [ "A THOUSAND WORDS", "has_genre", "DRAMA" ], [ "A THOUSAND WORDS", "release_year", "2012" ], [ "ABOUT CHERRY", "has_genre", "DRAMA" ], [ "ABOUT CHERRY", "release_year", "2012" ], [ "ACE ATTORNEY", "has_genre", "DRAMA" ], [ "ACE ATTORNEY", "release_year", "2012" ], [ "AMOUR", "has_genre", "DRAMA" ], [ "AMOUR", "release_year", "2012" ], [ "ANNA KARENINA", "has_genre", "DRAMA" ], [ "ANNA KARENINA", "has_tags", "DRAMA" ], [ "ANNA KARENINA", "release_year", "2012" ], [ "ANY DAY NOW", "has_genre", "DRAMA" ], [ "ANY DAY NOW", "release_year", "2012" ], [ "ARBITRAGE", "has_genre", "DRAMA" ], [ "ARBITRAGE", "release_year", "2012" ], [ "ARGO", "has_genre", "DRAMA" ], [ "ARGO", "has_tags", "DRAMA" ], [ "ARGO", "release_year", "2012" ], [ "ARTHUR NEWMAN", "has_genre", "DRAMA" ], [ "ARTHUR NEWMAN", "release_year", "2012" ], [ "AS COOL AS I AM", "has_genre", "DRAMA" ], [ "AS COOL AS I AM", "starred_actors", "JAMES MARSDEN" ], [ "AT ANY PRICE", "has_genre", "DRAMA" ], [ "AT ANY PRICE", "release_year", "2012" ], [ "BARABBAS", "has_genre", "DRAMA" ], [ "BARABBAS", "release_year", "2012" ], [ "BARBARA", "has_genre", "DRAMA" ], [ "BARBARA", "release_year", "2012" ], [ "BARFI!", "has_genre", "DRAMA" ], [ "BARFI!", "release_year", "2012" ], [ "BE KIND REWIND", "directed_by", "MICHEL GONDRY" ], [ "BE KIND REWIND", "has_genre", "DRAMA" ], [ "BE KIND REWIND", "has_tags", "MICHEL GONDRY" ], [ "BE KIND REWIND", "written_by", "MICHEL GONDRY" ], [ "BEASTS OF THE SOUTHERN WILD", "has_genre", "DRAMA" ], [ "BEASTS OF THE SOUTHERN WILD", "release_year", "2012" ], [ "BEING FLYNN", "has_genre", "DRAMA" ], [ "BEING FLYNN", "release_year", "2012" ], [ "BEL AMI", "has_genre", "DRAMA" ], [ "BEL AMI", "release_year", "2012" ], [ "BEST MAN DOWN", "has_genre", "DRAMA" ], [ "BEST MAN DOWN", "release_year", "2012" ], [ "BEYOND THE HILLS", "has_genre", "DRAMA" ], [ "BEYOND THE HILLS", "release_year", "2012" ], [ "BIG MIRACLE", "has_genre", "DRAMA" ], [ "BIG MIRACLE", "release_year", "2012" ], [ "BLACKBIRD", "has_genre", "DRAMA" ], [ "BLACKBIRD", "release_year", "2012" ], [ "BLUE LIKE JAZZ", "has_genre", "DRAMA" ], [ "BLUE LIKE JAZZ", "release_year", "2012" ], [ "BOY EATING THE BIRD'S FOOD", "has_genre", "DRAMA" ], [ "BOY EATING THE BIRD'S FOOD", "release_year", "2012" ], [ "BROKEN", "has_genre", "DRAMA" ], [ "BROKEN", "release_year", "2012" ], [ "CAESAR MUST DIE", "has_genre", "DRAMA" ], [ "CAESAR MUST DIE", "release_year", "2012" ], [ "CALL GIRL", "has_genre", "DRAMA" ], [ "CALL GIRL", "release_year", "2012" ], [ "CAMILLE REWINDS", "has_genre", "DRAMA" ], [ "CAMILLE REWINDS", "release_year", "2012" ], [ "CHASING MAVERICKS", "has_genre", "DRAMA" ], [ "CHASING MAVERICKS", "release_year", "2012" ], [ "CHEERFUL WEATHER FOR THE WEDDING", "has_genre", "DRAMA" ], [ "CHEERFUL WEATHER FOR THE WEDDING", "release_year", "2012" ], [ "CLIP", "has_genre", "DRAMA" ], [ "CLIP", "release_year", "2012" ], [ "CLOUD ATLAS", "has_genre", "DRAMA" ], [ "CLOUD ATLAS", "has_tags", "DRAMA" ], [ "CLOUD ATLAS", "release_year", "2012" ], [ "COMPLIANCE", "has_genre", "DRAMA" ], [ "COMPLIANCE", "release_year", "2012" ], [ "CONSUMING SPIRITS", "has_genre", "DRAMA" ], [ "CONSUMING SPIRITS", "release_year", "2012" ], [ "COSMOPOLIS", "has_genre", "DRAMA" ], [ "COSMOPOLIS", "release_year", "2012" ], [ "CRAVE", "has_genre", "DRAMA" ], [ "CRAVE", "release_year", "2012" ], [ "DANGEROUS LIAISONS", "has_genre", "DRAMA" ], [ "DANGEROUS LIAISONS", "release_year", "2012" ], [ "DARLING COMPANION", "has_genre", "DRAMA" ], [ "DARLING COMPANION", "release_year", "2012" ], [ "DEADFALL", "has_genre", "DRAMA" ], [ "DEADFALL", "release_year", "2012" ], [ "DISCONNECT", "has_genre", "DRAMA" ], [ "DISCONNECT", "has_tags", "DRAMA" ], [ "DISCONNECT", "release_year", "2012" ], [ "EDEN", "has_genre", "DRAMA" ], [ "EDEN", "release_year", "2012" ], [ "END OF WATCH", "has_genre", "DRAMA" ], [ "END OF WATCH", "release_year", "2012" ], [ "ENGLISH VINGLISH", "has_genre", "DRAMA" ], [ "ENGLISH VINGLISH", "release_year", "2012" ], [ "EXCISION", "has_genre", "DRAMA" ], [ "EXCISION", "release_year", "2012" ], [ "FAREWELL, MY QUEEN", "has_genre", "DRAMA" ], [ "FAREWELL, MY QUEEN", "release_year", "2012" ], [ "FILL THE VOID", "has_genre", "DRAMA" ], [ "FILL THE VOID", "release_year", "2012" ], [ "FLIGHT", "has_genre", "DRAMA" ], [ "FLIGHT", "release_year", "2012" ], [ "FOR ELLEN", "has_genre", "DRAMA" ], [ "FOR ELLEN", "release_year", "2012" ], [ "FOREIGN LETTERS", "has_genre", "DRAMA" ], [ "FOREIGN LETTERS", "release_year", "2012" ], [ "FOREVER AMBER", "has_genre", "DRAMA" ], [ "FOREVER AMBER", "written_by", "JEROME CADY" ], [ "FORGETTING THE GIRL", "has_genre", "DRAMA" ], [ "FORGETTING THE GIRL", "release_year", "2012" ], [ "FRANCES HA", "has_genre", "DRAMA" ], [ "FRANCES HA", "release_year", "2012" ], [ "GAME CHANGE", "has_genre", "DRAMA" ], [ "GAME CHANGE", "release_year", "2012" ], [ "GIRL IN PROGRESS", "has_genre", "DRAMA" ], [ "GIRL IN PROGRESS", "release_year", "2012" ], [ "GOSSIP", "has_genre", "DRAMA" ], [ "GOSSIP", "has_tags", "GOSSIP" ], [ "GOSSIP", "starred_actors", "JAMES MARSDEN" ], [ "HANNAH ARENDT", "has_genre", "DRAMA" ], [ "HANNAH ARENDT", "release_year", "2012" ], [ "HELLO HERMAN", "has_genre", "DRAMA" ], [ "HELLO HERMAN", "release_year", "2012" ], [ "HEROINE", "has_genre", "DRAMA" ], [ "HEROINE", "release_year", "2012" ], [ "HITCHCOCK", "has_genre", "DRAMA" ], [ "HITCHCOCK", "release_year", "2012" ], [ "HOLY MOTORS", "has_genre", "DRAMA" ], [ "HOLY MOTORS", "release_year", "2012" ], [ "HOPE SPRINGS", "has_genre", "DRAMA" ], [ "HOPE SPRINGS", "release_year", "2012" ], [ "HUMAN NATURE", "directed_by", "MICHEL GONDRY" ], [ "HUMAN NATURE", "has_genre", "DRAMA" ], [ "HUMAN NATURE", "has_tags", "MICHEL GONDRY" ], [ "HYDE PARK ON HUDSON", "has_genre", "DRAMA" ], [ "HYDE PARK ON HUDSON", "release_year", "2012" ], [ "I BELONG", "has_genre", "DRAMA" ], [ "I BELONG", "release_year", "2012" ], [ "I DO", "has_genre", "DRAMA" ], [ "I DO", "release_year", "2012" ], [ "IMAGINE", "has_genre", "DRAMA" ], [ "IMAGINE", "release_year", "2012" ], [ "IN THE FOG", "has_genre", "DRAMA" ], [ "IN THE FOG", "release_year", "2012" ], [ "INESCAPABLE", "has_genre", "DRAMA" ], [ "INESCAPABLE", "release_year", "2012" ], [ "JAYNE MANSFIELD'S CAR", "has_genre", "DRAMA" ], [ "JAYNE MANSFIELD'S CAR", "release_year", "2012" ], [ "K-11", "has_genre", "DRAMA" ], [ "K-11", "release_year", "2012" ], [ "KAUWBOY", "has_genre", "DRAMA" ], [ "KAUWBOY", "release_year", "2012" ], [ "KEEP THE LIGHTS ON", "has_genre", "DRAMA" ], [ "KEEP THE LIGHTS ON", "release_year", "2012" ], [ "LAURENCE ANYWAYS", "has_genre", "DRAMA" ], [ "LAURENCE ANYWAYS", "release_year", "2012" ], [ "LAWLESS", "has_genre", "DRAMA" ], [ "LAWLESS", "has_tags", "DRAMA" ], [ "LAWLESS", "release_year", "2012" ], [ "LES MISÉRABLES", "has_genre", "DRAMA" ], [ "LES MISÉRABLES", "release_year", "2012" ], [ "LIBERAL ARTS", "has_genre", "DRAMA" ], [ "LIBERAL ARTS", "release_year", "2012" ], [ "LIFE OF PI", "has_genre", "DRAMA" ], [ "LIFE OF PI", "release_year", "2012" ], [ "LIKE SOMEONE IN LOVE", "has_genre", "DRAMA" ], [ "LIKE SOMEONE IN LOVE", "release_year", "2012" ], [ "LINCOLN", "has_genre", "DRAMA" ], [ "LINCOLN", "has_tags", "DRAMA" ], [ "LINCOLN", "release_year", "2012" ], [ "LOL", "has_genre", "DRAMA" ], [ "LOL", "release_year", "2012" ], [ "LUV", "has_genre", "DRAMA" ], [ "LUV", "release_year", "2012" ], [ "MAGIC MIKE", "has_genre", "DRAMA" ], [ "MAGIC MIKE", "release_year", "2012" ], [ "MARFA GIRL", "has_genre", "DRAMA" ], [ "MARFA GIRL", "release_year", "2012" ], [ "ME AND YOU", "has_genre", "DRAMA" ], [ "ME AND YOU", "release_year", "2012" ], [ "MIDDLE OF NOWHERE", "has_genre", "DRAMA" ], [ "MIDDLE OF NOWHERE", "release_year", "2012" ], [ "MUD", "has_genre", "DRAMA" ], [ "MUD", "release_year", "2012" ], [ "MUSEUM HOURS", "has_genre", "DRAMA" ], [ "MUSEUM HOURS", "release_year", "2012" ], [ "MY WAY", "has_genre", "DRAMA" ], [ "MY WAY", "release_year", "2012" ], [ "NAKED HARBOUR", "has_genre", "DRAMA" ], [ "NAKED HARBOUR", "release_year", "2012" ], [ "NEIGHBORING SOUNDS", "has_genre", "DRAMA" ], [ "NEIGHBORING SOUNDS", "release_year", "2012" ], [ "NO", "has_genre", "DRAMA" ], [ "NO", "release_year", "2012" ], [ "NOBODY WALKS", "has_genre", "DRAMA" ], [ "NOBODY WALKS", "release_year", "2012" ], [ "NOT FADE AWAY", "has_genre", "DRAMA" ], [ "NOT FADE AWAY", "release_year", "2012" ], [ "NOW IS GOOD", "has_genre", "DRAMA" ], [ "NOW IS GOOD", "release_year", "2012" ], [ "ON THE ROAD", "has_genre", "DRAMA" ], [ "ON THE ROAD", "release_year", "2012" ], [ "OUR CHILDREN", "has_genre", "DRAMA" ], [ "OUR CHILDREN", "release_year", "2012" ], [ "OUT IN THE DARK", "has_genre", "DRAMA" ], [ "OUT IN THE DARK", "release_year", "2012" ], [ "PEOPLE LIKE US", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_tags", "DRAMA" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "POST TENEBRAS LUX", "has_genre", "DRAMA" ], [ "POST TENEBRAS LUX", "release_year", "2012" ], [ "PROMISED LAND", "has_genre", "DRAMA" ], [ "PROMISED LAND", "release_year", "2012" ], [ "PURGE", "has_genre", "DRAMA" ], [ "PURGE", "release_year", "2012" ], [ "QUARTET", "has_genre", "DRAMA" ], [ "QUARTET", "release_year", "2012" ], [ "REALITY", "has_genre", "DRAMA" ], [ "REALITY", "release_year", "2012" ], [ "RENOIR", "has_genre", "DRAMA" ], [ "RENOIR", "release_year", "2012" ], [ "REVENGE FOR JOLLY!", "has_genre", "DRAMA" ], [ "REVENGE FOR JOLLY!", "release_year", "2012" ], [ "RUBY SPARKS", "has_genre", "DRAMA" ], [ "RUBY SPARKS", "release_year", "2012" ], [ "RUST AND BONE", "has_genre", "DRAMA" ], [ "RUST AND BONE", "release_year", "2012" ], [ "SAFE", "has_genre", "DRAMA" ], [ "SAFE", "release_year", "2012" ], [ "SEEKING A FRIEND FOR THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "SEEKING A FRIEND FOR THE END OF THE WORLD", "release_year", "2012" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "has_genre", "DRAMA" ], [ "SEXUAL CHRONICLES OF A FRENCH FAMILY", "release_year", "2012" ], [ "SHADOW DANCER", "has_genre", "DRAMA" ], [ "SHADOW DANCER", "release_year", "2012" ], [ "SILVER LININGS PLAYBOOK", "has_genre", "DRAMA" ], [ "SILVER LININGS PLAYBOOK", "has_tags", "DRAMA" ], [ "SILVER LININGS PLAYBOOK", "release_year", "2012" ], [ "SISTER", "has_genre", "DRAMA" ], [ "SISTER", "release_year", "2012" ], [ "SMASHED", "has_genre", "DRAMA" ], [ "SMASHED", "release_year", "2012" ], [ "SOMEBODY UP THERE LIKES ME", "has_genre", "DRAMA" ], [ "SOMEBODY UP THERE LIKES ME", "release_year", "2012" ], [ "SOMETHING IN THE AIR", "has_genre", "DRAMA" ], [ "SOMETHING IN THE AIR", "release_year", "2012" ], [ "SPRING BREAKERS", "has_genre", "DRAMA" ], [ "SPRING BREAKERS", "release_year", "2012" ], [ "STARLET", "has_genre", "DRAMA" ], [ "STARLET", "release_year", "2012" ], [ "STILL MINE", "has_genre", "DRAMA" ], [ "STILL MINE", "release_year", "2012" ], [ "STOLEN", "has_genre", "DRAMA" ], [ "STOLEN", "release_year", "2012" ], [ "STRUCK BY LIGHTNING", "has_genre", "DRAMA" ], [ "STRUCK BY LIGHTNING", "release_year", "2012" ], [ "STUCK IN LOVE", "has_genre", "DRAMA" ], [ "STUCK IN LOVE", "release_year", "2012" ], [ "TABU", "has_genre", "DRAMA" ], [ "TABU", "release_year", "2012" ], [ "THANKS FOR SHARING", "has_genre", "DRAMA" ], [ "THANKS FOR SHARING", "release_year", "2012" ], [ "THE ARTIST AND THE MODEL", "has_genre", "DRAMA" ], [ "THE ARTIST AND THE MODEL", "release_year", "2012" ], [ "THE BATTERY", "has_genre", "DRAMA" ], [ "THE BATTERY", "release_year", "2012" ], [ "THE BEST OF ME", "has_genre", "DRAMA" ], [ "THE BEST OF ME", "starred_actors", "JAMES MARSDEN" ], [ "THE BROKEN CIRCLE BREAKDOWN", "has_genre", "DRAMA" ], [ "THE BROKEN CIRCLE BREAKDOWN", "has_tags", "DRAMA" ], [ "THE BROKEN CIRCLE BREAKDOWN", "release_year", "2012" ], [ "THE CITIZEN", "has_genre", "DRAMA" ], [ "THE CITIZEN", "release_year", "2012" ], [ "THE COMEDY", "has_genre", "DRAMA" ], [ "THE COMEDY", "release_year", "2012" ], [ "THE DEEP", "has_genre", "DRAMA" ], [ "THE DEEP", "release_year", "2012" ], [ "THE END OF LOVE", "has_genre", "DRAMA" ], [ "THE END OF LOVE", "release_year", "2012" ], [ "THE FITZGERALD FAMILY CHRISTMAS", "has_genre", "DRAMA" ], [ "THE FITZGERALD FAMILY CHRISTMAS", "release_year", "2012" ], [ "THE FLOATING CASTLE", "has_genre", "DRAMA" ], [ "THE FLOATING CASTLE", "release_year", "2012" ], [ "THE FORGER", "has_genre", "DRAMA" ], [ "THE FORGER", "release_year", "2012" ], [ "THE GIRL", "has_genre", "DRAMA" ], [ "THE GIRL", "release_year", "2012" ], [ "THE GUILT TRIP", "has_genre", "DRAMA" ], [ "THE GUILT TRIP", "release_year", "2012" ], [ "THE HUNT", "has_genre", "DRAMA" ], [ "THE HUNT", "has_tags", "DRAMA" ], [ "THE HUNT", "release_year", "2012" ], [ "THE IMPOSSIBLE", "has_genre", "DRAMA" ], [ "THE IMPOSSIBLE", "has_tags", "DRAMA" ], [ "THE IMPOSSIBLE", "release_year", "2012" ], [ "THE LESSER BLESSED", "has_genre", "DRAMA" ], [ "THE LESSER BLESSED", "release_year", "2012" ], [ "THE LETTER", "has_genre", "DRAMA" ], [ "THE LETTER", "release_year", "2012" ], [ "THE LUCKY ONE", "has_genre", "DRAMA" ], [ "THE LUCKY ONE", "release_year", "2012" ], [ "THE MAGIC OF BELLE ISLE", "has_genre", "DRAMA" ], [ "THE MAGIC OF BELLE ISLE", "release_year", "2012" ], [ "THE MAN WHO LAUGHS", "has_genre", "DRAMA" ], [ "THE MAN WHO LAUGHS", "release_year", "2012" ], [ "THE MASTER", "has_genre", "DRAMA" ], [ "THE MASTER", "release_year", "2012" ], [ "THE ODD LIFE OF TIMOTHY GREEN", "has_genre", "DRAMA" ], [ "THE ODD LIFE OF TIMOTHY GREEN", "release_year", "2012" ], [ "THE OTHER SON", "has_genre", "DRAMA" ], [ "THE OTHER SON", "release_year", "2012" ], [ "THE PATIENCE STONE", "has_genre", "DRAMA" ], [ "THE PATIENCE STONE", "release_year", "2012" ], [ "THE PERKS OF BEING A WALLFLOWER", "has_genre", "DRAMA" ], [ "THE PERKS OF BEING A WALLFLOWER", "has_tags", "DRAMA" ], [ "THE PERKS OF BEING A WALLFLOWER", "release_year", "2012" ], [ "THE SAPPHIRES", "has_genre", "DRAMA" ], [ "THE SAPPHIRES", "release_year", "2012" ], [ "THE SCAPEGOAT", "has_genre", "DRAMA" ], [ "THE SCAPEGOAT", "release_year", "2012" ], [ "THE SESSIONS", "has_genre", "DRAMA" ], [ "THE SESSIONS", "has_tags", "DRAMA" ], [ "THE SESSIONS", "release_year", "2012" ], [ "THE STORY OF LUKE", "has_genre", "DRAMA" ], [ "THE STORY OF LUKE", "release_year", "2012" ], [ "THE SWEENEY", "has_genre", "DRAMA" ], [ "THE SWEENEY", "release_year", "2012" ], [ "THE VOW", "has_genre", "DRAMA" ], [ "THE VOW", "release_year", "2012" ], [ "THE WALL", "has_genre", "DRAMA" ], [ "THE WALL", "release_year", "2012" ], [ "THE WE AND THE I", "directed_by", "MICHEL GONDRY" ], [ "THE WE AND THE I", "has_genre", "DRAMA" ], [ "THE WE AND THE I", "release_year", "2012" ], [ "THE WE AND THE I", "written_by", "MICHEL GONDRY" ], [ "THE WOMAN IN BLACK", "has_genre", "DRAMA" ], [ "THE WOMAN IN BLACK", "release_year", "2012" ], [ "THE WORDS", "has_genre", "DRAMA" ], [ "THE WORDS", "release_year", "2012" ], [ "THREE WORLDS", "has_genre", "DRAMA" ], [ "THREE WORLDS", "release_year", "2012" ], [ "THY WOMB", "has_genre", "DRAMA" ], [ "THY WOMB", "release_year", "2012" ], [ "TO THE WONDER", "has_genre", "DRAMA" ], [ "TO THE WONDER", "release_year", "2012" ], [ "TROUBLE WITH THE CURVE", "has_genre", "DRAMA" ], [ "TROUBLE WITH THE CURVE", "release_year", "2012" ], [ "TWO LIVES", "has_genre", "DRAMA" ], [ "TWO LIVES", "release_year", "2012" ], [ "UNCONDITIONAL", "has_genre", "DRAMA" ], [ "UNCONDITIONAL", "release_year", "2012" ], [ "WAR WITCH", "has_genre", "DRAMA" ], [ "WAR WITCH", "release_year", "2012" ], [ "WHAT IF...", "has_genre", "DRAMA" ], [ "WHAT IF...", "release_year", "2012" ], [ "WHAT MAISIE KNEW", "has_genre", "DRAMA" ], [ "WHAT MAISIE KNEW", "release_year", "2012" ], [ "WHAT TO EXPECT WHEN YOU'RE EXPECTING", "has_genre", "DRAMA" ], [ "WHAT TO EXPECT WHEN YOU'RE EXPECTING", "release_year", "2012" ], [ "WHITE ELEPHANT", "has_genre", "DRAMA" ], [ "WHITE ELEPHANT", "release_year", "2012" ], [ "WHITE FROG", "has_genre", "DRAMA" ], [ "WHITE FROG", "release_year", "2012" ], [ "WINNING STREAK", "has_genre", "DRAMA" ], [ "WINNING STREAK", "release_year", "2012" ], [ "WON'T BACK DOWN", "has_genre", "DRAMA" ], [ "WON'T BACK DOWN", "release_year", "2012" ], [ "XINGU", "has_genre", "DRAMA" ], [ "XINGU", "release_year", "2012" ], [ "YOSSI", "has_genre", "DRAMA" ], [ "YOSSI", "release_year", "2012" ], [ "ZERO DARK THIRTY", "has_genre", "DRAMA" ], [ "ZERO DARK THIRTY", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 28171, 1986 18899, A BUCKET OF BLOOD 39750, ALIENS 18169, APRIL FOOL'S DAY 10045, BD-R 19826, BLACK DEATH 26014, BLOOD OF THE VAMPIRE 32620, BUBBA HO-TEP 24454, CARRIE 37912, CAT PEOPLE 28328, CAT'S EYE 5741, CHILDREN OF THE CORN 36535, CHOPPING MALL 24443, CHRISTINE 14884, CLASS OF NUKE 'EM HIGH 22349, CRAWLSPACE 30260, CREEPSHOW 19984, CREEPSHOW 2 6743, CRITTERS 25956, CUJO 4381, DEAD OF NIGHT 21213, DEADLY FRIEND 27143, DEMENTIA 13 31980, DEMONS 2 8381, DETOUR 23807, DOCTOR X 3154, DONOVAN'S BRAIN 34827, DR. JEKYLL AND MR. HYDE 36920, DRACULA HAS RISEN FROM THE GRAVE 37707, DRACULA'S DAUGHTER 35978, DREAMCATCHER 29503, EYE OF THE DEVIL 24540, EYES WITHOUT A FACE 32144, FRANKENSTEIN MUST BE DESTROYED 3270, FROM BEYOND 38609, GALAXY OF TERROR 30778, GOTHIC 12378, HANDS OF THE RIPPER 39972, HOLLOW MAN 5870, HORROR 22421, HORROR EXPRESS 10147, HOUSE 10955, HOUSE OF USHER 9686, HOUSE OF WAX 13070, INVADERS FROM MARS 24952, LINK 8851, LITTLE SHOP OF HORRORS 40127, MACABRE 17728, MAD LOVE 26370, MADHOUSE 20487, MARC BRANDEL 25643, MARK OF THE VAMPIRE 3129, MAXIMUM OVERDRIVE 7625, MISERY 20500, MONSTER IN THE CLOSET 18402, MOUNTAINTOP MOTEL MASSACRE 5420, MYRNA FAHEY 16462, MYSTERY OF THE WAX MUSEUM 11181, NIGHT OF THE CREEPS 17189, NIGHT OF THE DEMONS 9330, NIGHT OF THE LEPUS 32988, NIGHT OF THE LIVING DEAD 39105, NOMADS 32891, NOSFERATU 19017, PEEPING TOM 28917, PET SEMATARY 16004, PLANET TERROR 17526, PSYCHO III 3322, QUICKSILVER HIGHWAY 31164, RAWHEAD REX 5897, REPULSION 32894, RIDING THE BULLET 30671, SILVER BULLET 16247, SLEEPWALKERS 8436, SPIRITS OF THE DEAD 32367, STAGE FRIGHT 23284, STEPHEN KING 39265, STORAGE 24 34349, SVENGALI 5932, TERRORVISION 14072, THE ABOMINABLE DR. PHIBES 12781, THE ALLIGATOR PEOPLE 13151, THE BAD SEED 17361, THE BRAIN THAT WOULDN'T DIE 25829, THE CABINET OF DR. CALIGARI 31239, THE CAT AND THE CANARY 38676, THE CREEPING FLESH 24990, THE CURSE OF FRANKENSTEIN 25979, THE DARK HALF 26351, THE DEAD ZONE 38265, THE DEVIL-DOLL 32732, THE DOCTOR AND THE DEVILS 23327, THE FEARLESS VAMPIRE KILLERS 32392, THE FLY 28048, THE GHOST BREAKERS 14113, THE GHOUL 14382, THE GORGON 5813, THE HAND 25175, THE HAUNTED PALACE 11787, THE HAUNTING 31283, THE HOUND OF THE BASKERVILLES 22212, THE HOUSE THAT DRIPPED BLOOD 32595, THE HOWLING 15198, THE HUNCHBACK OF NOTRE DAME 29358, THE HUNGER 27780, THE INNOCENTS 34005, THE INVISIBLE MAN 10379, THE LAWNMOWER MAN 8623, THE LEGEND OF HELL HOUSE 33794, THE LITTLE SHOP OF HORRORS 29109, THE LODGER 26566, THE MANGLER 11243, THE MASQUE OF THE RED DEATH 33919, THE MIST 26820, THE MUMMY 40021, THE NIGHT FLIER 8727, THE PICTURE OF DORIAN GRAY 1565, THE PLAGUE OF THE ZOMBIES 18162, THE RAVEN 10186, THE REVENGE OF FRANKENSTEIN 1143, THE SEVENTH VICTIM 19018, THE SHINING 23847, THE STEPFORD WIVES 23260, THE SWARM 33991, THE TERROR 9715, THE TEXAS CHAINSAW MASSACRE 2 19823, THE UNKNOWN 22751, THE WICKER MAN 6833, THE WITCHES 3594, THEATRE OF BLOOD 14444, THEM! 7808, THINNER 1596, TORTURE GARDEN 17409, TRICK OR TREAT 29370, TROG 31252, V/H/S 36374, VILLAGE OF THE DAMNED 28352, WHITE ZOMBIE 36013, WITCHBOARD 6037, WITCHFINDER GENERAL src, edge_attr, dst 35747, has_genre, 5870 35747, has_tags, 5870 35747, has_tags, 23284 35747, written_by, 23284 18899, has_genre, 5870 18899, has_tags, 10045 39750, has_tags, 5870 39750, release_year, 28171 18169, has_genre, 5870 18169, release_year, 28171 19826, has_genre, 5870 19826, has_tags, 10045 26014, has_genre, 5870 26014, has_tags, 10045 32620, has_tags, 10045 32620, has_tags, 5870 24454, has_genre, 5870 24454, has_tags, 5870 24454, has_tags, 23284 24454, written_by, 23284 37912, has_genre, 5870 37912, has_tags, 10045 28328, has_genre, 5870 28328, has_tags, 23284 28328, written_by, 23284 5741, has_genre, 5870 5741, has_tags, 23284 5741, written_by, 23284 36535, has_genre, 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5870 6833, has_tags, 10045 3594, has_genre, 5870 3594, has_tags, 10045 14444, has_genre, 5870 14444, has_tags, 10045 14444, has_tags, 5870 7808, has_genre, 5870 7808, has_tags, 23284 7808, written_by, 23284 1596, has_genre, 5870 1596, has_tags, 10045 17409, has_genre, 5870 17409, release_year, 28171 29370, has_genre, 5870 29370, has_tags, 10045 31252, has_genre, 5870 31252, has_tags, 10045 31252, has_tags, 5870 36374, has_genre, 5870 36374, has_tags, 10045 28352, has_genre, 5870 28352, has_tags, 10045 36013, has_genre, 5870 36013, release_year, 28171 6037, has_genre, 5870 6037, has_tags, 10045 Question: For what reason are MARC BRANDEL, MAXIMUM OVERDRIVE, and MYRNA FAHEY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MARC BRANDEL", "MAXIMUM OVERDRIVE", "MYRNA FAHEY" ], "valid_edges": [ [ "1408", "has_genre", "HORROR" ], [ "1408", "has_tags", "HORROR" ], [ "1408", "has_tags", "STEPHEN KING" ], [ "1408", "written_by", "STEPHEN KING" ], [ "A BUCKET OF BLOOD", "has_genre", "HORROR" ], [ "A BUCKET OF BLOOD", "has_tags", "BD-R" ], [ "ALIENS", "has_tags", "HORROR" ], [ "ALIENS", "release_year", "1986" ], [ "APRIL FOOL'S DAY", "has_genre", "HORROR" ], [ "APRIL FOOL'S DAY", "release_year", "1986" ], [ "BLACK DEATH", "has_genre", "HORROR" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLOOD OF THE VAMPIRE", "has_genre", "HORROR" ], [ "BLOOD OF THE VAMPIRE", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "HORROR" ], [ "CARRIE", "has_genre", "HORROR" ], [ "CARRIE", "has_tags", "HORROR" ], [ "CARRIE", "has_tags", "STEPHEN KING" ], [ "CARRIE", "written_by", "STEPHEN KING" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "has_tags", "BD-R" ], [ "CAT'S EYE", "has_genre", "HORROR" ], [ "CAT'S EYE", "has_tags", "STEPHEN KING" ], [ "CAT'S EYE", "written_by", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "has_genre", "HORROR" ], [ "CHILDREN OF THE CORN", "has_tags", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "written_by", "STEPHEN KING" ], [ "CHOPPING MALL", "has_genre", "HORROR" ], [ "CHOPPING MALL", "release_year", "1986" ], [ "CHRISTINE", "has_genre", "HORROR" ], [ "CHRISTINE", "has_tags", "STEPHEN KING" ], [ "CHRISTINE", "written_by", "STEPHEN KING" ], [ "CLASS OF NUKE 'EM HIGH", "has_genre", "HORROR" ], [ "CLASS OF NUKE 'EM HIGH", "release_year", "1986" ], [ "CRAWLSPACE", "has_genre", "HORROR" ], [ "CRAWLSPACE", "release_year", "1986" ], [ "CREEPSHOW", "has_genre", "HORROR" ], [ "CREEPSHOW", "written_by", "STEPHEN KING" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "has_tags", "STEPHEN KING" ], [ "CREEPSHOW 2", "written_by", "STEPHEN KING" ], [ "CRITTERS", "has_genre", "HORROR" ], [ "CRITTERS", "release_year", "1986" ], [ "CUJO", "has_genre", "HORROR" ], [ "CUJO", "has_tags", "STEPHEN KING" ], [ "CUJO", "written_by", "STEPHEN KING" ], [ "DEAD OF NIGHT", "has_genre", "HORROR" ], [ "DEAD OF NIGHT", "has_tags", "BD-R" ], [ "DEADLY FRIEND", "has_genre", "HORROR" ], [ "DEADLY FRIEND", "release_year", "1986" ], [ "DEMENTIA 13", "has_genre", "HORROR" ], [ "DEMENTIA 13", "has_tags", "BD-R" ], [ "DEMONS 2", "has_genre", "HORROR" ], [ "DEMONS 2", "release_year", "1986" ], [ "DETOUR", "has_genre", "HORROR" ], [ "DETOUR", "has_tags", "BD-R" ], [ "DOCTOR X", "has_genre", "HORROR" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DONOVAN'S BRAIN", "has_genre", "HORROR" ], [ "DONOVAN'S BRAIN", "has_tags", "BD-R" ], [ "DR. JEKYLL AND MR. HYDE", "has_genre", "HORROR" ], [ "DR. JEKYLL AND MR. HYDE", "has_tags", "BD-R" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_genre", "HORROR" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_tags", "BD-R" ], [ "DRACULA'S DAUGHTER", "has_genre", "HORROR" ], [ "DRACULA'S DAUGHTER", "has_tags", "BD-R" ], [ "DREAMCATCHER", "has_genre", "HORROR" ], [ "DREAMCATCHER", "has_tags", "STEPHEN KING" ], [ "DREAMCATCHER", "written_by", "STEPHEN KING" ], [ "EYE OF THE DEVIL", "has_genre", "HORROR" ], [ "EYE OF THE DEVIL", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_genre", "HORROR" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_genre", "HORROR" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_tags", "BD-R" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "release_year", "1986" ], [ "GALAXY OF TERROR", "has_genre", "HORROR" ], [ "GALAXY OF TERROR", "has_tags", "BD-R" ], [ "GOTHIC", "has_genre", "HORROR" ], [ "GOTHIC", "release_year", "1986" ], [ "HANDS OF THE RIPPER", "has_genre", "HORROR" ], [ "HANDS OF THE RIPPER", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "HORROR" ], [ "HORROR EXPRESS", "has_genre", "HORROR" ], [ "HORROR EXPRESS", "has_tags", "BD-R" ], [ "HOUSE", "has_genre", "HORROR" ], [ "HOUSE", "release_year", "1986" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF USHER", "starred_actors", "MYRNA FAHEY" ], [ "HOUSE OF WAX", "has_genre", "HORROR" ], [ "HOUSE OF WAX", "has_tags", "BD-R" ], [ "INVADERS FROM MARS", "has_genre", "HORROR" ], [ "INVADERS FROM MARS", "release_year", "1986" ], [ "LINK", "has_genre", "HORROR" ], [ "LINK", "release_year", "1986" ], [ "LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "LITTLE SHOP OF HORRORS", "release_year", "1986" ], [ "MACABRE", "has_genre", "HORROR" ], [ "MACABRE", "has_tags", "BD-R" ], [ "MAD LOVE", "has_genre", "HORROR" ], [ "MAD LOVE", "has_tags", "BD-R" ], [ "MADHOUSE", 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"1986" ], [ "QUICKSILVER HIGHWAY", "has_genre", "HORROR" ], [ "QUICKSILVER HIGHWAY", "written_by", "STEPHEN KING" ], [ "RAWHEAD REX", "has_genre", "HORROR" ], [ "RAWHEAD REX", "release_year", "1986" ], [ "REPULSION", "has_genre", "HORROR" ], [ "REPULSION", "has_tags", "BD-R" ], [ "RIDING THE BULLET", "has_genre", "HORROR" ], [ "RIDING THE BULLET", "has_tags", "STEPHEN KING" ], [ "RIDING THE BULLET", "written_by", "STEPHEN KING" ], [ "SILVER BULLET", "has_genre", "HORROR" ], [ "SILVER BULLET", "has_tags", "STEPHEN KING" ], [ "SILVER BULLET", "written_by", "STEPHEN KING" ], [ "SLEEPWALKERS", "has_genre", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "STEPHEN KING" ], [ "SLEEPWALKERS", "written_by", "STEPHEN KING" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "STAGE FRIGHT", "has_genre", "HORROR" ], [ "STAGE FRIGHT", "has_tags", "BD-R" ], [ "STORAGE 24", "has_genre", "HORROR" ], [ "STORAGE 24", "has_tags", "BD-R" ], [ "SVENGALI", "has_genre", "HORROR" ], [ "SVENGALI", "has_tags", "BD-R" ], [ "TERRORVISION", "has_genre", "HORROR" ], [ "TERRORVISION", "release_year", "1986" ], [ "THE ABOMINABLE DR. PHIBES", "has_genre", "HORROR" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "BD-R" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_genre", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_tags", "BD-R" ], [ "THE BAD SEED", "has_genre", "HORROR" ], [ "THE BAD SEED", "has_tags", "BD-R" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_tags", "BD-R" ], [ "THE CABINET OF DR. CALIGARI", "has_genre", "HORROR" ], [ "THE CABINET OF DR. CALIGARI", "has_tags", "BD-R" ], [ "THE CAT AND THE CANARY", "has_genre", "HORROR" ], [ "THE CAT AND THE CANARY", "has_tags", "BD-R" ], [ "THE CREEPING FLESH", "has_genre", "HORROR" ], [ "THE CREEPING FLESH", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "HORROR" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "has_tags", "STEPHEN KING" ], [ "THE DARK HALF", "written_by", "STEPHEN KING" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "has_tags", "STEPHEN KING" ], [ "THE DEAD ZONE", "written_by", "STEPHEN KING" ], [ "THE DEVIL-DOLL", "has_genre", "HORROR" ], [ "THE DEVIL-DOLL", "has_tags", "BD-R" ], [ "THE DOCTOR AND THE DEVILS", "has_genre", "HORROR" ], [ "THE DOCTOR AND THE DEVILS", "has_tags", "BD-R" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_genre", "HORROR" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_tags", "BD-R" ], [ "THE FLY", "has_genre", "HORROR" ], [ "THE FLY", "has_tags", "HORROR" ], [ "THE FLY", "release_year", "1986" ], [ "THE GHOST BREAKERS", "has_genre", "HORROR" ], [ "THE GHOST BREAKERS", "has_tags", "BD-R" ], [ "THE GHOUL", "has_genre", "HORROR" ], [ "THE GHOUL", "has_tags", "BD-R" ], [ "THE GORGON", "has_genre", "HORROR" ], [ "THE GORGON", "has_tags", "BD-R" ], [ "THE HAND", "has_genre", "HORROR" ], [ "THE HAND", "written_by", "MARC BRANDEL" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_genre", "HORROR" ], [ "THE HAUNTING", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_tags", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_genre", "HORROR" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_tags", "BD-R" ], [ "THE HOWLING", "has_genre", "HORROR" ], [ "THE HOWLING", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "HORROR" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNGER", "has_genre", "HORROR" ], [ "THE HUNGER", "has_tags", "BD-R" ], [ "THE INNOCENTS", "has_genre", "HORROR" ], [ "THE INNOCENTS", "has_tags", "BD-R" ], [ "THE INVISIBLE MAN", "has_genre", "HORROR" ], [ "THE INVISIBLE MAN", "has_tags", "BD-R" ], [ "THE LAWNMOWER MAN", "has_genre", "HORROR" ], [ "THE LAWNMOWER MAN", "written_by", "STEPHEN KING" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "BD-R" ], [ "THE LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "THE LITTLE SHOP OF HORRORS", "has_tags", "BD-R" ], [ "THE LODGER", "has_genre", "HORROR" ], [ "THE LODGER", "has_tags", "BD-R" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "has_tags", "STEPHEN KING" ], [ "THE MANGLER", "written_by", "STEPHEN KING" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "BD-R" ], [ "THE MIST", "has_genre", "HORROR" ], [ "THE MIST", "has_tags", "STEPHEN KING" ], [ "THE MIST", "written_by", "STEPHEN KING" ], [ "THE MUMMY", "has_genre", "HORROR" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE MUMMY", "has_tags", "HORROR" ], [ "THE NIGHT FLIER", "has_genre", "HORROR" ], [ "THE NIGHT FLIER", "written_by", "STEPHEN KING" ], [ "THE PICTURE OF DORIAN GRAY", "has_genre", "HORROR" ], [ "THE PICTURE OF DORIAN GRAY", "has_tags", "BD-R" ], [ "THE PLAGUE OF THE ZOMBIES", "has_genre", "HORROR" ], [ "THE PLAGUE OF THE ZOMBIES", "has_tags", "BD-R" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "BD-R" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE SEVENTH VICTIM", "has_genre", "HORROR" ], [ "THE SEVENTH VICTIM", "has_tags", "BD-R" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "STEPHEN KING" ], [ "THE SHINING", "written_by", "STEPHEN KING" ], [ "THE STEPFORD WIVES", "has_genre", "HORROR" ], [ "THE STEPFORD WIVES", "has_tags", "BD-R" ], [ "THE SWARM", "has_genre", "HORROR" ], [ "THE SWARM", "has_tags", "BD-R" ], [ "THE TERROR", "has_genre", "HORROR" ], [ "THE TERROR", "has_tags", "BD-R" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_genre", "HORROR" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "has_tags", "HORROR" ], [ "THE TEXAS CHAINSAW MASSACRE 2", "release_year", "1986" ], [ "THE UNKNOWN", "has_genre", "HORROR" ], [ "THE UNKNOWN", "has_tags", "BD-R" ], [ "THE WICKER MAN", "has_genre", "HORROR" ], [ "THE WICKER MAN", "has_tags", "BD-R" ], [ "THE WITCHES", "has_genre", "HORROR" ], [ "THE WITCHES", "has_tags", "BD-R" ], [ "THEATRE OF BLOOD", "has_genre", "HORROR" ], [ "THEATRE OF BLOOD", "has_tags", "BD-R" ], [ "THEM!", "has_genre", "HORROR" ], [ "THEM!", "has_tags", "BD-R" ], [ "THEM!", "has_tags", "HORROR" ], [ "THINNER", "has_genre", "HORROR" ], [ "THINNER", "has_tags", "STEPHEN KING" ], [ "THINNER", "written_by", "STEPHEN KING" ], [ "TORTURE GARDEN", "has_genre", "HORROR" ], [ "TORTURE GARDEN", "has_tags", "BD-R" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "release_year", "1986" ], [ "TROG", "has_genre", "HORROR" ], [ "TROG", "has_tags", "BD-R" ], [ "V/H/S", "has_genre", "HORROR" ], [ "V/H/S", "has_tags", "BD-R" ], [ "V/H/S", "has_tags", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_genre", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_tags", "BD-R" ], [ "WHITE ZOMBIE", "has_genre", "HORROR" ], [ "WHITE ZOMBIE", "has_tags", "BD-R" ], [ "WITCHBOARD", "has_genre", "HORROR" ], [ "WITCHBOARD", "release_year", "1986" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29157, BOCA 14724, CRIME 15631, EDWARD G. ROBINSON 32536, FLAVIO FREDERICO 19711, FRANK MCHUGH 2554, JOHN FARROW 25821, NIGHT HAS A THOUSAND EYES 20292, THE WIDOW FROM CHICAGO src, edge_attr, dst 29157, directed_by, 32536 29157, has_genre, 14724 29157, written_by, 32536 25821, directed_by, 2554 25821, has_tags, 2554 25821, starred_actors, 15631 20292, has_genre, 14724 20292, starred_actors, 15631 20292, starred_actors, 19711 Question: For what reason are FLAVIO FREDERICO, FRANK MCHUGH, and JOHN FARROW associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FLAVIO FREDERICO", "FRANK MCHUGH", "JOHN FARROW" ], "valid_edges": [ [ "BOCA", "directed_by", "FLAVIO FREDERICO" ], [ "BOCA", "has_genre", "CRIME" ], [ "BOCA", "written_by", "FLAVIO FREDERICO" ], [ "NIGHT HAS A THOUSAND EYES", "directed_by", "JOHN FARROW" ], [ "NIGHT HAS A THOUSAND EYES", "has_tags", "JOHN FARROW" ], [ "NIGHT HAS A THOUSAND EYES", "starred_actors", "EDWARD G. ROBINSON" ], [ "THE WIDOW FROM CHICAGO", "has_genre", "CRIME" ], [ "THE WIDOW FROM CHICAGO", "starred_actors", "EDWARD G. ROBINSON" ], [ "THE WIDOW FROM CHICAGO", "starred_actors", "FRANK MCHUGH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 10110, A TIME FOR KILLING 7687, ADVANCE TO THE REAR 23328, APPALOOSA 26781, CIMARRON 34347, COUNT THREE AND PRAY 18170, COWBOY 25442, GLENN FORD 8819, JUBAL 6417, LUST FOR GOLD 15037, OTIS 12214, PRAIRIE FEVER 7585, TEXAS 37288, THE COURTSHIP OF EDDIE'S FATHER 18466, THE DESPERADOES 10084, THE FASTEST GUN ALIVE 35340, THE MAN FROM THE ALAMO 28829, THE SECRET OF CONVICT LAKE 5394, THE SHEEPMAN 30942, THE VIOLENT MEN 36026, WESTERN src, edge_attr, dst 10110, has_genre, 36026 10110, starred_actors, 25442 7687, has_genre, 36026 7687, starred_actors, 25442 23328, has_genre, 36026 23328, has_tags, 36026 23328, release_year, 26762 26781, has_genre, 36026 26781, starred_actors, 25442 34347, has_genre, 36026 18170, has_genre, 36026 18170, starred_actors, 25442 8819, has_genre, 36026 8819, starred_actors, 25442 6417, has_genre, 36026 6417, starred_actors, 25442 15037, release_year, 26762 12214, has_genre, 36026 12214, release_year, 26762 7585, has_genre, 36026 7585, starred_actors, 25442 37288, starred_actors, 25442 18466, has_genre, 36026 18466, starred_actors, 25442 10084, has_genre, 36026 10084, starred_actors, 25442 35340, has_genre, 36026 35340, starred_actors, 25442 28829, has_genre, 36026 28829, starred_actors, 25442 5394, has_genre, 36026 5394, starred_actors, 25442 30942, has_genre, 36026 30942, starred_actors, 25442 Question: In what context are COUNT THREE AND PRAY, OTIS, and THE COURTSHIP OF EDDIE'S FATHER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "COUNT THREE AND PRAY", "OTIS", "THE COURTSHIP OF EDDIE'S FATHER" ], "valid_edges": [ [ "A TIME FOR KILLING", "has_genre", "WESTERN" ], [ "A TIME FOR KILLING", "starred_actors", "GLENN FORD" ], [ "ADVANCE TO THE REAR", "has_genre", "WESTERN" ], [ "ADVANCE TO THE REAR", "starred_actors", "GLENN FORD" ], [ "APPALOOSA", "has_genre", "WESTERN" ], [ "APPALOOSA", "has_tags", "WESTERN" ], [ "APPALOOSA", "release_year", "2008" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "starred_actors", "GLENN FORD" ], [ "COUNT THREE AND PRAY", "has_genre", "WESTERN" ], [ "COWBOY", "has_genre", "WESTERN" ], [ "COWBOY", "starred_actors", "GLENN FORD" ], [ "JUBAL", "has_genre", "WESTERN" ], [ "JUBAL", "starred_actors", "GLENN FORD" ], [ "LUST FOR GOLD", "has_genre", "WESTERN" ], [ "LUST FOR GOLD", "starred_actors", "GLENN FORD" ], [ "OTIS", "release_year", "2008" ], [ "PRAIRIE FEVER", "has_genre", "WESTERN" ], [ "PRAIRIE FEVER", "release_year", "2008" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "TEXAS", "starred_actors", "GLENN FORD" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "starred_actors", "GLENN FORD" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "GLENN FORD" ], [ "THE FASTEST GUN ALIVE", "has_genre", "WESTERN" ], [ "THE FASTEST GUN ALIVE", "starred_actors", "GLENN FORD" ], [ "THE MAN FROM THE ALAMO", "has_genre", "WESTERN" ], [ "THE MAN FROM THE ALAMO", "starred_actors", "GLENN FORD" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "starred_actors", "GLENN FORD" ], [ "THE SHEEPMAN", "has_genre", "WESTERN" ], [ "THE SHEEPMAN", "starred_actors", "GLENN FORD" ], [ "THE VIOLENT MEN", "has_genre", "WESTERN" ], [ "THE VIOLENT MEN", "starred_actors", "GLENN FORD" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36173, 1946 24818, 1992 30553, 7TH CAVALRY 12094, A LAWLESS STREET 12549, ALBUQUERQUE 27991, BADMAN'S TERRITORY 29926, BUCHANAN RIDES ALONE 34547, CANYON PASSAGE 8622, CAROLE EASTMAN 27943, CARSON CITY 18014, COMANCHE STATION 13930, DECISION AT SUNDOWN 22900, DUEL IN THE SUN 26417, FIVE EASY PIECES 17966, HANGMAN'S KNOT 25413, HELDORADO 32025, HIGH, WIDE, AND HANDSOME 21488, JACK NICHOLSON 13787, MAN IN THE SADDLE 24068, MAN TROUBLE 15797, MY DARLING CLEMENTINE 10835, RAGE AT DAWN 22364, RANDOLPH SCOTT 2314, RIDE LONESOME 4848, RIDE THE HIGH COUNTRY 30533, SANTA FE 21240, SEVEN MEN FROM NOW 15270, SHOOT-OUT AT MEDICINE BEND 36482, STUART SAMUELS 18466, THE DESPERADOES 25351, THE MAN BEHIND THE GUN 18556, THE SHOOTING 33389, THE SPOILERS 1144, THE TALL T 28632, THE VIRGINIAN 30844, VISIONS OF LIGHT 36026, WESTERN 5882, WESTERN UNION src, edge_attr, dst 30553, has_genre, 36026 30553, starred_actors, 22364 12094, has_genre, 36026 12094, starred_actors, 22364 12549, has_genre, 36026 12549, starred_actors, 22364 27991, has_genre, 36026 27991, release_year, 36173 27991, starred_actors, 22364 29926, has_genre, 36026 29926, starred_actors, 22364 34547, has_genre, 36026 34547, release_year, 36173 27943, has_genre, 36026 27943, starred_actors, 22364 18014, has_genre, 36026 18014, starred_actors, 22364 13930, has_genre, 36026 13930, starred_actors, 22364 22900, has_genre, 36026 22900, release_year, 36173 26417, has_tags, 21488 26417, starred_actors, 21488 26417, written_by, 8622 17966, has_genre, 36026 17966, starred_actors, 22364 25413, has_genre, 36026 25413, release_year, 36173 32025, has_genre, 36026 32025, starred_actors, 22364 13787, has_genre, 36026 13787, starred_actors, 22364 24068, has_tags, 21488 24068, release_year, 24818 24068, starred_actors, 21488 24068, written_by, 8622 15797, has_genre, 36026 15797, release_year, 36173 10835, has_genre, 36026 10835, starred_actors, 22364 2314, has_genre, 36026 2314, starred_actors, 22364 4848, has_genre, 36026 4848, has_tags, 22364 4848, starred_actors, 22364 30533, has_genre, 36026 30533, starred_actors, 22364 21240, has_genre, 36026 21240, starred_actors, 22364 15270, has_genre, 36026 15270, starred_actors, 22364 18466, has_genre, 36026 18466, starred_actors, 22364 25351, has_genre, 36026 25351, starred_actors, 22364 18556, has_genre, 36026 18556, has_tags, 21488 18556, starred_actors, 21488 18556, written_by, 8622 33389, has_genre, 36026 33389, starred_actors, 22364 1144, has_genre, 36026 1144, has_tags, 36026 1144, starred_actors, 22364 28632, has_genre, 36026 28632, release_year, 36173 30844, directed_by, 36482 30844, release_year, 24818 5882, has_genre, 36026 5882, starred_actors, 22364 Question: In what context are BADMAN'S TERRITORY, CAROLE EASTMAN, and STUART SAMUELS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BADMAN'S TERRITORY", "CAROLE EASTMAN", "STUART SAMUELS" ], "valid_edges": [ [ "7TH CAVALRY", "has_genre", "WESTERN" ], [ "7TH CAVALRY", "starred_actors", "RANDOLPH SCOTT" ], [ "A LAWLESS STREET", "has_genre", "WESTERN" ], [ "A LAWLESS STREET", "starred_actors", "RANDOLPH SCOTT" ], [ "ALBUQUERQUE", "has_genre", "WESTERN" ], [ "ALBUQUERQUE", "starred_actors", "RANDOLPH SCOTT" ], [ "BADMAN'S TERRITORY", "has_genre", "WESTERN" ], [ "BADMAN'S TERRITORY", "release_year", "1946" ], [ "BADMAN'S TERRITORY", "starred_actors", "RANDOLPH SCOTT" ], [ "BUCHANAN RIDES ALONE", "has_genre", "WESTERN" ], [ "BUCHANAN RIDES ALONE", "starred_actors", "RANDOLPH SCOTT" ], [ "CANYON PASSAGE", "has_genre", "WESTERN" ], [ "CANYON PASSAGE", "release_year", "1946" ], [ "CARSON CITY", "has_genre", "WESTERN" ], [ "CARSON CITY", "starred_actors", "RANDOLPH SCOTT" ], [ "COMANCHE STATION", "has_genre", "WESTERN" ], [ "COMANCHE STATION", "starred_actors", "RANDOLPH SCOTT" ], [ "DECISION AT SUNDOWN", "has_genre", "WESTERN" ], [ "DECISION AT SUNDOWN", "starred_actors", "RANDOLPH SCOTT" ], [ "DUEL IN THE SUN", "has_genre", "WESTERN" ], [ "DUEL IN THE SUN", "release_year", "1946" ], [ "FIVE EASY PIECES", "has_tags", "JACK NICHOLSON" ], [ "FIVE EASY PIECES", "starred_actors", "JACK NICHOLSON" ], [ "FIVE EASY PIECES", "written_by", "CAROLE EASTMAN" ], [ "HANGMAN'S KNOT", "has_genre", "WESTERN" ], [ "HANGMAN'S KNOT", "starred_actors", "RANDOLPH SCOTT" ], [ "HELDORADO", "has_genre", "WESTERN" ], [ "HELDORADO", "release_year", "1946" ], [ "HIGH, WIDE, AND HANDSOME", "has_genre", "WESTERN" ], [ "HIGH, WIDE, AND HANDSOME", "starred_actors", "RANDOLPH SCOTT" ], [ "MAN IN THE SADDLE", "has_genre", "WESTERN" ], [ "MAN IN THE SADDLE", "starred_actors", "RANDOLPH SCOTT" ], [ "MAN TROUBLE", "has_tags", "JACK NICHOLSON" ], [ "MAN TROUBLE", "release_year", "1992" ], [ "MAN TROUBLE", "starred_actors", "JACK NICHOLSON" ], [ "MAN TROUBLE", "written_by", "CAROLE EASTMAN" ], [ "MY DARLING CLEMENTINE", "has_genre", "WESTERN" ], [ "MY DARLING CLEMENTINE", "release_year", "1946" ], [ "RAGE AT DAWN", "has_genre", "WESTERN" ], [ "RAGE AT DAWN", "starred_actors", "RANDOLPH SCOTT" ], [ "RIDE LONESOME", "has_genre", "WESTERN" ], [ "RIDE LONESOME", "starred_actors", "RANDOLPH SCOTT" ], [ "RIDE THE HIGH COUNTRY", "has_genre", "WESTERN" ], [ "RIDE THE HIGH COUNTRY", "has_tags", "RANDOLPH SCOTT" ], [ "RIDE THE HIGH COUNTRY", "starred_actors", "RANDOLPH SCOTT" ], [ "SANTA FE", "has_genre", "WESTERN" ], [ "SANTA FE", "starred_actors", "RANDOLPH SCOTT" ], [ "SEVEN MEN FROM NOW", "has_genre", "WESTERN" ], [ "SEVEN MEN FROM NOW", "starred_actors", "RANDOLPH SCOTT" ], [ "SHOOT-OUT AT MEDICINE BEND", "has_genre", "WESTERN" ], [ "SHOOT-OUT AT MEDICINE BEND", "starred_actors", "RANDOLPH SCOTT" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "RANDOLPH SCOTT" ], [ "THE MAN BEHIND THE GUN", "has_genre", "WESTERN" ], [ "THE MAN BEHIND THE GUN", "starred_actors", "RANDOLPH SCOTT" ], [ "THE SHOOTING", "has_genre", "WESTERN" ], [ "THE SHOOTING", "has_tags", "JACK NICHOLSON" ], [ "THE SHOOTING", "starred_actors", "JACK NICHOLSON" ], [ "THE SHOOTING", "written_by", "CAROLE EASTMAN" ], [ "THE SPOILERS", "has_genre", "WESTERN" ], [ "THE SPOILERS", "starred_actors", "RANDOLPH SCOTT" ], [ "THE TALL T", "has_genre", "WESTERN" ], [ "THE TALL T", "has_tags", "WESTERN" ], [ "THE TALL T", "starred_actors", "RANDOLPH SCOTT" ], [ "THE VIRGINIAN", "has_genre", "WESTERN" ], [ "THE VIRGINIAN", "release_year", "1946" ], [ "VISIONS OF LIGHT", "directed_by", "STUART SAMUELS" ], [ "VISIONS OF LIGHT", "release_year", "1992" ], [ "WESTERN UNION", "has_genre", "WESTERN" ], [ "WESTERN UNION", "starred_actors", "RANDOLPH SCOTT" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 26277, A FEW GOOD MEN 31344, A LEAGUE OF THEIR OWN 9317, A RIVER RUNS THROUGH IT 35276, A TALE OF WINTER 36782, AFTERBURN 39584, AMERICAN ME 34836, ARTICLE 99 5247, BAD LIEUTENANT 5618, BREAKING THE RULES 25358, CAMERA 11673, CITY OF JOY 22229, CLAIRE OF THE MOON 2408, CRISSCROSS 7946, CROSSING THE BRIDGE 656, CRUSH 28562, DAENS 30624, DANCES WITH WOLVES 2890, DESERT HEARTS 33069, DOING TIME ON MAPLE DRIVE 36212, DRAMA 38483, EVERLASTING MOMENTS 18031, FAR AND AWAY 17947, FINAL ANALYSIS 8089, FOREVER YOUNG 35150, FRIED GREEN TOMATOES 9778, GLADIATOR 16491, GLENGARRY GLEN ROSS 35421, GO FISH 35838, GUNCRAZY 19463, HEDD WYN 3829, HERO 9849, HOUSE OF ANGELS 25277, HUSBANDS AND WIVES 19642, JUICE 34688, LAWS OF GRAVITY 191, LEAVING NORMAL 8635, LESBIAN 16441, LIGHT SLEEPER 2682, LORENZO'S OIL 14167, LOVE FIELD 7221, LOVE SICK 19549, MALCOLM X 29234, MICHAEL BLAKE 34536, MISTRESS 23375, NEWSIES 8720, OLIVIER, OLIVIER 8280, PARIAH 25678, PETER'S FRIENDS 27925, POISON IVY 38711, PURE COUNTRY 37297, RADIO FLYER 1844, ROMPER STOMPER 13542, SAVAGE NIGHTS 40001, SCENT OF A WOMAN 28758, SCHOOL TIES 30817, SHINING THROUGH 36604, SOUTH CENTRAL 24853, SPIDER LILIES 1432, STRICTLY BALLROOM 23746, THE BEST INTENTIONS 37993, THE BOYS OF ST. VINCENT 165, THE CRYING GAME 14308, THE LOVER 22217, THE MAMBO KINGS 25792, THE OAK 214, THE POWER OF ONE 11845, THE TURNING 22264, THE WATERDANCE 20210, THE WOMEN 36340, TRACES OF RED 22214, WAR 8611, ZEBRAHEAD src, edge_attr, dst 26277, has_genre, 36212 26277, has_tags, 36212 26277, release_year, 24818 31344, has_genre, 36212 31344, has_tags, 36212 31344, release_year, 24818 9317, has_genre, 36212 9317, release_year, 24818 35276, has_genre, 36212 35276, release_year, 24818 36782, has_genre, 36212 36782, release_year, 24818 39584, has_genre, 36212 39584, release_year, 24818 34836, has_genre, 36212 34836, release_year, 24818 5247, has_genre, 36212 5247, release_year, 24818 5618, has_genre, 36212 5618, release_year, 24818 11673, has_genre, 36212 11673, release_year, 24818 22229, has_genre, 36212 22229, has_tags, 8635 22229, release_year, 24818 2408, has_genre, 36212 2408, release_year, 24818 7946, has_genre, 36212 7946, release_year, 24818 656, has_genre, 36212 656, release_year, 24818 28562, has_genre, 36212 28562, release_year, 24818 30624, has_genre, 36212 30624, has_tags, 36212 30624, has_tags, 22214 30624, written_by, 29234 2890, has_genre, 36212 2890, has_tags, 8635 33069, has_genre, 36212 33069, release_year, 24818 38483, has_genre, 36212 38483, has_tags, 25358 38483, has_tags, 22214 18031, has_genre, 36212 18031, release_year, 24818 17947, has_genre, 36212 17947, release_year, 24818 8089, has_genre, 36212 8089, release_year, 24818 35150, has_genre, 36212 35150, has_tags, 36212 35150, has_tags, 8635 9778, has_genre, 36212 9778, has_tags, 36212 9778, release_year, 24818 16491, has_genre, 36212 16491, release_year, 24818 35421, has_genre, 36212 35421, has_tags, 8635 35838, has_genre, 36212 35838, release_year, 24818 19463, has_genre, 36212 19463, release_year, 24818 3829, has_genre, 36212 3829, release_year, 24818 9849, has_genre, 36212 9849, release_year, 24818 25277, has_genre, 36212 25277, release_year, 24818 19642, has_genre, 36212 19642, release_year, 24818 34688, has_genre, 36212 34688, release_year, 24818 191, has_genre, 36212 191, release_year, 24818 16441, has_genre, 36212 16441, release_year, 24818 2682, has_genre, 36212 2682, release_year, 24818 14167, has_genre, 36212 14167, release_year, 24818 7221, has_genre, 36212 7221, has_tags, 8635 19549, has_genre, 36212 19549, release_year, 24818 34536, has_genre, 36212 34536, release_year, 24818 23375, has_genre, 36212 23375, release_year, 24818 8720, has_genre, 36212 8720, release_year, 24818 8280, has_genre, 36212 8280, has_tags, 8635 25678, has_genre, 36212 25678, release_year, 24818 27925, has_genre, 36212 27925, release_year, 24818 38711, has_genre, 36212 38711, release_year, 24818 37297, has_genre, 36212 37297, release_year, 24818 1844, has_genre, 36212 1844, release_year, 24818 13542, has_genre, 36212 13542, release_year, 24818 40001, has_genre, 36212 40001, has_tags, 36212 40001, release_year, 24818 28758, has_genre, 36212 28758, release_year, 24818 30817, has_genre, 36212 30817, release_year, 24818 36604, has_genre, 36212 36604, release_year, 24818 24853, has_genre, 36212 24853, has_tags, 36212 24853, has_tags, 8635 1432, has_genre, 36212 1432, release_year, 24818 23746, has_genre, 36212 23746, release_year, 24818 37993, has_genre, 36212 37993, release_year, 24818 165, has_genre, 36212 165, release_year, 24818 14308, has_genre, 36212 14308, release_year, 24818 22217, has_genre, 36212 22217, release_year, 24818 25792, has_genre, 36212 25792, release_year, 24818 214, has_genre, 36212 214, release_year, 24818 11845, has_genre, 36212 11845, release_year, 24818 22264, has_genre, 36212 22264, release_year, 24818 20210, has_genre, 36212 20210, has_tags, 8635 36340, has_genre, 36212 36340, release_year, 24818 8611, has_genre, 36212 8611, release_year, 24818 Question: How are CAMERA, CLAIRE OF THE MOON, and MICHAEL BLAKE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CAMERA", "CLAIRE OF THE MOON", "MICHAEL BLAKE" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "release_year", "1992" ], [ "A LEAGUE OF THEIR OWN", "has_genre", "DRAMA" ], [ "A LEAGUE OF THEIR OWN", "has_tags", "DRAMA" ], [ "A LEAGUE OF THEIR OWN", "release_year", "1992" ], [ "A RIVER RUNS THROUGH IT", "has_genre", "DRAMA" ], [ "A RIVER RUNS THROUGH IT", "release_year", "1992" ], [ "A TALE OF WINTER", "has_genre", "DRAMA" ], [ "A TALE OF WINTER", "release_year", "1992" ], [ "AFTERBURN", "has_genre", "DRAMA" ], [ "AFTERBURN", "release_year", "1992" ], [ "AMERICAN ME", "has_genre", "DRAMA" ], [ "AMERICAN ME", "release_year", "1992" ], [ "ARTICLE 99", "has_genre", "DRAMA" ], [ "ARTICLE 99", "release_year", "1992" ], [ "BAD LIEUTENANT", "has_genre", "DRAMA" ], [ "BAD LIEUTENANT", "release_year", "1992" ], [ "BREAKING THE RULES", "has_genre", "DRAMA" ], [ "BREAKING THE RULES", "release_year", "1992" ], [ "CITY OF JOY", "has_genre", "DRAMA" ], [ "CITY OF JOY", "release_year", "1992" ], [ "CLAIRE OF THE MOON", "has_genre", "DRAMA" ], [ "CLAIRE OF THE MOON", "has_tags", "LESBIAN" ], [ "CLAIRE OF THE MOON", "release_year", "1992" ], [ "CRISSCROSS", "has_genre", "DRAMA" ], [ "CRISSCROSS", "release_year", "1992" ], [ "CROSSING THE BRIDGE", "has_genre", "DRAMA" ], [ "CROSSING THE BRIDGE", "release_year", "1992" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "1992" ], [ "DAENS", "has_genre", "DRAMA" ], [ "DAENS", "release_year", "1992" ], [ "DANCES WITH WOLVES", "has_genre", "DRAMA" ], [ "DANCES WITH WOLVES", "has_tags", "DRAMA" ], [ "DANCES WITH WOLVES", "has_tags", "WAR" ], [ "DANCES WITH WOLVES", "written_by", "MICHAEL BLAKE" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "has_tags", "LESBIAN" ], [ "DOING TIME ON MAPLE DRIVE", "has_genre", "DRAMA" ], [ "DOING TIME ON MAPLE DRIVE", "release_year", "1992" ], [ "EVERLASTING MOMENTS", "has_genre", "DRAMA" ], [ "EVERLASTING MOMENTS", "has_tags", "CAMERA" ], [ "EVERLASTING MOMENTS", "has_tags", "WAR" ], [ "FAR AND AWAY", "has_genre", "DRAMA" ], [ "FAR AND AWAY", "release_year", "1992" ], [ "FINAL ANALYSIS", "has_genre", "DRAMA" ], [ "FINAL ANALYSIS", "release_year", "1992" ], [ "FOREVER YOUNG", "has_genre", "DRAMA" ], [ "FOREVER YOUNG", "release_year", "1992" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "LESBIAN" ], [ "GLADIATOR", "has_genre", "DRAMA" ], [ "GLADIATOR", "has_tags", "DRAMA" ], [ "GLADIATOR", "release_year", "1992" ], [ "GLENGARRY GLEN ROSS", "has_genre", "DRAMA" ], [ "GLENGARRY GLEN ROSS", "release_year", "1992" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "LESBIAN" ], [ "GUNCRAZY", "has_genre", "DRAMA" ], [ "GUNCRAZY", "release_year", "1992" ], [ "HEDD WYN", "has_genre", "DRAMA" ], [ "HEDD WYN", "release_year", "1992" ], [ "HERO", "has_genre", "DRAMA" ], [ "HERO", "release_year", "1992" ], [ "HOUSE OF ANGELS", "has_genre", "DRAMA" ], [ "HOUSE OF ANGELS", "release_year", "1992" ], [ "HUSBANDS AND WIVES", "has_genre", "DRAMA" ], [ "HUSBANDS AND WIVES", "release_year", "1992" ], [ "JUICE", "has_genre", "DRAMA" ], [ "JUICE", "release_year", "1992" ], [ "LAWS OF GRAVITY", "has_genre", "DRAMA" ], [ "LAWS OF GRAVITY", "release_year", "1992" ], [ "LEAVING NORMAL", "has_genre", "DRAMA" ], [ "LEAVING NORMAL", "release_year", "1992" ], [ "LIGHT SLEEPER", "has_genre", "DRAMA" ], [ "LIGHT SLEEPER", "release_year", "1992" ], [ "LORENZO'S OIL", "has_genre", "DRAMA" ], [ "LORENZO'S OIL", "release_year", "1992" ], [ "LOVE FIELD", "has_genre", "DRAMA" ], [ "LOVE FIELD", "release_year", "1992" ], [ "LOVE SICK", "has_genre", "DRAMA" ], [ "LOVE SICK", "has_tags", "LESBIAN" ], [ "MALCOLM X", "has_genre", "DRAMA" ], [ "MALCOLM X", "release_year", "1992" ], [ "MISTRESS", "has_genre", "DRAMA" ], [ "MISTRESS", "release_year", "1992" ], [ "NEWSIES", "has_genre", "DRAMA" ], [ "NEWSIES", "release_year", "1992" ], [ "OLIVIER, OLIVIER", "has_genre", "DRAMA" ], [ "OLIVIER, OLIVIER", "release_year", "1992" ], [ "PARIAH", "has_genre", "DRAMA" ], [ "PARIAH", "has_tags", "LESBIAN" ], [ "PETER'S FRIENDS", "has_genre", "DRAMA" ], [ "PETER'S FRIENDS", "release_year", "1992" ], [ "POISON IVY", "has_genre", "DRAMA" ], [ "POISON IVY", "release_year", "1992" ], [ "PURE COUNTRY", "has_genre", "DRAMA" ], [ "PURE COUNTRY", "release_year", "1992" ], [ "RADIO FLYER", "has_genre", "DRAMA" ], [ "RADIO FLYER", "release_year", "1992" ], [ "ROMPER STOMPER", "has_genre", "DRAMA" ], [ "ROMPER STOMPER", "release_year", "1992" ], [ "SAVAGE NIGHTS", "has_genre", "DRAMA" ], [ "SAVAGE NIGHTS", "release_year", "1992" ], [ "SCENT OF A WOMAN", "has_genre", "DRAMA" ], [ "SCENT OF A WOMAN", "has_tags", "DRAMA" ], [ "SCENT OF A WOMAN", "release_year", "1992" ], [ "SCHOOL TIES", "has_genre", "DRAMA" ], [ "SCHOOL TIES", "release_year", "1992" ], [ "SHINING THROUGH", "has_genre", "DRAMA" ], [ "SHINING THROUGH", "release_year", "1992" ], [ "SOUTH CENTRAL", "has_genre", "DRAMA" ], [ "SOUTH CENTRAL", "release_year", "1992" ], [ "SPIDER LILIES", "has_genre", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "LESBIAN" ], [ "STRICTLY BALLROOM", "has_genre", "DRAMA" ], [ "STRICTLY BALLROOM", "release_year", "1992" ], [ "THE BEST INTENTIONS", "has_genre", "DRAMA" ], [ "THE BEST INTENTIONS", "release_year", "1992" ], [ "THE BOYS OF ST. VINCENT", "has_genre", "DRAMA" ], [ "THE BOYS OF ST. VINCENT", "release_year", "1992" ], [ "THE CRYING GAME", "has_genre", "DRAMA" ], [ "THE CRYING GAME", "release_year", "1992" ], [ "THE LOVER", "has_genre", "DRAMA" ], [ "THE LOVER", "release_year", "1992" ], [ "THE MAMBO KINGS", "has_genre", "DRAMA" ], [ "THE MAMBO KINGS", "release_year", "1992" ], [ "THE OAK", "has_genre", "DRAMA" ], [ "THE OAK", "release_year", "1992" ], [ "THE POWER OF ONE", "has_genre", "DRAMA" ], [ "THE POWER OF ONE", "release_year", "1992" ], [ "THE TURNING", "has_genre", "DRAMA" ], [ "THE TURNING", "release_year", "1992" ], [ "THE WATERDANCE", "has_genre", "DRAMA" ], [ "THE WATERDANCE", "release_year", "1992" ], [ "THE WOMEN", "has_genre", "DRAMA" ], [ "THE WOMEN", "has_tags", "LESBIAN" ], [ "TRACES OF RED", "has_genre", "DRAMA" ], [ "TRACES OF RED", "release_year", "1992" ], [ "ZEBRAHEAD", "has_genre", "DRAMA" ], [ "ZEBRAHEAD", "release_year", "1992" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 10702, 1991 1421, 2013 9377, 2014 15407, 29TH STREET 13170, A BRIGHTER SUMMER DAY 30736, A KISS BEFORE DYING 39705, A LITTLE STIFF 39289, ACTION 23683, ALL I WANT FOR CHRISTMAS 24177, ANIMATION 22321, ANNABELLA SCIORRA 4329, ANNETTE BENING 30578, ANOTHER YOU 11870, ANYTHING GOES 8688, AT PLAY IN THE FIELDS OF THE LORD 37608, AUSTRALIA 10045, BD-R 25570, BEAUTY AND THE BEAST 9414, BINGO 23922, BOB DENVER 1637, BOYZ N THE HOOD 21748, BRUCE WILLIS 13639, BUGSY 28295, CAREER OPPORTUNITIES 3343, CARNE 24274, CITY OF HOPE 15585, CITY SLICKERS 8484, CLASS ACTION 30463, COMEDY 29148, CRAZY SAFARI 14724, CRIME 8100, CURLY SUE 24841, DANNY AIELLO 31214, DEFENDING YOUR LIFE 29485, DELIRIOUS 37395, DEN OFRIVILLIGE GOLFAREN 14733, DIARY OF A HITMAN 31163, DIRECTORIAL DEBUT 12903, DISNEY 3160, DOC HOLLYWOOD 16978, DON'T TELL MOM THE BABYSITTER'S DEAD 36212, DRAMA 20846, DROP DEAD FRED 31008, DUTCH 31783, ENGLISH 36202, ERNEST SCARED STUPID 27930, EYES OF AN ANGEL 9791, FAIRY TALE 36066, FANTASY 38250, FATHER OF THE BRIDE 21606, FLIRTING 15589, FRANKIE AND JOHNNY 6012, FRENCH 35150, FRIED GREEN TOMATOES 34231, GENE HACKMAN 6480, GERMAN 11565, GOOD 36229, GRAND CANYON 18119, HE SAID, SHE SAID 34320, HEAR MY SONG 30939, HIGH HEELS 25610, HIGH STRUNG 22676, HOLLY HUNTER 8579, HOMICIDE 6546, HOT SHOTS! 39726, HUDSON HAWK 3909, IF LOOKS COULD KILL 32542, INTO THE WOODS 12389, JOBETH WILLIAMS 1841, JOE MANTEGNA 21996, JOHN CANDY 29019, JOHN HUGHES 528, JOHNNY STECCHINO 18391, JUNGLE FEVER 29911, KEVIN BACON 30015, KING RALPH 7439, L.A. STORY 29323, LIFE STINKS 26893, LITTLE MAN TATE 4139, MERYL STREEP 5678, MICHAEL J. FOX 14165, MISSISSIPPI MASALA 31100, MOBSTERS 24593, MUSICAL 33507, MY GIRL 34472, MY OWN PRIVATE IDAHO 32627, MYSTERY DATE 27118, NAKED LUNCH 5337, NATHAN LANE 37497, NATIONAL FILM REGISTRY 25620, NECESSARY ROUGHNESS 30144, NEW JACK CITY 40059, ONCE AROUND 32528, ONE GOOD COP 23735, ONLY THE LONELY 34288, ONLY YESTERDAY 30662, OSCAR 17667, OTHER PEOPLE'S MONEY 25715, P.G. WODEHOUSE 25824, PARADISE 21683, PARIS TROUT 32423, PERFECTLY NORMAL 36610, PHOEBE CATES 284, POISON 23297, PROBLEM CHILD 2 4584, PROOF 39, PURE LUCK 25772, PYRATES 29601, QUEENS LOGIC 33257, RAMBLING ROSE 15283, REGARDING HENRY 2373, RICHARD DREYFUSS 8379, ROMANCE 31600, RUBIN AND ED 11468, RUSH 18913, SALMONBERRIES 33291, SCORCHERS 33607, SEX AND ZEN 8932, SLACKER 38469, SLEEPING WITH THE ENEMY 11883, SOAPDISH 38762, SPEAKING OF THE DEVIL 24849, STEVE MARTIN 16219, STORY 29906, SUBURBAN COMMANDO 35064, SWITCH 33479, THANK YOU, JEEVES! 10559, THE ADJUSTER 8210, THE BUTCHER'S WIFE 4345, THE COMMITMENTS 252, THE DARK BACKWARD 16528, THE DOCTOR 20229, THE FISHER KING 21817, THE FIVE HEARTBEATS 32102, THE HARD WAY 34438, THE INDIAN RUNNER 37849, THE INNER CIRCLE 37565, THE LAST BOY SCOUT 35557, THE MAN IN THE MOON 12947, THE MARRYING MAN 15388, THE PRINCE OF TIDES 4037, THE RAPTURE 1545, THE SUPER 18296, THE SWEET RIDE 24811, THRILLER 13776, TOY SOLDIERS 30063, TRUE COLORS 26494, UNDER SUSPICION 33802, UNTIL THE END OF THE WORLD 24117, VOYAGER 24634, WESLEY SNIPES 7593, WHAT ABOUT BOB? 6397, WHERE ANGELS FEAR TO TREAD 1178, WHORE src, edge_attr, dst 15407, has_genre, 30463 15407, has_genre, 36212 15407, release_year, 10702 13170, has_genre, 36212 13170, release_year, 10702 30736, release_year, 9177 30736, release_year, 10702 39705, has_genre, 30463 39705, release_year, 10702 23683, has_genre, 30463 23683, release_year, 10702 30578, has_genre, 30463 30578, release_year, 10702 11870, has_genre, 24593 11870, in_language, 31783 11870, release_year, 9177 11870, written_by, 25715 8688, has_genre, 36212 8688, release_year, 10702 25570, has_genre, 24177 25570, has_genre, 36066 25570, has_tags, 24177 25570, has_tags, 12903 25570, has_tags, 9791 25570, has_tags, 36066 25570, has_tags, 24593 25570, has_tags, 37497 25570, has_tags, 16219 25570, in_language, 6012 25570, release_year, 10702 25570, release_year, 9377 9414, has_genre, 30463 9414, release_year, 10702 1637, has_genre, 36212 1637, has_imdb_rating, 11565 1637, has_tags, 31163 1637, has_tags, 36212 1637, has_tags, 37497 1637, release_year, 10702 13639, has_genre, 14724 13639, has_genre, 36212 13639, release_year, 10702 13639, starred_actors, 4329 28295, has_genre, 30463 28295, release_year, 10702 28295, written_by, 29019 3343, has_genre, 36212 3343, has_tags, 6012 3343, in_language, 6012 3343, release_year, 10702 24274, has_genre, 36212 24274, release_year, 10702 15585, has_genre, 30463 15585, release_year, 10702 8484, has_genre, 36212 8484, has_genre, 24811 8484, has_tags, 34231 8484, release_year, 10702 8484, starred_actors, 34231 29148, has_genre, 30463 29148, release_year, 10702 8100, directed_by, 29019 8100, has_genre, 30463 8100, has_genre, 36212 8100, has_tags, 29019 8100, release_year, 10702 8100, written_by, 29019 31214, has_genre, 30463 31214, has_genre, 36212 31214, has_genre, 36066 31214, has_tags, 4139 31214, release_year, 10702 29485, has_genre, 30463 29485, release_year, 10702 29485, starred_actors, 21996 37395, has_genre, 30463 37395, in_language, 31783 37395, release_year, 10702 14733, has_genre, 36212 14733, release_year, 10702 3160, has_genre, 30463 3160, has_tags, 30463 3160, has_tags, 5678 3160, release_year, 10702 3160, starred_actors, 5678 16978, has_genre, 30463 16978, release_year, 10702 20846, has_genre, 30463 20846, has_genre, 36066 20846, release_year, 10702 20846, starred_actors, 36610 31008, has_genre, 30463 31008, has_genre, 36212 31008, has_tags, 29019 31008, release_year, 10702 31008, starred_actors, 12389 31008, written_by, 29019 36202, has_genre, 30463 36202, release_year, 10702 27930, has_genre, 36212 27930, release_year, 10702 38250, has_genre, 30463 38250, has_imdb_rating, 11565 38250, has_tags, 10045 38250, has_tags, 30463 38250, has_tags, 24849 38250, release_year, 10702 38250, starred_actors, 24849 21606, has_genre, 36212 21606, has_genre, 8379 21606, has_tags, 37608 21606, release_year, 10702 15589, has_genre, 36212 15589, has_genre, 24593 15589, has_genre, 8379 15589, release_year, 10702 15589, starred_actors, 5337 35150, has_genre, 30463 35150, has_genre, 36212 35150, has_tags, 36212 35150, release_year, 10702 36229, has_genre, 36212 36229, release_year, 10702 18119, has_genre, 30463 18119, release_year, 10702 18119, starred_actors, 29911 18119, starred_actors, 5337 34320, has_genre, 30463 34320, release_year, 10702 30939, has_genre, 36212 30939, release_year, 10702 25610, has_genre, 30463 25610, release_year, 10702 8579, has_genre, 14724 8579, has_genre, 36212 8579, has_tags, 1841 8579, release_year, 10702 8579, starred_actors, 1841 6546, has_genre, 30463 6546, has_tags, 30463 6546, release_year, 10702 39726, has_genre, 39289 39726, has_genre, 30463 39726, has_tags, 21748 39726, has_tags, 30463 39726, release_year, 10702 39726, starred_actors, 21748 39726, starred_actors, 24841 39726, written_by, 21748 3909, has_genre, 39289 3909, has_genre, 30463 3909, release_year, 10702 32542, has_genre, 36066 32542, has_genre, 24593 32542, has_tags, 12903 32542, has_tags, 9791 32542, has_tags, 36066 32542, has_tags, 4139 32542, has_tags, 24593 32542, release_year, 10702 32542, release_year, 9377 528, has_genre, 30463 528, release_year, 10702 18391, has_genre, 36212 18391, has_genre, 8379 18391, release_year, 10702 18391, starred_actors, 22321 18391, starred_actors, 24634 30015, has_genre, 30463 30015, has_tags, 30463 30015, release_year, 10702 7439, has_genre, 30463 7439, has_genre, 36066 7439, has_tags, 24849 7439, has_tags, 16219 7439, release_year, 10702 7439, starred_actors, 24849 7439, written_by, 24849 29323, has_genre, 30463 29323, release_year, 10702 26893, has_genre, 36212 26893, has_tags, 31163 26893, release_year, 10702 14165, has_genre, 36212 14165, has_genre, 8379 14165, release_year, 10702 31100, has_genre, 14724 31100, has_genre, 36212 31100, release_year, 10702 33507, has_genre, 36212 33507, has_tags, 36212 33507, release_year, 10702 34472, has_genre, 36212 34472, release_year, 10702 32627, has_genre, 30463 32627, release_year, 10702 27118, has_genre, 36212 27118, in_language, 31783 27118, release_year, 10702 25620, has_genre, 30463 25620, release_year, 10702 30144, has_genre, 14724 30144, has_genre, 36212 30144, has_tags, 24634 30144, release_year, 10702 30144, starred_actors, 24634 40059, has_genre, 30463 40059, has_genre, 36212 40059, has_tags, 36212 40059, release_year, 10702 40059, starred_actors, 24841 40059, starred_actors, 22676 40059, starred_actors, 2373 32528, has_genre, 14724 32528, has_genre, 36212 32528, release_year, 10702 23735, has_genre, 30463 23735, release_year, 10702 23735, starred_actors, 21996 34288, has_genre, 24177 34288, has_genre, 36212 34288, release_year, 10702 30662, has_genre, 30463 30662, in_language, 31783 30662, release_year, 10702 17667, has_genre, 30463 17667, has_genre, 36212 17667, release_year, 10702 25824, has_genre, 30463 25824, has_genre, 36212 25824, has_genre, 8379 25824, in_language, 31783 25824, release_year, 10702 25824, release_year, 1421 25824, starred_actors, 22676 25824, starred_actors, 36610 21683, has_genre, 36212 21683, release_year, 10702 32423, has_genre, 30463 32423, release_year, 10702 284, has_genre, 36212 284, release_year, 10702 23297, has_genre, 30463 23297, release_year, 10702 4584, has_genre, 36212 4584, has_tags, 37608 4584, release_year, 10702 39, has_genre, 30463 39, release_year, 10702 25772, has_genre, 30463 25772, release_year, 10702 25772, starred_actors, 29911 29601, has_genre, 30463 29601, release_year, 10702 29601, starred_actors, 1841 29601, starred_actors, 29911 33257, has_genre, 36212 33257, release_year, 10702 15283, has_genre, 36212 15283, has_tags, 4329 15283, release_year, 10702 15283, starred_actors, 4329 31600, has_genre, 30463 31600, release_year, 10702 11468, has_genre, 14724 11468, has_genre, 36212 11468, release_year, 10702 11468, release_year, 1421 18913, has_genre, 36212 18913, in_language, 31783 18913, release_year, 10702 33291, has_genre, 36212 33291, release_year, 10702 33607, has_genre, 30463 33607, release_year, 10702 8932, has_genre, 30463 8932, has_genre, 36212 8932, release_year, 10702 38469, has_genre, 36212 38469, has_genre, 24811 38469, release_year, 10702 11883, has_genre, 30463 11883, has_tags, 30463 11883, release_year, 10702 38762, has_genre, 30463 38762, release_year, 10702 29906, has_genre, 39289 29906, has_genre, 30463 29906, release_year, 10702 35064, has_genre, 30463 35064, release_year, 10702 35064, starred_actors, 12389 33479, has_genre, 30463 33479, written_by, 25715 10559, has_genre, 36212 10559, release_year, 10702 8210, has_genre, 30463 8210, release_year, 10702 4345, has_genre, 30463 4345, has_genre, 36212 4345, release_year, 10702 252, has_genre, 30463 252, release_year, 10702 16528, has_genre, 36212 16528, release_year, 10702 20229, has_genre, 30463 20229, has_genre, 36212 20229, release_year, 10702 21817, has_genre, 36212 21817, release_year, 10702 32102, has_genre, 39289 32102, has_genre, 30463 32102, has_genre, 36212 32102, has_genre, 24593 32102, has_tags, 5678 32102, release_year, 10702 32102, starred_actors, 22321 32102, starred_actors, 5678 34438, has_genre, 36212 34438, release_year, 10702 37849, has_genre, 36212 37849, in_language, 31783 37849, release_year, 10702 37565, has_genre, 39289 37565, has_genre, 30463 37565, has_tags, 21748 37565, release_year, 10702 37565, starred_actors, 21748 35557, has_genre, 36212 35557, release_year, 10702 12947, has_genre, 30463 12947, release_year, 10702 15388, has_genre, 36212 15388, has_tags, 10045 15388, release_year, 10702 4037, has_genre, 36212 4037, release_year, 10702 1545, has_genre, 30463 1545, release_year, 10702 18296, has_genre, 36212 18296, starred_actors, 23922 13776, has_genre, 39289 13776, has_genre, 36212 13776, has_imdb_rating, 11565 13776, release_year, 10702 30063, has_genre, 36212 30063, release_year, 10702 26494, has_genre, 36212 26494, has_tags, 34231 26494, release_year, 10702 26494, starred_actors, 34231 33802, has_genre, 36212 33802, has_tags, 6480 33802, in_language, 6480 33802, release_year, 10702 24117, has_genre, 36212 24117, in_language, 31783 24117, in_language, 6480 24117, release_year, 10702 7593, has_genre, 30463 7593, has_tags, 2373 7593, release_year, 10702 7593, starred_actors, 2373 6397, has_genre, 36212 6397, release_year, 10702 1178, has_genre, 36212 1178, release_year, 10702 Question: How are 1991, BOB DENVER, and P.G. WODEHOUSE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1991", "BOB DENVER", "P.G. WODEHOUSE" ], "valid_edges": [ [ "29TH STREET", "has_genre", "COMEDY" ], [ "29TH STREET", "has_genre", "DRAMA" ], [ "29TH STREET", "release_year", "1991" ], [ "A BRIGHTER SUMMER DAY", "has_genre", "DRAMA" ], [ "A BRIGHTER SUMMER DAY", "release_year", "1991" ], [ "A KISS BEFORE DYING", "release_year", "1956" ], [ "A KISS BEFORE DYING", "release_year", "1991" ], [ "A LITTLE STIFF", "has_genre", "COMEDY" ], [ "A LITTLE STIFF", "release_year", "1991" ], [ "ALL I WANT FOR CHRISTMAS", "has_genre", "COMEDY" ], [ "ALL I WANT FOR CHRISTMAS", "release_year", "1991" ], [ "ANOTHER YOU", "has_genre", "COMEDY" ], [ "ANOTHER YOU", "release_year", "1991" ], [ "ANYTHING GOES", "has_genre", "MUSICAL" ], [ "ANYTHING GOES", "in_language", "ENGLISH" ], [ "ANYTHING GOES", "release_year", "1956" ], [ "ANYTHING GOES", "written_by", "P.G. WODEHOUSE" ], [ "AT PLAY IN THE FIELDS OF THE LORD", "has_genre", "DRAMA" ], [ "AT PLAY IN THE FIELDS OF THE LORD", "release_year", "1991" ], [ "BEAUTY AND THE BEAST", "has_genre", "ANIMATION" ], [ "BEAUTY AND THE BEAST", "has_genre", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "ANIMATION" ], [ "BEAUTY AND THE BEAST", "has_tags", "DISNEY" ], [ "BEAUTY AND THE BEAST", "has_tags", "FAIRY TALE" ], [ "BEAUTY AND THE BEAST", "has_tags", "FANTASY" ], [ "BEAUTY AND THE BEAST", "has_tags", "MUSICAL" ], [ "BEAUTY AND THE BEAST", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BEAUTY AND THE BEAST", "has_tags", "STORY" ], [ "BEAUTY AND THE BEAST", "in_language", "FRENCH" ], [ "BEAUTY AND THE BEAST", "release_year", "1991" ], [ "BEAUTY AND THE BEAST", "release_year", "2014" ], [ "BINGO", "has_genre", "COMEDY" ], [ "BINGO", "release_year", "1991" ], [ "BOYZ N THE HOOD", "has_genre", "DRAMA" ], [ "BOYZ N THE HOOD", "has_imdb_rating", "GOOD" ], [ "BOYZ N THE HOOD", "has_tags", "DIRECTORIAL DEBUT" ], [ "BOYZ N THE HOOD", "has_tags", "DRAMA" ], [ "BOYZ N THE HOOD", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BOYZ N THE HOOD", "release_year", "1991" ], [ "BUGSY", "has_genre", "CRIME" ], [ "BUGSY", "has_genre", "DRAMA" ], [ "BUGSY", "release_year", "1991" ], [ "BUGSY", "starred_actors", "ANNETTE BENING" ], [ "CAREER OPPORTUNITIES", "has_genre", "COMEDY" ], [ "CAREER OPPORTUNITIES", "release_year", "1991" ], [ "CAREER OPPORTUNITIES", "written_by", "JOHN HUGHES" ], [ "CARNE", "has_genre", "DRAMA" ], [ "CARNE", "has_tags", "FRENCH" ], [ "CARNE", "in_language", "FRENCH" ], [ "CARNE", "release_year", "1991" ], [ "CITY OF HOPE", "has_genre", "DRAMA" ], [ "CITY OF HOPE", "release_year", "1991" ], [ "CITY SLICKERS", "has_genre", "COMEDY" ], [ "CITY SLICKERS", "release_year", "1991" ], [ "CLASS ACTION", "has_genre", "DRAMA" ], [ "CLASS ACTION", "has_genre", "THRILLER" ], [ "CLASS ACTION", "has_tags", "GENE HACKMAN" ], [ "CLASS ACTION", "release_year", "1991" ], [ "CLASS ACTION", "starred_actors", "GENE HACKMAN" ], [ "CRAZY SAFARI", "has_genre", "COMEDY" ], [ "CRAZY SAFARI", "release_year", "1991" ], [ "CURLY SUE", "directed_by", "JOHN HUGHES" ], [ "CURLY SUE", "has_genre", "COMEDY" ], [ "CURLY SUE", "has_genre", "DRAMA" ], [ "CURLY SUE", "has_tags", "JOHN HUGHES" ], [ "CURLY SUE", "release_year", "1991" ], [ "CURLY SUE", "written_by", "JOHN HUGHES" ], [ "DEFENDING YOUR LIFE", "has_genre", "COMEDY" ], [ "DEFENDING YOUR LIFE", "has_genre", "DRAMA" ], [ "DEFENDING YOUR LIFE", "has_genre", "FANTASY" ], [ "DEFENDING YOUR LIFE", "has_tags", "MERYL STREEP" ], [ "DEFENDING YOUR LIFE", "release_year", "1991" ], [ "DELIRIOUS", "has_genre", "COMEDY" ], [ "DELIRIOUS", "release_year", "1991" ], [ "DELIRIOUS", "starred_actors", "JOHN CANDY" ], [ "DEN OFRIVILLIGE GOLFAREN", "has_genre", "COMEDY" ], [ "DEN OFRIVILLIGE GOLFAREN", "in_language", "ENGLISH" ], [ "DEN OFRIVILLIGE GOLFAREN", "release_year", "1991" ], [ "DIARY OF A HITMAN", "has_genre", "DRAMA" ], [ "DIARY OF A HITMAN", "release_year", "1991" ], [ "DOC HOLLYWOOD", "has_genre", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "COMEDY" ], [ "DOC HOLLYWOOD", "has_tags", "MICHAEL J. FOX" ], [ "DOC HOLLYWOOD", "release_year", "1991" ], [ "DOC HOLLYWOOD", "starred_actors", "MICHAEL J. FOX" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "has_genre", "COMEDY" ], [ "DON'T TELL MOM THE BABYSITTER'S DEAD", "release_year", "1991" ], [ "DROP DEAD FRED", "has_genre", "COMEDY" ], [ "DROP DEAD FRED", "has_genre", "FANTASY" ], [ "DROP DEAD FRED", "release_year", "1991" ], [ "DROP DEAD FRED", "starred_actors", "PHOEBE CATES" ], [ "DUTCH", "has_genre", "COMEDY" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "DUTCH", "has_tags", "JOHN HUGHES" ], [ "DUTCH", "release_year", "1991" ], [ "DUTCH", "starred_actors", "JOBETH WILLIAMS" ], [ "DUTCH", "written_by", "JOHN HUGHES" ], [ "ERNEST SCARED STUPID", "has_genre", "COMEDY" ], [ "ERNEST SCARED STUPID", "release_year", "1991" ], [ "EYES OF AN ANGEL", "has_genre", "DRAMA" ], [ "EYES OF AN ANGEL", "release_year", "1991" ], [ "FATHER OF THE BRIDE", "has_genre", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_tags", "BD-R" ], [ "FATHER OF THE BRIDE", "has_tags", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_tags", "STEVE MARTIN" ], [ "FATHER OF THE BRIDE", "release_year", "1991" ], [ "FATHER OF THE BRIDE", "starred_actors", "STEVE MARTIN" ], [ "FLIRTING", "has_genre", "DRAMA" ], [ "FLIRTING", "has_genre", "ROMANCE" ], [ "FLIRTING", "has_tags", "AUSTRALIA" ], [ "FLIRTING", "release_year", "1991" ], [ "FRANKIE AND JOHNNY", "has_genre", "DRAMA" ], [ "FRANKIE AND JOHNNY", "has_genre", "MUSICAL" ], [ "FRANKIE AND JOHNNY", "has_genre", "ROMANCE" ], [ "FRANKIE AND JOHNNY", "release_year", "1991" ], [ "FRANKIE AND JOHNNY", "starred_actors", "NATHAN LANE" ], [ "FRIED GREEN TOMATOES", "has_genre", "COMEDY" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "release_year", "1991" ], [ "GRAND CANYON", "has_genre", "DRAMA" ], [ "GRAND CANYON", "release_year", "1991" ], [ "HE SAID, SHE SAID", "has_genre", "COMEDY" ], [ "HE SAID, SHE SAID", "release_year", "1991" ], [ "HE SAID, SHE SAID", "starred_actors", "KEVIN BACON" ], [ "HE SAID, SHE SAID", "starred_actors", "NATHAN LANE" ], [ "HEAR MY SONG", "has_genre", "COMEDY" ], [ "HEAR MY SONG", "release_year", "1991" ], [ "HIGH HEELS", "has_genre", "DRAMA" ], [ "HIGH HEELS", "release_year", "1991" ], [ "HIGH STRUNG", "has_genre", "COMEDY" ], [ "HIGH STRUNG", "release_year", "1991" ], [ "HOMICIDE", "has_genre", "CRIME" ], [ "HOMICIDE", "has_genre", "DRAMA" ], [ "HOMICIDE", "has_tags", "JOE MANTEGNA" ], [ "HOMICIDE", "release_year", "1991" ], [ "HOMICIDE", "starred_actors", "JOE MANTEGNA" ], [ "HOT SHOTS!", "has_genre", "COMEDY" ], [ "HOT SHOTS!", "has_tags", "COMEDY" ], [ "HOT SHOTS!", "release_year", "1991" ], [ "HUDSON HAWK", "has_genre", "ACTION" ], [ "HUDSON HAWK", "has_genre", "COMEDY" ], [ "HUDSON HAWK", "has_tags", "BRUCE WILLIS" ], [ "HUDSON HAWK", "has_tags", "COMEDY" ], [ "HUDSON HAWK", "release_year", "1991" ], [ "HUDSON HAWK", "starred_actors", "BRUCE WILLIS" ], [ "HUDSON HAWK", "starred_actors", "DANNY AIELLO" ], [ "HUDSON HAWK", "written_by", "BRUCE WILLIS" ], [ "IF LOOKS COULD KILL", "has_genre", "ACTION" ], [ "IF LOOKS COULD KILL", "has_genre", "COMEDY" ], [ "IF LOOKS COULD KILL", "release_year", "1991" ], [ "INTO THE WOODS", "has_genre", "FANTASY" ], [ "INTO THE WOODS", "has_genre", "MUSICAL" ], [ "INTO THE WOODS", "has_tags", "DISNEY" ], [ "INTO THE WOODS", "has_tags", "FAIRY TALE" ], [ "INTO THE WOODS", "has_tags", "FANTASY" ], [ "INTO THE WOODS", "has_tags", "MERYL STREEP" ], [ "INTO THE WOODS", "has_tags", "MUSICAL" ], [ "INTO THE WOODS", "release_year", "1991" ], [ "INTO THE WOODS", "release_year", "2014" ], [ "JOHNNY STECCHINO", "has_genre", "COMEDY" ], [ "JOHNNY STECCHINO", "release_year", "1991" ], [ "JUNGLE FEVER", "has_genre", "DRAMA" ], [ "JUNGLE FEVER", "has_genre", "ROMANCE" ], [ "JUNGLE FEVER", "release_year", "1991" ], [ "JUNGLE FEVER", "starred_actors", "ANNABELLA SCIORRA" ], [ "JUNGLE FEVER", "starred_actors", "WESLEY SNIPES" ], [ "KING RALPH", "has_genre", "COMEDY" ], [ "KING RALPH", "has_tags", "COMEDY" ], [ "KING RALPH", "release_year", "1991" ], [ "L.A. STORY", "has_genre", "COMEDY" ], [ "L.A. STORY", "has_genre", "FANTASY" ], [ "L.A. STORY", "has_tags", "STEVE MARTIN" ], [ "L.A. STORY", "has_tags", "STORY" ], [ "L.A. STORY", "release_year", "1991" ], [ "L.A. STORY", "starred_actors", "STEVE MARTIN" ], [ "L.A. STORY", "written_by", "STEVE MARTIN" ], [ "LIFE STINKS", "has_genre", "COMEDY" ], [ "LIFE STINKS", "release_year", "1991" ], [ "LITTLE MAN TATE", "has_genre", "DRAMA" ], [ "LITTLE MAN TATE", "has_tags", "DIRECTORIAL DEBUT" ], [ "LITTLE MAN TATE", "release_year", "1991" ], [ "MISSISSIPPI MASALA", "has_genre", "DRAMA" ], [ "MISSISSIPPI MASALA", "has_genre", "ROMANCE" ], [ "MISSISSIPPI MASALA", "release_year", "1991" ], [ "MOBSTERS", "has_genre", "CRIME" ], [ "MOBSTERS", "has_genre", "DRAMA" ], [ "MOBSTERS", "release_year", "1991" ], [ "MY GIRL", "has_genre", "DRAMA" ], [ "MY GIRL", "has_tags", "DRAMA" ], [ "MY GIRL", "release_year", "1991" ], [ "MY OWN PRIVATE IDAHO", "has_genre", "DRAMA" ], [ "MY OWN PRIVATE IDAHO", "release_year", "1991" ], [ "MYSTERY DATE", "has_genre", "COMEDY" ], [ "MYSTERY DATE", "release_year", "1991" ], [ "NAKED LUNCH", "has_genre", "DRAMA" ], [ "NAKED LUNCH", "in_language", "ENGLISH" ], [ "NAKED LUNCH", "release_year", "1991" ], [ "NECESSARY ROUGHNESS", "has_genre", "COMEDY" ], [ "NECESSARY ROUGHNESS", "release_year", "1991" ], [ "NEW JACK CITY", "has_genre", "CRIME" ], [ "NEW JACK CITY", "has_genre", "DRAMA" ], [ "NEW JACK CITY", "has_tags", "WESLEY SNIPES" ], [ "NEW JACK CITY", "release_year", "1991" ], [ "NEW JACK CITY", "starred_actors", "WESLEY SNIPES" ], [ "ONCE AROUND", "has_genre", "COMEDY" ], [ "ONCE AROUND", "has_genre", "DRAMA" ], [ "ONCE AROUND", "has_tags", "DRAMA" ], [ "ONCE AROUND", "release_year", "1991" ], [ "ONCE AROUND", "starred_actors", "DANNY AIELLO" ], [ "ONCE AROUND", "starred_actors", "HOLLY HUNTER" ], [ "ONCE AROUND", "starred_actors", "RICHARD DREYFUSS" ], [ "ONE GOOD COP", "has_genre", "CRIME" ], [ "ONE GOOD COP", "has_genre", "DRAMA" ], [ "ONE GOOD COP", "release_year", "1991" ], [ "ONLY THE LONELY", "has_genre", "COMEDY" ], [ "ONLY THE LONELY", "release_year", "1991" ], [ "ONLY THE LONELY", "starred_actors", "JOHN CANDY" ], [ "ONLY YESTERDAY", "has_genre", "ANIMATION" ], [ "ONLY YESTERDAY", "has_genre", "DRAMA" ], [ "ONLY YESTERDAY", "release_year", "1991" ], [ "OSCAR", "has_genre", "COMEDY" ], [ "OSCAR", "in_language", "ENGLISH" ], [ "OSCAR", "release_year", "1991" ], [ "OTHER PEOPLE'S MONEY", "has_genre", "COMEDY" ], [ "OTHER PEOPLE'S MONEY", "has_genre", "DRAMA" ], [ "OTHER PEOPLE'S MONEY", "release_year", "1991" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "ROMANCE" ], [ "PARADISE", "in_language", "ENGLISH" ], [ "PARADISE", "release_year", "1991" ], [ "PARADISE", "release_year", "2013" ], [ "PARADISE", "starred_actors", "HOLLY HUNTER" ], [ "PARADISE", "starred_actors", "PHOEBE CATES" ], [ "PARIS TROUT", "has_genre", "DRAMA" ], [ "PARIS TROUT", "release_year", "1991" ], [ "PERFECTLY NORMAL", "has_genre", "COMEDY" ], [ "PERFECTLY NORMAL", "release_year", "1991" ], [ "POISON", "has_genre", "DRAMA" ], [ "POISON", "release_year", "1991" ], [ "PROBLEM CHILD 2", "has_genre", "COMEDY" ], [ "PROBLEM CHILD 2", "release_year", "1991" ], [ "PROOF", "has_genre", "DRAMA" ], [ "PROOF", "has_tags", "AUSTRALIA" ], [ "PROOF", "release_year", "1991" ], [ "PURE LUCK", "has_genre", "COMEDY" ], [ "PURE LUCK", "release_year", "1991" ], [ "PYRATES", "has_genre", "COMEDY" ], [ "PYRATES", "release_year", "1991" ], [ "PYRATES", "starred_actors", "KEVIN BACON" ], [ "QUEENS LOGIC", "has_genre", "COMEDY" ], [ "QUEENS LOGIC", "release_year", "1991" ], [ "QUEENS LOGIC", "starred_actors", "JOE MANTEGNA" ], [ "QUEENS LOGIC", "starred_actors", "KEVIN BACON" ], [ "RAMBLING ROSE", "has_genre", "DRAMA" ], [ "RAMBLING ROSE", "release_year", "1991" ], [ "REGARDING HENRY", "has_genre", "DRAMA" ], [ "REGARDING HENRY", "has_tags", "ANNETTE BENING" ], [ "REGARDING HENRY", "release_year", "1991" ], [ "REGARDING HENRY", "starred_actors", "ANNETTE BENING" ], [ "RUBIN AND ED", "has_genre", "COMEDY" ], [ "RUBIN AND ED", "release_year", "1991" ], [ "RUSH", "has_genre", "CRIME" ], [ "RUSH", "has_genre", "DRAMA" ], [ "RUSH", "release_year", "1991" ], [ "RUSH", "release_year", "2013" ], [ "SALMONBERRIES", "has_genre", "DRAMA" ], [ "SALMONBERRIES", "in_language", "ENGLISH" ], [ "SALMONBERRIES", "release_year", "1991" ], [ "SCORCHERS", "has_genre", "DRAMA" ], [ "SCORCHERS", "release_year", "1991" ], [ "SEX AND ZEN", "has_genre", "COMEDY" ], [ "SEX AND ZEN", "release_year", "1991" ], [ "SLACKER", "has_genre", "COMEDY" ], [ "SLACKER", "has_genre", "DRAMA" ], [ "SLACKER", "release_year", "1991" ], [ "SLEEPING WITH THE ENEMY", "has_genre", "DRAMA" ], [ "SLEEPING WITH THE ENEMY", "has_genre", "THRILLER" ], [ "SLEEPING WITH THE ENEMY", "release_year", "1991" ], [ "SOAPDISH", "has_genre", "COMEDY" ], [ "SOAPDISH", "has_tags", "COMEDY" ], [ "SOAPDISH", "release_year", "1991" ], [ "SPEAKING OF THE DEVIL", "has_genre", "COMEDY" ], [ "SPEAKING OF THE DEVIL", "release_year", "1991" ], [ "SUBURBAN COMMANDO", "has_genre", "ACTION" ], [ "SUBURBAN COMMANDO", "has_genre", "COMEDY" ], [ "SUBURBAN COMMANDO", "release_year", "1991" ], [ "SWITCH", "has_genre", "COMEDY" ], [ "SWITCH", "release_year", "1991" ], [ "SWITCH", "starred_actors", "JOBETH WILLIAMS" ], [ "THANK YOU, JEEVES!", "has_genre", "COMEDY" ], [ "THANK YOU, JEEVES!", "written_by", "P.G. WODEHOUSE" ], [ "THE ADJUSTER", "has_genre", "DRAMA" ], [ "THE ADJUSTER", "release_year", "1991" ], [ "THE BUTCHER'S WIFE", "has_genre", "COMEDY" ], [ "THE BUTCHER'S WIFE", "release_year", "1991" ], [ "THE COMMITMENTS", "has_genre", "COMEDY" ], [ "THE COMMITMENTS", "has_genre", "DRAMA" ], [ "THE COMMITMENTS", "release_year", "1991" ], [ "THE DARK BACKWARD", "has_genre", "COMEDY" ], [ "THE DARK BACKWARD", "release_year", "1991" ], [ "THE DOCTOR", "has_genre", "DRAMA" ], [ "THE DOCTOR", "release_year", "1991" ], [ "THE FISHER KING", "has_genre", "COMEDY" ], [ "THE FISHER KING", "has_genre", "DRAMA" ], [ "THE FISHER KING", "release_year", "1991" ], [ "THE FIVE HEARTBEATS", "has_genre", "DRAMA" ], [ "THE FIVE HEARTBEATS", "release_year", "1991" ], [ "THE HARD WAY", "has_genre", "ACTION" ], [ "THE HARD WAY", "has_genre", "COMEDY" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_genre", "MUSICAL" ], [ "THE HARD WAY", "has_tags", "MICHAEL J. FOX" ], [ "THE HARD WAY", "release_year", "1991" ], [ "THE HARD WAY", "starred_actors", "ANNABELLA SCIORRA" ], [ "THE HARD WAY", "starred_actors", "MICHAEL J. FOX" ], [ "THE INDIAN RUNNER", "has_genre", "DRAMA" ], [ "THE INDIAN RUNNER", "release_year", "1991" ], [ "THE INNER CIRCLE", "has_genre", "DRAMA" ], [ "THE INNER CIRCLE", "in_language", "ENGLISH" ], [ "THE INNER CIRCLE", "release_year", "1991" ], [ "THE LAST BOY SCOUT", "has_genre", "ACTION" ], [ "THE LAST BOY SCOUT", "has_genre", "COMEDY" ], [ "THE LAST BOY SCOUT", "has_tags", "BRUCE WILLIS" ], [ "THE LAST BOY SCOUT", "release_year", "1991" ], [ "THE LAST BOY SCOUT", "starred_actors", "BRUCE WILLIS" ], [ "THE MAN IN THE MOON", "has_genre", "DRAMA" ], [ "THE MAN IN THE MOON", "release_year", "1991" ], [ "THE MARRYING MAN", "has_genre", "COMEDY" ], [ "THE MARRYING MAN", "release_year", "1991" ], [ "THE PRINCE OF TIDES", "has_genre", "DRAMA" ], [ "THE PRINCE OF TIDES", "has_tags", "BD-R" ], [ "THE PRINCE OF TIDES", "release_year", "1991" ], [ "THE RAPTURE", "has_genre", "DRAMA" ], [ "THE RAPTURE", "release_year", "1991" ], [ "THE SUPER", "has_genre", "COMEDY" ], [ "THE SUPER", "release_year", "1991" ], [ "THE SWEET RIDE", "has_genre", "DRAMA" ], [ "THE SWEET RIDE", "starred_actors", "BOB DENVER" ], [ "TOY SOLDIERS", "has_genre", "ACTION" ], [ "TOY SOLDIERS", "has_genre", "DRAMA" ], [ "TOY SOLDIERS", "has_imdb_rating", "GOOD" ], [ "TOY SOLDIERS", "release_year", "1991" ], [ "TRUE COLORS", "has_genre", "DRAMA" ], [ "TRUE COLORS", "release_year", "1991" ], [ "UNDER SUSPICION", "has_genre", "DRAMA" ], [ "UNDER SUSPICION", "has_tags", "GENE HACKMAN" ], [ "UNDER SUSPICION", "release_year", "1991" ], [ "UNDER SUSPICION", "starred_actors", "GENE HACKMAN" ], [ "UNTIL THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "UNTIL THE END OF THE WORLD", "has_tags", "GERMAN" ], [ "UNTIL THE END OF THE WORLD", "in_language", "GERMAN" ], [ "UNTIL THE END OF THE WORLD", "release_year", "1991" ], [ "VOYAGER", "has_genre", "DRAMA" ], [ "VOYAGER", "in_language", "ENGLISH" ], [ "VOYAGER", "in_language", "GERMAN" ], [ "VOYAGER", "release_year", "1991" ], [ "WHAT ABOUT BOB?", "has_genre", "COMEDY" ], [ "WHAT ABOUT BOB?", "has_tags", "RICHARD DREYFUSS" ], [ "WHAT ABOUT BOB?", "release_year", "1991" ], [ "WHAT ABOUT BOB?", "starred_actors", "RICHARD DREYFUSS" ], [ "WHERE ANGELS FEAR TO TREAD", "has_genre", "DRAMA" ], [ "WHERE ANGELS FEAR TO TREAD", "release_year", "1991" ], [ "WHORE", "has_genre", "DRAMA" ], [ "WHORE", "release_year", "1991" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27410, ANGELS IN THE OUTFIELD 10072, CHRISTINE JEFFS 30463, COMEDY 36212, DRAMA 19463, HEDD WYN 6064, PAUL TURNER 8367, RAIN 29231, SUNSHINE CLEANING 16954, SYLVIA src, edge_attr, dst 27410, has_genre, 30463 19463, directed_by, 6064 19463, has_genre, 36212 8367, directed_by, 10072 8367, has_genre, 36212 8367, written_by, 10072 29231, directed_by, 10072 29231, has_genre, 30463 29231, has_genre, 36212 29231, has_tags, 10072 16954, directed_by, 10072 16954, has_genre, 36212 16954, has_tags, 10072 Question: How are ANGELS IN THE OUTFIELD, CHRISTINE JEFFS, and PAUL TURNER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANGELS IN THE OUTFIELD", "CHRISTINE JEFFS", "PAUL TURNER" ], "valid_edges": [ [ "ANGELS IN THE OUTFIELD", "has_genre", "COMEDY" ], [ "HEDD WYN", "directed_by", "PAUL TURNER" ], [ "HEDD WYN", "has_genre", "DRAMA" ], [ "RAIN", "directed_by", "CHRISTINE JEFFS" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "written_by", "CHRISTINE JEFFS" ], [ "SUNSHINE CLEANING", "directed_by", "CHRISTINE JEFFS" ], [ "SUNSHINE CLEANING", "has_genre", "COMEDY" ], [ "SUNSHINE CLEANING", "has_genre", "DRAMA" ], [ "SUNSHINE CLEANING", "has_tags", "CHRISTINE JEFFS" ], [ "SYLVIA", "directed_by", "CHRISTINE JEFFS" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "has_tags", "CHRISTINE JEFFS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39289, ACTION 8233, AJANTRIK 20356, APARAJITO 14600, APU TRILOGY 16154, ATTACK FORCE 9669, AUDREY WELLS 32624, BENGALI 18764, CHARULATA 35040, DAVID KENNEDY 36212, DRAMA 19204, GUINEVERE 37384, GUNDAY 25862, INDIA 11222, PATHER PANCHALI 28200, SATYAJIT RAY 15523, SOUMITRA CHATTERJEE 32531, THE WORLD OF APU 1491, TRILOGY 11544, UNDER THE TUSCAN SUN src, edge_attr, dst 8233, has_genre, 36212 8233, in_language, 32624 20356, directed_by, 28200 20356, has_genre, 36212 20356, has_tags, 14600 20356, has_tags, 25862 20356, has_tags, 28200 20356, has_tags, 1491 20356, in_language, 32624 20356, written_by, 28200 16154, has_genre, 39289 16154, starred_actors, 35040 18764, directed_by, 28200 18764, has_genre, 36212 18764, has_tags, 28200 18764, in_language, 32624 18764, starred_actors, 15523 18764, written_by, 28200 19204, directed_by, 9669 19204, has_genre, 36212 19204, written_by, 9669 37384, has_genre, 39289 37384, in_language, 32624 11222, directed_by, 28200 11222, has_genre, 36212 11222, has_tags, 14600 11222, has_tags, 25862 11222, has_tags, 28200 11222, has_tags, 1491 11222, in_language, 32624 11222, written_by, 28200 32531, directed_by, 28200 32531, has_genre, 36212 32531, has_tags, 14600 32531, has_tags, 25862 32531, has_tags, 28200 32531, in_language, 32624 32531, starred_actors, 15523 32531, written_by, 28200 11544, directed_by, 9669 11544, has_genre, 36212 11544, written_by, 9669 Question: For what reason are AUDREY WELLS, BENGALI, and DAVID KENNEDY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AUDREY WELLS", "BENGALI", "DAVID KENNEDY" ], "valid_edges": [ [ "AJANTRIK", "has_genre", "DRAMA" ], [ "AJANTRIK", "in_language", "BENGALI" ], [ "APARAJITO", "directed_by", "SATYAJIT RAY" ], [ "APARAJITO", "has_genre", "DRAMA" ], [ "APARAJITO", "has_tags", "APU TRILOGY" ], [ "APARAJITO", "has_tags", "INDIA" ], [ "APARAJITO", "has_tags", "SATYAJIT RAY" ], [ "APARAJITO", "has_tags", "TRILOGY" ], [ "APARAJITO", "in_language", "BENGALI" ], [ "APARAJITO", "written_by", "SATYAJIT RAY" ], [ "ATTACK FORCE", "has_genre", "ACTION" ], [ "ATTACK FORCE", "starred_actors", "DAVID KENNEDY" ], [ "CHARULATA", "directed_by", "SATYAJIT RAY" ], [ "CHARULATA", "has_genre", "DRAMA" ], [ "CHARULATA", "has_tags", "SATYAJIT RAY" ], [ "CHARULATA", "in_language", "BENGALI" ], [ "CHARULATA", "starred_actors", "SOUMITRA CHATTERJEE" ], [ "CHARULATA", "written_by", "SATYAJIT RAY" ], [ "GUINEVERE", "directed_by", "AUDREY WELLS" ], [ "GUINEVERE", "has_genre", "DRAMA" ], [ "GUINEVERE", "written_by", "AUDREY WELLS" ], [ "GUNDAY", "has_genre", "ACTION" ], [ "GUNDAY", "in_language", "BENGALI" ], [ "PATHER PANCHALI", "directed_by", "SATYAJIT RAY" ], [ "PATHER PANCHALI", "has_genre", "DRAMA" ], [ "PATHER PANCHALI", "has_tags", "APU TRILOGY" ], [ "PATHER PANCHALI", "has_tags", "INDIA" ], [ "PATHER PANCHALI", "has_tags", "SATYAJIT RAY" ], [ "PATHER PANCHALI", "has_tags", "TRILOGY" ], [ "PATHER PANCHALI", "in_language", "BENGALI" ], [ "PATHER PANCHALI", "written_by", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "directed_by", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "has_genre", "DRAMA" ], [ "THE WORLD OF APU", "has_tags", "APU TRILOGY" ], [ "THE WORLD OF APU", "has_tags", "INDIA" ], [ "THE WORLD OF APU", "has_tags", "SATYAJIT RAY" ], [ "THE WORLD OF APU", "in_language", "BENGALI" ], [ "THE WORLD OF APU", "starred_actors", "SOUMITRA CHATTERJEE" ], [ "THE WORLD OF APU", "written_by", "SATYAJIT RAY" ], [ "UNDER THE TUSCAN SUN", "directed_by", "AUDREY WELLS" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "written_by", "AUDREY WELLS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21931, 1941 24438, 1993 1006, 1996 33657, A NIGHT AT THE ROXBURY 26763, ACCIÓN MUTANTE 1274, ADDAMS FAMILY VALUES 19308, AIRBORNE 14296, ANOTHER STAKEOUT 35941, ANTZ 5658, BAD BOY BUBBY 3256, BHAJI ON THE BEACH 16023, BLUES BROTHERS 2000 37616, BORN YESTERDAY 10201, BRIAN YUZNA 36392, CANNIBAL! THE MUSICAL 37126, CASTLE FREAK 29831, CB4 11620, CELTIC PRIDE 16386, CITY HUNTER 30463, COMEDY 24459, CONEHEADS 4824, DAGON 6519, DAN AYKROYD 32420, DAVE 36009, DAZED AND CONFUSED 12688, DENNIS PAOLI 36492, DIAMONDS 21558, DOCTOR DETROIT 23612, DOLLS 30803, DOPPELGANGER 31407, DRAGNET 7815, DRÖMKÅKEN 29122, ED AND HIS DEAD MOTHER 254, EDMOND 28612, ELECTRIC DREAMS 20426, ERNEST RIDES AGAIN 10648, EVEN COWGIRLS GET THE BLUES 20441, EXIT TO EDEN 11065, FATAL INSTINCT 4297, FATHER HOOD 26053, FOR LOVE OR MONEY 278, FORTRESS 845, FREAKED 3270, FROM BEYOND 39198, GETTING AWAY WITH MURDER 29393, GHOSTBUSTERS 30959, GROSSE POINTE BLANK 4680, GROUNDHOG DAY 10918, GRUMPY OLD MEN 19871, GYPSY 25648, HEART AND SOULS 36376, HEXED 17578, HOCUS POCUS 5870, HORROR 5068, HOT SHOTS! PART DEUX 18026, INDIAN SUMMER 34092, IT CAME FROM HOLLYWOOD 37202, IT'S PAT 28152, JEFFREY COMBS 1841, JOE MANTEGNA 7228, JOSH AND S.A.M. 8587, KEN FOREE 27812, LA ESTRATEGIA DEL CARACOL 39841, LAST ACTION HERO 32278, LEPRECHAUN 12766, LIFE WITH MIKEY 9946, LOADED WEAPON 1 35654, LOOSE CANNONS 14647, LOVE BITES 16700, LOVECRAFT 17855, MACGRUBER 14587, MAD DOG AND GLORY 17663, MADE IN AMERICA 39670, MAN'S BEST FRIEND 28789, MANHATTAN MURDER MYSTERY 39913, MATINEE 19791, MEAN GIRLS 15787, MONEY FOR NOTHING 5930, MR. WONDERFUL 862, MRS. DOUBTFIRE 31377, MUCH ADO ABOUT NOTHING 8519, MY BOYFRIEND'S BACK 37465, MY FELLOW AMERICANS 28963, MY GIRL 2 25950, MY STEPMOTHER IS AN ALIEN 11905, NAKED IN NEW YORK 30766, NEIGHBORS 27284, PARIS, FRANCE 11005, PAUL KOSLO 35198, RAT 39358, RE-ANIMATOR 33471, ROBOT JOX 4602, ROOKIE OF THE YEAR 18201, SATURDAY NIGHT LIVE 12936, SGT. BILKO 26699, SHORT CUTS 31824, SIX DEGREES OF SEPARATION 36264, SLEEPLESS IN SEATTLE 30664, SMOKING/NO SMOKING 10666, SO I MARRIED AN AXE MURDERER 29811, SON IN LAW 19541, SPACE TRUCKERS 18657, SPIES LIKE US 11421, STEFANO QUANTESTORIE 29425, STEVE BARRON 18809, STUART GORDON 22718, STUART SAVES HIS FAMILY 40061, STUCK 25480, SUPER MARIO BROS. 27511, SUPERSTAR 39976, TEENAGE MUTANT NINJA TURTLES 27760, THE BEVERLY HILLBILLIES 26008, THE BLUES BROTHERS 12710, THE COUCH TRIP 23699, THE DENTIST 7087, THE GREAT OUTDOORS 39842, THE LADIES MAN 1648, THE METEOR MAN 37211, THE PIT AND THE PENDULUM 15471, THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM 7816, THE THREE MUSKETEERS 9725, THE WONDERFUL ICE CREAM SUIT 27619, THE WRONG TROUSERS 24929, THREE OF HEARTS 24811, THRILLER 18863, TRADING PLACES 31130, UNDERCOVER BLUES 25299, UNTAMED HEART 38839, WAYNE'S WORLD 5306, WAYNE'S WORLD 2 4857, WEEKEND AT BERNIE'S II 18181, WHO'S THE MAN? 1287, WILDER NAPALM 22756, WINDOW TO PARIS 30255, YOGI BEAR src, edge_attr, dst 21931, has_genre, 30463 21931, starred_actors, 6519 33657, has_genre, 30463 33657, has_tags, 18201 26763, has_genre, 30463 26763, release_year, 24438 1274, has_genre, 30463 1274, release_year, 24438 19308, has_genre, 30463 19308, has_tags, 30463 19308, release_year, 24438 14296, has_genre, 30463 14296, release_year, 24438 35941, has_genre, 30463 35941, starred_actors, 6519 5658, has_genre, 30463 5658, release_year, 24438 3256, has_genre, 30463 3256, release_year, 24438 16023, has_genre, 30463 16023, has_tags, 6519 16023, starred_actors, 6519 16023, written_by, 6519 37616, has_genre, 30463 37616, release_year, 24438 36392, has_genre, 30463 36392, has_tags, 30463 36392, release_year, 24438 37126, directed_by, 18809 37126, has_genre, 5870 37126, written_by, 18809 29831, has_genre, 30463 29831, release_year, 24438 11620, has_genre, 30463 11620, has_tags, 6519 11620, starred_actors, 6519 16386, has_genre, 30463 16386, release_year, 24438 24459, directed_by, 29425 24459, has_genre, 30463 24459, has_tags, 6519 24459, has_tags, 18201 24459, has_tags, 29425 24459, release_year, 24438 24459, starred_actors, 6519 24459, written_by, 6519 4824, directed_by, 18809 4824, has_genre, 5870 4824, written_by, 12688 32420, has_genre, 30463 32420, release_year, 24438 36009, has_genre, 30463 36009, release_year, 24438 36492, has_genre, 30463 36492, starred_actors, 6519 21558, has_genre, 30463 21558, starred_actors, 6519 23612, directed_by, 18809 23612, has_genre, 5870 23612, has_tags, 23612 30803, has_genre, 30463 30803, release_year, 24438 31407, has_genre, 30463 31407, starred_actors, 6519 31407, written_by, 6519 7815, has_genre, 30463 7815, release_year, 24438 29122, has_genre, 30463 29122, release_year, 24438 254, directed_by, 18809 254, has_genre, 24811 254, starred_actors, 1841 28612, directed_by, 29425 28612, has_genre, 30463 20426, has_genre, 30463 20426, release_year, 24438 10648, has_genre, 30463 10648, release_year, 24438 20441, has_genre, 30463 20441, starred_actors, 6519 11065, has_genre, 30463 11065, release_year, 24438 4297, has_genre, 30463 4297, release_year, 24438 26053, has_genre, 30463 26053, release_year, 24438 278, directed_by, 18809 278, has_genre, 24811 845, has_genre, 30463 845, release_year, 24438 3270, directed_by, 18809 3270, has_genre, 5870 3270, has_tags, 16700 3270, starred_actors, 28152 3270, starred_actors, 8587 3270, written_by, 10201 3270, written_by, 12688 3270, written_by, 18809 39198, has_genre, 30463 39198, starred_actors, 6519 29393, has_genre, 30463 29393, has_tags, 30463 29393, has_tags, 6519 29393, has_tags, 18201 29393, starred_actors, 6519 29393, written_by, 6519 30959, has_genre, 30463 30959, has_tags, 6519 30959, starred_actors, 6519 4680, has_genre, 30463 4680, has_tags, 30463 4680, release_year, 24438 10918, has_genre, 30463 10918, has_tags, 30463 10918, release_year, 24438 19871, has_genre, 30463 19871, release_year, 24438 25648, has_genre, 30463 25648, release_year, 24438 36376, has_genre, 30463 36376, release_year, 24438 17578, has_genre, 30463 17578, release_year, 24438 5068, has_genre, 30463 5068, has_tags, 30463 5068, release_year, 24438 18026, has_genre, 30463 18026, release_year, 24438 34092, has_genre, 30463 34092, starred_actors, 6519 37202, has_genre, 30463 37202, has_tags, 18201 7228, has_genre, 30463 7228, release_year, 24438 27812, has_genre, 30463 27812, release_year, 24438 39841, has_genre, 30463 39841, has_tags, 30463 39841, release_year, 24438 32278, has_genre, 30463 32278, release_year, 24438 12766, has_genre, 30463 12766, release_year, 24438 9946, has_genre, 30463 9946, release_year, 24438 35654, has_genre, 30463 35654, starred_actors, 6519 14647, has_genre, 30463 14647, release_year, 24438 17855, has_genre, 30463 17855, has_tags, 30463 17855, has_tags, 18201 14587, has_genre, 30463 14587, release_year, 24438 17663, has_genre, 30463 17663, release_year, 24438 39670, has_genre, 30463 39670, release_year, 24438 28789, has_genre, 30463 28789, release_year, 24438 39913, has_genre, 30463 39913, release_year, 24438 19791, has_genre, 30463 19791, has_tags, 30463 19791, has_tags, 18201 15787, has_genre, 30463 15787, release_year, 24438 5930, has_genre, 30463 5930, release_year, 24438 862, has_genre, 30463 862, has_tags, 30463 862, release_year, 24438 31377, has_genre, 30463 31377, has_tags, 30463 31377, release_year, 24438 8519, has_genre, 30463 8519, release_year, 24438 37465, has_genre, 30463 37465, has_tags, 6519 37465, starred_actors, 6519 28963, has_genre, 30463 28963, has_tags, 6519 28963, starred_actors, 6519 25950, has_genre, 30463 25950, starred_actors, 6519 11905, has_genre, 30463 11905, release_year, 24438 30766, has_genre, 30463 30766, starred_actors, 6519 27284, has_genre, 30463 27284, release_year, 24438 35198, directed_by, 29425 35198, has_genre, 30463 39358, directed_by, 18809 39358, has_genre, 30463 39358, has_genre, 5870 39358, has_tags, 5870 39358, has_tags, 16700 39358, starred_actors, 28152 39358, written_by, 18809 33471, directed_by, 18809 33471, starred_actors, 11005 33471, written_by, 18809 4602, has_genre, 30463 4602, release_year, 24438 12936, has_genre, 30463 12936, starred_actors, 6519 26699, has_genre, 30463 26699, release_year, 24438 31824, has_genre, 30463 31824, release_year, 24438 36264, has_genre, 30463 36264, has_tags, 30463 36264, release_year, 24438 30664, has_genre, 30463 30664, release_year, 24438 10666, has_genre, 30463 10666, has_tags, 30463 10666, release_year, 24438 29811, has_genre, 30463 29811, release_year, 24438 19541, directed_by, 18809 19541, has_genre, 30463 19541, release_year, 1006 19541, written_by, 18809 18657, has_genre, 30463 18657, starred_actors, 6519 18657, written_by, 6519 11421, has_genre, 30463 11421, release_year, 24438 22718, has_genre, 30463 22718, has_tags, 18201 40061, directed_by, 18809 40061, has_genre, 24811 40061, written_by, 18809 25480, has_genre, 30463 25480, has_tags, 30463 25480, release_year, 24438 27511, has_genre, 30463 27511, has_tags, 18201 39976, directed_by, 29425 39976, has_genre, 30463 39976, has_tags, 29425 27760, has_genre, 30463 27760, release_year, 24438 26008, has_genre, 30463 26008, has_tags, 30463 26008, has_tags, 6519 26008, has_tags, 18201 26008, starred_actors, 6519 26008, written_by, 6519 12710, has_genre, 30463 12710, starred_actors, 6519 23699, directed_by, 10201 23699, has_genre, 5870 23699, release_year, 1006 23699, starred_actors, 8587 23699, written_by, 12688 23699, written_by, 18809 7087, has_genre, 30463 7087, starred_actors, 6519 39842, has_genre, 30463 39842, has_tags, 18201 1648, has_genre, 30463 1648, release_year, 24438 37211, directed_by, 18809 37211, has_genre, 5870 15471, has_genre, 30463 15471, release_year, 24438 7816, has_genre, 30463 7816, release_year, 24438 9725, directed_by, 18809 9725, starred_actors, 1841 27619, has_genre, 30463 27619, has_tags, 30463 27619, release_year, 24438 24929, has_genre, 30463 24929, release_year, 24438 18863, has_genre, 30463 18863, has_tags, 30463 18863, has_tags, 6519 18863, starred_actors, 6519 31130, has_genre, 30463 31130, release_year, 24438 25299, has_genre, 30463 25299, release_year, 24438 38839, has_genre, 30463 38839, has_tags, 30463 38839, has_tags, 18201 5306, has_genre, 30463 5306, has_tags, 18201 5306, release_year, 24438 4857, has_genre, 30463 4857, release_year, 24438 18181, has_genre, 30463 18181, release_year, 24438 1287, has_genre, 30463 1287, release_year, 24438 22756, has_genre, 30463 22756, release_year, 24438 30255, has_genre, 30463 30255, starred_actors, 6519 Question: How are CONEHEADS, PAUL KOSLO, and STUART GORDON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CONEHEADS", "PAUL KOSLO", "STUART GORDON" ], "valid_edges": [ [ "1941", "has_genre", "COMEDY" ], [ "1941", "starred_actors", "DAN AYKROYD" ], [ "A NIGHT AT THE ROXBURY", "has_genre", "COMEDY" ], [ "A NIGHT AT THE ROXBURY", "has_tags", "SATURDAY NIGHT LIVE" ], [ "ACCIÓN MUTANTE", "has_genre", "COMEDY" ], [ "ACCIÓN MUTANTE", "release_year", "1993" ], [ "ADDAMS FAMILY VALUES", "has_genre", "COMEDY" ], [ "ADDAMS FAMILY VALUES", "release_year", "1993" ], [ "AIRBORNE", "has_genre", "COMEDY" ], [ "AIRBORNE", "has_tags", "COMEDY" ], [ "AIRBORNE", "release_year", "1993" ], [ "ANOTHER STAKEOUT", "has_genre", "COMEDY" ], [ "ANOTHER STAKEOUT", "release_year", "1993" ], [ "ANTZ", "has_genre", "COMEDY" ], [ "ANTZ", "starred_actors", "DAN AYKROYD" ], [ "BAD BOY BUBBY", "has_genre", "COMEDY" ], [ "BAD BOY BUBBY", "release_year", "1993" ], [ "BHAJI ON THE BEACH", "has_genre", "COMEDY" ], [ "BHAJI ON THE BEACH", "release_year", "1993" ], [ "BLUES BROTHERS 2000", "has_genre", "COMEDY" ], [ "BLUES BROTHERS 2000", "has_tags", "DAN AYKROYD" ], [ "BLUES BROTHERS 2000", "starred_actors", "DAN AYKROYD" ], [ "BLUES BROTHERS 2000", "written_by", "DAN AYKROYD" ], [ "BORN YESTERDAY", "has_genre", "COMEDY" ], [ "BORN YESTERDAY", "release_year", "1993" ], [ "CANNIBAL! THE MUSICAL", "has_genre", "COMEDY" ], [ "CANNIBAL! THE MUSICAL", "has_tags", "COMEDY" ], [ "CANNIBAL! THE MUSICAL", "release_year", "1993" ], [ "CASTLE FREAK", "directed_by", "STUART GORDON" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "written_by", "STUART GORDON" ], [ "CB4", "has_genre", "COMEDY" ], [ "CB4", "release_year", "1993" ], [ "CELTIC PRIDE", "has_genre", "COMEDY" ], [ "CELTIC PRIDE", "has_tags", "DAN AYKROYD" ], [ "CELTIC PRIDE", "starred_actors", "DAN AYKROYD" ], [ "CITY HUNTER", "has_genre", "COMEDY" ], [ "CITY HUNTER", "release_year", "1993" ], [ "CONEHEADS", "directed_by", "STEVE BARRON" ], [ "CONEHEADS", "has_genre", "COMEDY" ], [ "CONEHEADS", "has_tags", "DAN AYKROYD" ], [ "CONEHEADS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "CONEHEADS", "has_tags", "STEVE BARRON" ], [ "CONEHEADS", "release_year", "1993" ], [ "CONEHEADS", "starred_actors", "DAN AYKROYD" ], [ "CONEHEADS", "written_by", "DAN AYKROYD" ], [ "DAGON", "directed_by", "STUART GORDON" ], [ "DAGON", "has_genre", "HORROR" ], [ "DAGON", "written_by", "DENNIS PAOLI" ], [ "DAVE", "has_genre", "COMEDY" ], [ "DAVE", "release_year", "1993" ], [ "DAZED AND CONFUSED", "has_genre", "COMEDY" ], [ "DAZED AND CONFUSED", "release_year", "1993" ], [ "DIAMONDS", "has_genre", "COMEDY" ], [ "DIAMONDS", "starred_actors", "DAN AYKROYD" ], [ "DOCTOR DETROIT", "has_genre", "COMEDY" ], [ "DOCTOR DETROIT", "starred_actors", "DAN AYKROYD" ], [ "DOLLS", "directed_by", "STUART GORDON" ], [ "DOLLS", "has_genre", "HORROR" ], [ "DOLLS", "has_tags", "DOLLS" ], [ "DOPPELGANGER", "has_genre", "COMEDY" ], [ "DOPPELGANGER", "release_year", "1993" ], [ "DRAGNET", "has_genre", "COMEDY" ], [ "DRAGNET", "starred_actors", "DAN AYKROYD" ], [ "DRAGNET", "written_by", "DAN AYKROYD" ], [ "DRÖMKÅKEN", "has_genre", "COMEDY" ], [ "DRÖMKÅKEN", "release_year", "1993" ], [ "ED AND HIS DEAD MOTHER", "has_genre", "COMEDY" ], [ "ED AND HIS DEAD MOTHER", "release_year", "1993" ], [ "EDMOND", "directed_by", "STUART GORDON" ], [ "EDMOND", "has_genre", "THRILLER" ], [ "EDMOND", "starred_actors", "JOE MANTEGNA" ], [ "ELECTRIC DREAMS", "directed_by", "STEVE BARRON" ], [ "ELECTRIC DREAMS", "has_genre", "COMEDY" ], [ "ERNEST RIDES AGAIN", "has_genre", "COMEDY" ], [ "ERNEST RIDES AGAIN", "release_year", "1993" ], [ "EVEN COWGIRLS GET THE BLUES", "has_genre", "COMEDY" ], [ "EVEN COWGIRLS GET THE BLUES", "release_year", "1993" ], [ "EXIT TO EDEN", "has_genre", "COMEDY" ], [ "EXIT TO EDEN", "starred_actors", "DAN AYKROYD" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "release_year", "1993" ], [ "FATHER HOOD", "has_genre", "COMEDY" ], [ "FATHER HOOD", "release_year", "1993" ], [ "FOR LOVE OR MONEY", "has_genre", "COMEDY" ], [ "FOR LOVE OR MONEY", "release_year", "1993" ], [ "FORTRESS", "directed_by", "STUART GORDON" ], [ "FORTRESS", "has_genre", "THRILLER" ], [ "FREAKED", "has_genre", "COMEDY" ], [ "FREAKED", "release_year", "1993" ], [ "FROM BEYOND", "directed_by", "STUART GORDON" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "has_tags", "LOVECRAFT" ], [ "FROM BEYOND", "starred_actors", "JEFFREY COMBS" ], [ "FROM BEYOND", "starred_actors", "KEN FOREE" ], [ "FROM BEYOND", "written_by", "BRIAN YUZNA" ], [ "FROM BEYOND", "written_by", "DENNIS PAOLI" ], [ "FROM BEYOND", "written_by", "STUART GORDON" ], [ "GETTING AWAY WITH MURDER", "has_genre", "COMEDY" ], [ "GETTING AWAY WITH MURDER", "starred_actors", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "has_genre", "COMEDY" ], [ "GHOSTBUSTERS", "has_tags", "COMEDY" ], [ "GHOSTBUSTERS", "has_tags", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "GHOSTBUSTERS", "starred_actors", "DAN AYKROYD" ], [ "GHOSTBUSTERS", "written_by", "DAN AYKROYD" ], [ "GROSSE POINTE BLANK", "has_genre", "COMEDY" ], [ "GROSSE POINTE BLANK", "has_tags", "DAN AYKROYD" ], [ "GROSSE POINTE BLANK", "starred_actors", "DAN AYKROYD" ], [ "GROUNDHOG DAY", "has_genre", "COMEDY" ], [ "GROUNDHOG DAY", "has_tags", "COMEDY" ], [ "GROUNDHOG DAY", "release_year", "1993" ], [ "GRUMPY OLD MEN", "has_genre", "COMEDY" ], [ "GRUMPY OLD MEN", "has_tags", "COMEDY" ], [ "GRUMPY OLD MEN", "release_year", "1993" ], [ "GYPSY", "has_genre", "COMEDY" ], [ "GYPSY", "release_year", "1993" ], [ "HEART AND SOULS", "has_genre", "COMEDY" ], [ "HEART AND SOULS", "release_year", "1993" ], [ "HEXED", "has_genre", "COMEDY" ], [ "HEXED", "release_year", "1993" ], [ "HOCUS POCUS", "has_genre", "COMEDY" ], [ "HOCUS POCUS", "release_year", "1993" ], [ "HOT SHOTS! PART DEUX", "has_genre", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "has_tags", "COMEDY" ], [ "HOT SHOTS! PART DEUX", "release_year", "1993" ], [ "INDIAN SUMMER", "has_genre", "COMEDY" ], [ "INDIAN SUMMER", "release_year", "1993" ], [ "IT CAME FROM HOLLYWOOD", "has_genre", "COMEDY" ], [ "IT CAME FROM HOLLYWOOD", "starred_actors", "DAN AYKROYD" ], [ "IT'S PAT", "has_genre", "COMEDY" ], [ "IT'S PAT", "has_tags", "SATURDAY NIGHT LIVE" ], [ "JOSH AND S.A.M.", "has_genre", "COMEDY" ], [ "JOSH AND S.A.M.", "release_year", "1993" ], [ "LA ESTRATEGIA DEL CARACOL", "has_genre", "COMEDY" ], [ "LA ESTRATEGIA DEL CARACOL", "release_year", "1993" ], [ "LAST ACTION HERO", "has_genre", "COMEDY" ], [ "LAST ACTION HERO", "has_tags", "COMEDY" ], [ "LAST ACTION HERO", "release_year", "1993" ], [ "LEPRECHAUN", "has_genre", "COMEDY" ], [ "LEPRECHAUN", "release_year", "1993" ], [ "LIFE WITH MIKEY", "has_genre", "COMEDY" ], [ "LIFE WITH MIKEY", "release_year", "1993" ], [ "LOADED WEAPON 1", "has_genre", "COMEDY" ], [ "LOADED WEAPON 1", "release_year", "1993" ], [ "LOOSE CANNONS", "has_genre", "COMEDY" ], [ "LOOSE CANNONS", "starred_actors", "DAN AYKROYD" ], [ "LOVE BITES", "has_genre", "COMEDY" ], [ "LOVE BITES", "release_year", "1993" ], [ "MACGRUBER", "has_genre", "COMEDY" ], [ "MACGRUBER", "has_tags", "COMEDY" ], [ "MACGRUBER", "has_tags", "SATURDAY NIGHT LIVE" ], [ "MAD DOG AND GLORY", "has_genre", "COMEDY" ], [ "MAD DOG AND GLORY", "release_year", "1993" ], [ "MADE IN AMERICA", "has_genre", "COMEDY" ], [ "MADE IN AMERICA", "release_year", "1993" ], [ "MAN'S BEST FRIEND", "has_genre", "COMEDY" ], [ "MAN'S BEST FRIEND", "release_year", "1993" ], [ "MANHATTAN MURDER MYSTERY", "has_genre", "COMEDY" ], [ "MANHATTAN MURDER MYSTERY", "release_year", "1993" ], [ "MATINEE", "has_genre", "COMEDY" ], [ "MATINEE", "release_year", "1993" ], [ "MEAN GIRLS", "has_genre", "COMEDY" ], [ "MEAN GIRLS", "has_tags", "COMEDY" ], [ "MEAN GIRLS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "MONEY FOR NOTHING", "has_genre", "COMEDY" ], [ "MONEY FOR NOTHING", "release_year", "1993" ], [ "MR. WONDERFUL", "has_genre", "COMEDY" ], [ "MR. WONDERFUL", "release_year", "1993" ], [ "MRS. DOUBTFIRE", "has_genre", "COMEDY" ], [ "MRS. DOUBTFIRE", "has_tags", "COMEDY" ], [ "MRS. DOUBTFIRE", "release_year", "1993" ], [ "MUCH ADO ABOUT NOTHING", "has_genre", "COMEDY" ], [ "MUCH ADO ABOUT NOTHING", "has_tags", "COMEDY" ], [ "MUCH ADO ABOUT NOTHING", "release_year", "1993" ], [ "MY BOYFRIEND'S BACK", "has_genre", "COMEDY" ], [ "MY BOYFRIEND'S BACK", "release_year", "1993" ], [ "MY FELLOW AMERICANS", "has_genre", "COMEDY" ], [ "MY FELLOW AMERICANS", "has_tags", "DAN AYKROYD" ], [ "MY FELLOW AMERICANS", "starred_actors", "DAN AYKROYD" ], [ "MY GIRL 2", "has_genre", "COMEDY" ], [ "MY GIRL 2", "has_tags", "DAN AYKROYD" ], [ "MY GIRL 2", "starred_actors", "DAN AYKROYD" ], [ "MY STEPMOTHER IS AN ALIEN", "has_genre", "COMEDY" ], [ "MY STEPMOTHER IS AN ALIEN", "starred_actors", "DAN AYKROYD" ], [ "NAKED IN NEW YORK", "has_genre", "COMEDY" ], [ "NAKED IN NEW YORK", "release_year", "1993" ], [ "NEIGHBORS", "has_genre", "COMEDY" ], [ "NEIGHBORS", "starred_actors", "DAN AYKROYD" ], [ "PARIS, FRANCE", "has_genre", "COMEDY" ], [ "PARIS, FRANCE", "release_year", "1993" ], [ "RAT", "directed_by", "STEVE BARRON" ], [ "RAT", "has_genre", "COMEDY" ], [ "RE-ANIMATOR", "directed_by", "STUART GORDON" ], [ "RE-ANIMATOR", "has_genre", "COMEDY" ], [ "RE-ANIMATOR", "has_genre", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "LOVECRAFT" ], [ "RE-ANIMATOR", "starred_actors", "JEFFREY COMBS" ], [ "RE-ANIMATOR", "written_by", "STUART GORDON" ], [ "ROBOT JOX", "directed_by", "STUART GORDON" ], [ "ROBOT JOX", "starred_actors", "PAUL KOSLO" ], [ "ROBOT JOX", "written_by", "STUART GORDON" ], [ "ROOKIE OF THE YEAR", "has_genre", "COMEDY" ], [ "ROOKIE OF THE YEAR", "release_year", "1993" ], [ "SGT. BILKO", "has_genre", "COMEDY" ], [ "SGT. BILKO", "starred_actors", "DAN AYKROYD" ], [ "SHORT CUTS", "has_genre", "COMEDY" ], [ "SHORT CUTS", "release_year", "1993" ], [ "SIX DEGREES OF SEPARATION", "has_genre", "COMEDY" ], [ "SIX DEGREES OF SEPARATION", "release_year", "1993" ], [ "SLEEPLESS IN SEATTLE", "has_genre", "COMEDY" ], [ "SLEEPLESS IN SEATTLE", "has_tags", "COMEDY" ], [ "SLEEPLESS IN SEATTLE", "release_year", "1993" ], [ "SMOKING/NO SMOKING", "has_genre", "COMEDY" ], [ "SMOKING/NO SMOKING", "release_year", "1993" ], [ "SO I MARRIED AN AXE MURDERER", "has_genre", "COMEDY" ], [ "SO I MARRIED AN AXE MURDERER", "has_tags", "COMEDY" ], [ "SO I MARRIED AN AXE MURDERER", "release_year", "1993" ], [ "SON IN LAW", "has_genre", "COMEDY" ], [ "SON IN LAW", "release_year", "1993" ], [ "SPACE TRUCKERS", "directed_by", "STUART GORDON" ], [ "SPACE TRUCKERS", "has_genre", "COMEDY" ], [ "SPACE TRUCKERS", "release_year", "1996" ], [ "SPACE TRUCKERS", "written_by", "STUART GORDON" ], [ "SPIES LIKE US", "has_genre", "COMEDY" ], [ "SPIES LIKE US", "starred_actors", "DAN AYKROYD" ], [ "SPIES LIKE US", "written_by", "DAN AYKROYD" ], [ "STEFANO QUANTESTORIE", "has_genre", "COMEDY" ], [ "STEFANO QUANTESTORIE", "release_year", "1993" ], [ "STUART SAVES HIS FAMILY", "has_genre", "COMEDY" ], [ "STUART SAVES HIS FAMILY", "has_tags", "SATURDAY NIGHT LIVE" ], [ "STUCK", "directed_by", "STUART GORDON" ], [ "STUCK", "has_genre", "THRILLER" ], [ "STUCK", "written_by", "STUART GORDON" ], [ "SUPER MARIO BROS.", "has_genre", "COMEDY" ], [ "SUPER MARIO BROS.", "has_tags", "COMEDY" ], [ "SUPER MARIO BROS.", "release_year", "1993" ], [ "SUPERSTAR", "has_genre", "COMEDY" ], [ "SUPERSTAR", "has_tags", "SATURDAY NIGHT LIVE" ], [ "TEENAGE MUTANT NINJA TURTLES", "directed_by", "STEVE BARRON" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "COMEDY" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_tags", "STEVE BARRON" ], [ "THE BEVERLY HILLBILLIES", "has_genre", "COMEDY" ], [ "THE BEVERLY HILLBILLIES", "release_year", "1993" ], [ "THE BLUES BROTHERS", "has_genre", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "COMEDY" ], [ "THE BLUES BROTHERS", "has_tags", "DAN AYKROYD" ], [ "THE BLUES BROTHERS", "has_tags", "SATURDAY NIGHT LIVE" ], [ "THE BLUES BROTHERS", "starred_actors", "DAN AYKROYD" ], [ "THE BLUES BROTHERS", "written_by", "DAN AYKROYD" ], [ "THE COUCH TRIP", "has_genre", "COMEDY" ], [ "THE COUCH TRIP", "starred_actors", "DAN AYKROYD" ], [ "THE DENTIST", "directed_by", "BRIAN YUZNA" ], [ "THE DENTIST", "has_genre", "HORROR" ], [ "THE DENTIST", "release_year", "1996" ], [ "THE DENTIST", "starred_actors", "KEN FOREE" ], [ "THE DENTIST", "written_by", "DENNIS PAOLI" ], [ "THE DENTIST", "written_by", "STUART GORDON" ], [ "THE GREAT OUTDOORS", "has_genre", "COMEDY" ], [ "THE GREAT OUTDOORS", "starred_actors", "DAN AYKROYD" ], [ "THE LADIES MAN", "has_genre", "COMEDY" ], [ "THE LADIES MAN", "has_tags", "SATURDAY NIGHT LIVE" ], [ "THE METEOR MAN", "has_genre", "COMEDY" ], [ "THE METEOR MAN", "release_year", "1993" ], [ "THE PIT AND THE PENDULUM", "directed_by", "STUART GORDON" ], [ "THE PIT AND THE PENDULUM", "has_genre", "HORROR" ], [ "THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM", "has_genre", "COMEDY" ], [ "THE POSITIVELY TRUE ADVENTURES OF THE ALLEGED TEXAS CHEERLEADER-MURDERING MOM", "release_year", "1993" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "release_year", "1993" ], [ "THE WONDERFUL ICE CREAM SUIT", "directed_by", "STUART GORDON" ], [ "THE WONDERFUL ICE CREAM SUIT", "starred_actors", "JOE MANTEGNA" ], [ "THE WRONG TROUSERS", "has_genre", "COMEDY" ], [ "THE WRONG TROUSERS", "has_tags", "COMEDY" ], [ "THE WRONG TROUSERS", "release_year", "1993" ], [ "THREE OF HEARTS", "has_genre", "COMEDY" ], [ "THREE OF HEARTS", "release_year", "1993" ], [ "TRADING PLACES", "has_genre", "COMEDY" ], [ "TRADING PLACES", "has_tags", "COMEDY" ], [ "TRADING PLACES", "has_tags", "DAN AYKROYD" ], [ "TRADING PLACES", "starred_actors", "DAN AYKROYD" ], [ "UNDERCOVER BLUES", "has_genre", "COMEDY" ], [ "UNDERCOVER BLUES", "release_year", "1993" ], [ "UNTAMED HEART", "has_genre", "COMEDY" ], [ "UNTAMED HEART", "release_year", "1993" ], [ "WAYNE'S WORLD", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "COMEDY" ], [ "WAYNE'S WORLD", "has_tags", "SATURDAY NIGHT LIVE" ], [ "WAYNE'S WORLD 2", "has_genre", "COMEDY" ], [ "WAYNE'S WORLD 2", "has_tags", "SATURDAY NIGHT LIVE" ], [ "WAYNE'S WORLD 2", "release_year", "1993" ], [ "WEEKEND AT BERNIE'S II", "has_genre", "COMEDY" ], [ "WEEKEND AT BERNIE'S II", "release_year", "1993" ], [ "WHO'S THE MAN?", "has_genre", "COMEDY" ], [ "WHO'S THE MAN?", "release_year", "1993" ], [ "WILDER NAPALM", "has_genre", "COMEDY" ], [ "WILDER NAPALM", "release_year", "1993" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "release_year", "1993" ], [ "YOGI BEAR", "has_genre", "COMEDY" ], [ "YOGI BEAR", "starred_actors", "DAN AYKROYD" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 2043, 9 SONGS 5321, A GOOD WOMAN 38203, A HOLE IN MY HEART 20026, A HOME AT THE END OF THE WORLD 5441, A LOVE SONG FOR BOBBY LONG 11398, A MOMENT TO REMEMBER 20576, A WORLD WITHOUT THIEVES 30109, A.C.O.D. 27020, AGAINST THE ROPES 1698, ALFIE 34789, BAD EDUCATION 18380, BEFORE SUNSET 1815, BEFORE THE FALL 2137, BEING JULIA 20294, BIRTH 2856, BROTHERS 20489, CHANGING TIMES 30885, CLOSER 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 32049, CRASH 34180, CRUEL INTENTIONS 3 15696, DAY AND NIGHT 27982, DEAR FRANKIE 16961, DIRTY FILTHY LOVE 2283, DIVORCE 15779, DORIAN BLUES 1441, DOWN TO THE BONE 36212, DRAMA 1329, ENVY 5924, EROS 15635, ETHAN MAO 5501, EVERYDAY PEOPLE 36165, FALLING DOWN 32706, FIRST LOVE 15080, FLIGHT OF THE PHOENIX 13263, FREEZE FRAME 3175, FRIDAY NIGHT LIGHTS 21640, GARDEN STATE 16914, GILLES' WIFE 17567, HARRY + MAX 9621, HAWAII, OSLO 23477, HAWKING 4840, HEAD IN THE CLOUDS 1044, HOTEL RWANDA 20303, HOUSE OF D 6753, IMAGINARY HEROES 38426, IRON JAWED ANGELS 21861, JERSEY GIRL 8849, KEANE 34731, KINSEY 926, LADDER 49 30600, LADIES IN LAVENDER 37237, LAND OF PLENTY 5251, LIGHTNING BUG 11689, LOOK AT ME 12292, MARIE AND BRUCE 20283, MEAN CREEK 831, MELINDA AND MELINDA 33998, MICKEY 28532, MILLION DOLLAR BABY 13143, MILLIONS 4168, MIRACLE 34674, MY SUMMER OF LOVE 26817, MYSTERIOUS SKIN 20433, NEW POLICE STORY 25709, NOBODY KNOWS 37353, NOEL 4132, OMAGH 11031, OUT OF REACH 13268, OYSTER FARMER 29275, P.S. 28047, PALINDROMES 12683, PRIMER 35167, PRIVATE 28125, RAINCOAT 5693, RAISING HELEN 33617, RED DUST 31114, SAINT RALPH 11313, SAVED! 2135, SAVING FACE 12902, SHE HATE ME 36797, SIDEWAYS 12464, SILVER CITY 32387, SIMON 7717, SPANGLISH 10978, STAGE BEAUTY 8374, STRIP SEARCH 4845, STU ZICHERMAN 24987, SUMMER STORM 6439, THE AVIATOR 16499, THE BEAUTIFUL COUNTRY 5686, THE BRIDGE OF SAN LUIS REY 33022, THE CHORUS 18130, THE CLEARING 21465, THE DOOR IN THE FLOOR 19685, THE FINAL CUT 15429, THE FORGOTTEN 14807, THE GOODBYE GIRL 38765, THE HOLY GIRL 8435, THE KEYS TO THE HOUSE 11711, THE LIBERTINE 28217, THE LIFE AQUATIC WITH STEVE ZISSOU 36024, THE LIZARD 38433, THE MERCHANT OF VENICE 11555, THE NOTEBOOK 34751, THE PASSION OF THE CHRIST 7537, THE RETURNED 15768, THE TERMINAL 25426, THE WOODSMAN 16413, TROPICAL MALADY 29947, TURTLES CAN FLY 32733, VANITY FAIR 7577, VEER-ZAARA 22949, VERA DRAKE 37859, WE DON'T LIVE HERE ANYMORE 21897, WHEN WILL I BE LOVED 7055, WICKER PARK 18720, WILBY WONDERFUL 32096, WILD SIDE 7208, WINTER SOLSTICE 9901, YOU GOT SERVED src, edge_attr, dst 2043, has_genre, 36212 2043, release_year, 37484 5321, has_genre, 36212 5321, release_year, 37484 38203, has_genre, 36212 38203, release_year, 37484 20026, has_genre, 36212 20026, release_year, 37484 5441, has_genre, 36212 5441, release_year, 37484 11398, has_genre, 36212 11398, release_year, 37484 20576, has_genre, 36212 20576, release_year, 37484 30109, directed_by, 4845 30109, has_tags, 2283 30109, written_by, 4845 27020, has_genre, 36212 27020, release_year, 37484 1698, has_genre, 36212 1698, release_year, 37484 34789, has_genre, 36212 34789, has_tags, 36212 34789, release_year, 37484 18380, has_genre, 36212 18380, release_year, 37484 1815, has_genre, 36212 1815, release_year, 37484 2137, has_genre, 36212 2137, release_year, 37484 20294, has_genre, 36212 20294, release_year, 37484 2856, has_genre, 36212 2856, release_year, 37484 20489, has_genre, 36212 20489, release_year, 37484 30885, has_genre, 36212 30885, has_tags, 36212 30885, release_year, 37484 10272, has_tags, 36212 10272, release_year, 37484 32049, has_genre, 36212 32049, release_year, 37484 34180, has_genre, 36212 34180, release_year, 37484 15696, has_genre, 36212 15696, has_tags, 36212 15696, release_year, 37484 27982, has_genre, 36212 27982, release_year, 37484 16961, has_genre, 36212 16961, release_year, 37484 2283, has_genre, 36212 15779, has_genre, 36212 15779, release_year, 37484 1441, has_genre, 36212 1441, release_year, 37484 1329, has_genre, 36212 1329, release_year, 37484 5924, has_genre, 36212 5924, release_year, 37484 15635, has_genre, 36212 15635, release_year, 37484 5501, has_genre, 36212 5501, release_year, 37484 36165, has_genre, 36212 32706, has_genre, 36212 32706, release_year, 37484 15080, has_genre, 36212 15080, release_year, 37484 13263, has_genre, 36212 13263, release_year, 37484 3175, has_genre, 36212 3175, has_tags, 36212 3175, release_year, 37484 21640, has_genre, 36212 21640, release_year, 37484 16914, has_genre, 36212 16914, release_year, 37484 17567, has_genre, 36212 17567, release_year, 37484 9621, has_genre, 36212 9621, release_year, 37484 23477, has_genre, 36212 23477, release_year, 37484 4840, has_genre, 36212 4840, release_year, 37484 1044, has_genre, 36212 1044, has_tags, 36212 1044, release_year, 37484 20303, has_genre, 36212 20303, release_year, 37484 6753, has_genre, 36212 6753, release_year, 37484 38426, has_genre, 36212 38426, release_year, 37484 21861, has_genre, 36212 21861, has_tags, 36212 21861, release_year, 37484 8849, has_genre, 36212 8849, release_year, 37484 34731, has_genre, 36212 34731, release_year, 37484 926, has_genre, 36212 926, release_year, 37484 30600, has_genre, 36212 30600, release_year, 37484 37237, has_genre, 36212 37237, release_year, 37484 5251, has_genre, 36212 5251, release_year, 37484 11689, has_genre, 36212 11689, release_year, 37484 12292, has_genre, 36212 12292, release_year, 37484 20283, has_genre, 36212 20283, has_tags, 36212 20283, release_year, 37484 831, has_genre, 36212 831, release_year, 37484 33998, has_genre, 36212 33998, release_year, 37484 28532, has_genre, 36212 28532, has_tags, 36212 28532, release_year, 37484 13143, has_genre, 36212 13143, release_year, 37484 4168, has_genre, 36212 4168, release_year, 37484 34674, has_genre, 36212 34674, has_tags, 36212 34674, release_year, 37484 26817, has_genre, 36212 26817, release_year, 37484 20433, has_genre, 36212 20433, release_year, 37484 25709, has_genre, 36212 25709, release_year, 37484 37353, has_genre, 36212 37353, has_tags, 36212 37353, release_year, 37484 4132, has_genre, 36212 4132, release_year, 37484 11031, has_genre, 36212 11031, release_year, 37484 13268, has_genre, 36212 13268, release_year, 37484 29275, has_genre, 36212 29275, release_year, 37484 28047, has_genre, 36212 28047, release_year, 37484 12683, has_genre, 36212 12683, release_year, 37484 35167, has_genre, 36212 35167, release_year, 37484 28125, has_genre, 36212 28125, release_year, 37484 5693, has_genre, 36212 5693, release_year, 37484 33617, has_genre, 36212 33617, release_year, 37484 31114, has_genre, 36212 31114, release_year, 37484 11313, has_genre, 36212 11313, release_year, 37484 2135, has_genre, 36212 2135, release_year, 37484 12902, has_genre, 36212 12902, release_year, 37484 36797, has_genre, 36212 36797, release_year, 37484 12464, has_genre, 36212 12464, release_year, 37484 32387, has_genre, 36212 32387, release_year, 37484 7717, has_genre, 36212 7717, release_year, 37484 10978, has_genre, 36212 10978, release_year, 37484 8374, has_genre, 36212 8374, release_year, 37484 24987, has_genre, 36212 24987, release_year, 37484 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 37484 16499, has_genre, 36212 16499, has_tags, 36212 16499, release_year, 37484 5686, has_genre, 36212 5686, release_year, 37484 33022, has_genre, 36212 33022, has_tags, 36212 33022, release_year, 37484 18130, has_genre, 36212 18130, release_year, 37484 21465, has_genre, 36212 21465, has_tags, 36212 21465, release_year, 37484 19685, has_genre, 36212 19685, release_year, 37484 15429, has_genre, 36212 15429, release_year, 37484 14807, has_genre, 36212 14807, release_year, 37484 38765, has_genre, 36212 38765, release_year, 37484 8435, has_genre, 36212 8435, release_year, 37484 11711, has_genre, 36212 11711, release_year, 37484 28217, has_genre, 36212 28217, release_year, 37484 36024, has_genre, 36212 36024, release_year, 37484 38433, has_genre, 36212 38433, release_year, 37484 11555, has_genre, 36212 11555, release_year, 37484 34751, has_genre, 36212 34751, release_year, 37484 7537, has_genre, 36212 7537, release_year, 37484 15768, has_genre, 36212 15768, has_tags, 36212 15768, release_year, 37484 25426, has_genre, 36212 25426, has_tags, 36212 25426, release_year, 37484 16413, has_genre, 36212 16413, release_year, 37484 29947, has_genre, 36212 29947, release_year, 37484 32733, has_genre, 36212 32733, release_year, 37484 7577, has_genre, 36212 7577, release_year, 37484 22949, has_genre, 36212 22949, release_year, 37484 37859, has_genre, 36212 37859, release_year, 37484 21897, has_genre, 36212 21897, release_year, 37484 7055, has_genre, 36212 7055, release_year, 37484 18720, has_genre, 36212 18720, release_year, 37484 32096, has_genre, 36212 32096, release_year, 37484 7208, has_genre, 36212 7208, release_year, 37484 9901, release_year, 37484 Question: For what reason are FALLING DOWN, STU ZICHERMAN, and YOU GOT SERVED associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FALLING DOWN", "STU ZICHERMAN", "YOU GOT SERVED" ], "valid_edges": [ [ "9 SONGS", "has_genre", "DRAMA" ], [ "9 SONGS", "release_year", "2004" ], [ "A GOOD WOMAN", "has_genre", "DRAMA" ], [ "A GOOD WOMAN", "release_year", "2004" ], [ "A HOLE IN MY HEART", "has_genre", "DRAMA" ], [ "A HOLE IN MY HEART", "release_year", "2004" ], [ "A HOME AT THE END OF THE WORLD", "has_genre", "DRAMA" ], [ "A HOME AT THE END OF THE WORLD", "release_year", "2004" ], [ "A LOVE SONG FOR BOBBY LONG", "has_genre", "DRAMA" ], [ "A LOVE SONG FOR BOBBY LONG", "release_year", "2004" ], [ "A MOMENT TO REMEMBER", "has_genre", "DRAMA" ], [ "A MOMENT TO REMEMBER", "release_year", "2004" ], [ "A WORLD WITHOUT THIEVES", "has_genre", "DRAMA" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "A.C.O.D.", "directed_by", "STU ZICHERMAN" ], [ "A.C.O.D.", "has_tags", "DIVORCE" ], [ "A.C.O.D.", "written_by", "STU ZICHERMAN" ], [ "AGAINST THE ROPES", "has_genre", "DRAMA" ], [ "AGAINST THE ROPES", "release_year", "2004" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "release_year", "2004" ], [ "BAD EDUCATION", "has_genre", "DRAMA" ], [ "BAD EDUCATION", "has_tags", "DRAMA" ], [ "BAD EDUCATION", "release_year", "2004" ], [ "BEFORE SUNSET", "has_genre", "DRAMA" ], [ "BEFORE SUNSET", "release_year", "2004" ], [ "BEFORE THE FALL", "has_genre", "DRAMA" ], [ "BEFORE THE FALL", "release_year", "2004" ], [ "BEING JULIA", "has_genre", "DRAMA" ], [ "BEING JULIA", "release_year", "2004" ], [ "BIRTH", "has_genre", "DRAMA" ], [ "BIRTH", "release_year", "2004" ], [ "BROTHERS", "has_genre", "DRAMA" ], [ "BROTHERS", "release_year", "2004" ], [ "CHANGING TIMES", "has_genre", "DRAMA" ], [ "CHANGING TIMES", "release_year", "2004" ], [ "CLOSER", "has_genre", "DRAMA" ], [ "CLOSER", "has_tags", "DRAMA" ], [ "CLOSER", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CRASH", "has_genre", "DRAMA" ], [ "CRASH", "release_year", "2004" ], [ "CRUEL INTENTIONS 3", "has_genre", "DRAMA" ], [ "CRUEL INTENTIONS 3", "release_year", "2004" ], [ "DAY AND NIGHT", "has_genre", "DRAMA" ], [ "DAY AND NIGHT", "has_tags", "DRAMA" ], [ "DAY AND NIGHT", "release_year", "2004" ], [ "DEAR FRANKIE", "has_genre", "DRAMA" ], [ "DEAR FRANKIE", "release_year", "2004" ], [ "DIRTY FILTHY LOVE", "has_genre", "DRAMA" ], [ "DIRTY FILTHY LOVE", "release_year", "2004" ], [ "DIVORCE", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "has_genre", "DRAMA" ], [ "DORIAN BLUES", "release_year", "2004" ], [ "DOWN TO THE BONE", "has_genre", "DRAMA" ], [ "DOWN TO THE BONE", "release_year", "2004" ], [ "ENVY", "has_genre", "DRAMA" ], [ "ENVY", "release_year", "2004" ], [ "EROS", "has_genre", "DRAMA" ], [ "EROS", "release_year", "2004" ], [ "ETHAN MAO", "has_genre", "DRAMA" ], [ "ETHAN MAO", "release_year", "2004" ], [ "EVERYDAY PEOPLE", "has_genre", "DRAMA" ], [ "EVERYDAY PEOPLE", "release_year", "2004" ], [ "FALLING DOWN", "has_genre", "DRAMA" ], [ "FIRST LOVE", "has_genre", "DRAMA" ], [ "FIRST LOVE", "release_year", "2004" ], [ "FLIGHT OF THE PHOENIX", "has_genre", "DRAMA" ], [ "FLIGHT OF THE PHOENIX", "release_year", "2004" ], [ "FREEZE FRAME", "has_genre", "DRAMA" ], [ "FREEZE FRAME", "release_year", "2004" ], [ "FRIDAY NIGHT LIGHTS", "has_genre", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "has_tags", "DRAMA" ], [ "FRIDAY NIGHT LIGHTS", "release_year", "2004" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "release_year", "2004" ], [ "GILLES' WIFE", "has_genre", "DRAMA" ], [ "GILLES' WIFE", "release_year", "2004" ], [ "HARRY + MAX", "has_genre", "DRAMA" ], [ "HARRY + MAX", "release_year", "2004" ], [ "HAWAII, OSLO", "has_genre", "DRAMA" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWKING", "has_genre", "DRAMA" ], [ "HAWKING", "release_year", "2004" ], [ "HEAD IN THE CLOUDS", "has_genre", "DRAMA" ], [ "HEAD IN THE CLOUDS", "release_year", "2004" ], [ "HOTEL RWANDA", "has_genre", "DRAMA" ], [ "HOTEL RWANDA", "has_tags", "DRAMA" ], [ "HOTEL RWANDA", "release_year", "2004" ], [ "HOUSE OF D", "has_genre", "DRAMA" ], [ "HOUSE OF D", "release_year", "2004" ], [ "IMAGINARY HEROES", "has_genre", "DRAMA" ], [ "IMAGINARY HEROES", "release_year", "2004" ], [ "IRON JAWED ANGELS", "has_genre", "DRAMA" ], [ "IRON JAWED ANGELS", "release_year", "2004" ], [ "JERSEY GIRL", "has_genre", "DRAMA" ], [ "JERSEY GIRL", "has_tags", "DRAMA" ], [ "JERSEY GIRL", "release_year", "2004" ], [ "KEANE", "has_genre", "DRAMA" ], [ "KEANE", "release_year", "2004" ], [ "KINSEY", "has_genre", "DRAMA" ], [ "KINSEY", "release_year", "2004" ], [ "LADDER 49", "has_genre", "DRAMA" ], [ "LADDER 49", "release_year", "2004" ], [ "LADIES IN LAVENDER", "has_genre", "DRAMA" ], [ "LADIES IN LAVENDER", "release_year", "2004" ], [ "LAND OF PLENTY", "has_genre", "DRAMA" ], [ "LAND OF PLENTY", "release_year", "2004" ], [ "LIGHTNING BUG", "has_genre", "DRAMA" ], [ "LIGHTNING BUG", "release_year", "2004" ], [ "LOOK AT ME", "has_genre", "DRAMA" ], [ "LOOK AT ME", "release_year", "2004" ], [ "MARIE AND BRUCE", "has_genre", "DRAMA" ], [ "MARIE AND BRUCE", "release_year", "2004" ], [ "MEAN CREEK", "has_genre", "DRAMA" ], [ "MEAN CREEK", "has_tags", "DRAMA" ], [ "MEAN CREEK", "release_year", "2004" ], [ "MELINDA AND MELINDA", "has_genre", "DRAMA" ], [ "MELINDA AND MELINDA", "release_year", "2004" ], [ "MICKEY", "has_genre", "DRAMA" ], [ "MICKEY", "release_year", "2004" ], [ "MILLION DOLLAR BABY", "has_genre", "DRAMA" ], [ "MILLION DOLLAR BABY", "has_tags", "DRAMA" ], [ "MILLION DOLLAR BABY", "release_year", "2004" ], [ "MILLIONS", "has_genre", "DRAMA" ], [ "MILLIONS", "release_year", "2004" ], [ "MIRACLE", "has_genre", "DRAMA" ], [ "MIRACLE", "release_year", "2004" ], [ "MY SUMMER OF LOVE", "has_genre", "DRAMA" ], [ "MY SUMMER OF LOVE", "has_tags", "DRAMA" ], [ "MY SUMMER OF LOVE", "release_year", "2004" ], [ "MYSTERIOUS SKIN", "has_genre", "DRAMA" ], [ "MYSTERIOUS SKIN", "release_year", "2004" ], [ "NEW POLICE STORY", "has_genre", "DRAMA" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NOBODY KNOWS", "has_genre", "DRAMA" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "release_year", "2004" ], [ "OMAGH", "has_genre", "DRAMA" ], [ "OMAGH", "release_year", "2004" ], [ "OUT OF REACH", "has_genre", "DRAMA" ], [ "OUT OF REACH", "release_year", "2004" ], [ "OYSTER FARMER", "has_genre", "DRAMA" ], [ "OYSTER FARMER", "release_year", "2004" ], [ "P.S.", "has_genre", "DRAMA" ], [ "P.S.", "release_year", "2004" ], [ "PALINDROMES", "has_genre", "DRAMA" ], [ "PALINDROMES", "release_year", "2004" ], [ "PRIMER", "has_genre", "DRAMA" ], [ "PRIMER", "release_year", "2004" ], [ "PRIVATE", "has_genre", "DRAMA" ], [ "PRIVATE", "release_year", "2004" ], [ "RAINCOAT", "has_genre", "DRAMA" ], [ "RAINCOAT", "release_year", "2004" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "RAISING HELEN", "release_year", "2004" ], [ "RED DUST", "has_genre", "DRAMA" ], [ "RED DUST", "release_year", "2004" ], [ "SAINT RALPH", "has_genre", "DRAMA" ], [ "SAINT RALPH", "release_year", "2004" ], [ "SAVED!", "has_genre", "DRAMA" ], [ "SAVED!", "release_year", "2004" ], [ "SAVING FACE", "has_genre", "DRAMA" ], [ "SAVING FACE", "release_year", "2004" ], [ "SHE HATE ME", "has_genre", "DRAMA" ], [ "SHE HATE ME", "release_year", "2004" ], [ "SIDEWAYS", "has_genre", "DRAMA" ], [ "SIDEWAYS", "release_year", "2004" ], [ "SILVER CITY", "has_genre", "DRAMA" ], [ "SILVER CITY", "release_year", "2004" ], [ "SIMON", "has_genre", "DRAMA" ], [ "SIMON", "release_year", "2004" ], [ "SPANGLISH", "has_genre", "DRAMA" ], [ "SPANGLISH", "release_year", "2004" ], [ "STAGE BEAUTY", "has_genre", "DRAMA" ], [ "STAGE BEAUTY", "release_year", "2004" ], [ "STRIP SEARCH", "has_genre", "DRAMA" ], [ "STRIP SEARCH", "release_year", "2004" ], [ "SUMMER STORM", "has_genre", "DRAMA" ], [ "SUMMER STORM", "release_year", "2004" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "2004" ], [ "THE BEAUTIFUL COUNTRY", "has_genre", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "has_tags", "DRAMA" ], [ "THE BEAUTIFUL COUNTRY", "release_year", "2004" ], [ "THE BRIDGE OF SAN LUIS REY", "has_genre", "DRAMA" ], [ "THE BRIDGE OF SAN LUIS REY", "release_year", "2004" ], [ "THE CHORUS", "has_genre", "DRAMA" ], [ "THE CHORUS", "has_tags", "DRAMA" ], [ "THE CHORUS", "release_year", "2004" ], [ "THE CLEARING", "has_genre", "DRAMA" ], [ "THE CLEARING", "release_year", "2004" ], [ "THE DOOR IN THE FLOOR", "has_genre", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "has_tags", "DRAMA" ], [ "THE DOOR IN THE FLOOR", "release_year", "2004" ], [ "THE FINAL CUT", "has_genre", "DRAMA" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE FORGOTTEN", "has_genre", "DRAMA" ], [ "THE FORGOTTEN", "release_year", "2004" ], [ "THE GOODBYE GIRL", "has_genre", "DRAMA" ], [ "THE GOODBYE GIRL", "release_year", "2004" ], [ "THE HOLY GIRL", "has_genre", "DRAMA" ], [ "THE HOLY GIRL", "release_year", "2004" ], [ "THE KEYS TO THE HOUSE", "has_genre", "DRAMA" ], [ "THE KEYS TO THE HOUSE", "release_year", "2004" ], [ "THE LIBERTINE", "has_genre", "DRAMA" ], [ "THE LIBERTINE", "release_year", "2004" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "has_genre", "DRAMA" ], [ "THE LIFE AQUATIC WITH STEVE ZISSOU", "release_year", "2004" ], [ "THE LIZARD", "has_genre", "DRAMA" ], [ "THE LIZARD", "release_year", "2004" ], [ "THE MERCHANT OF VENICE", "has_genre", "DRAMA" ], [ "THE MERCHANT OF VENICE", "release_year", "2004" ], [ "THE NOTEBOOK", "has_genre", "DRAMA" ], [ "THE NOTEBOOK", "release_year", "2004" ], [ "THE PASSION OF THE CHRIST", "has_genre", "DRAMA" ], [ "THE PASSION OF THE CHRIST", "release_year", "2004" ], [ "THE RETURNED", "has_genre", "DRAMA" ], [ "THE RETURNED", "release_year", "2004" ], [ "THE TERMINAL", "has_genre", "DRAMA" ], [ "THE TERMINAL", "has_tags", "DRAMA" ], [ "THE TERMINAL", "release_year", "2004" ], [ "THE WOODSMAN", "has_genre", "DRAMA" ], [ "THE WOODSMAN", "has_tags", "DRAMA" ], [ "THE WOODSMAN", "release_year", "2004" ], [ "TROPICAL MALADY", "has_genre", "DRAMA" ], [ "TROPICAL MALADY", "release_year", "2004" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "release_year", "2004" ], [ "VANITY FAIR", "has_genre", "DRAMA" ], [ "VANITY FAIR", "release_year", "2004" ], [ "VEER-ZAARA", "has_genre", "DRAMA" ], [ "VEER-ZAARA", "release_year", "2004" ], [ "VERA DRAKE", "has_genre", "DRAMA" ], [ "VERA DRAKE", "release_year", "2004" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHEN WILL I BE LOVED", "has_genre", "DRAMA" ], [ "WHEN WILL I BE LOVED", "release_year", "2004" ], [ "WICKER PARK", "has_genre", "DRAMA" ], [ "WICKER PARK", "release_year", "2004" ], [ "WILBY WONDERFUL", "has_genre", "DRAMA" ], [ "WILBY WONDERFUL", "release_year", "2004" ], [ "WILD SIDE", "has_genre", "DRAMA" ], [ "WILD SIDE", "release_year", "2004" ], [ "WINTER SOLSTICE", "has_genre", "DRAMA" ], [ "WINTER SOLSTICE", "release_year", "2004" ], [ "YOU GOT SERVED", "release_year", "2004" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 24818, 1992 29424, 2011 17280, CHRISTMAS 26766, CHRISTOPHER CAIN 6029, EMILIO ESTEVEZ 32518, FREEJACK 31648, FRIGHT NIGHT 1153, MICHAEL CAINE 10743, ONE MAGIC CHRISTMAS 38711, PURE COUNTRY 19260, ST. ELMO'S FIRE 15048, THAT WAS THEN... THIS IS NOW 17931, THE BREAKFAST CLUB 29997, THE HOLCROFT COVENANT 24724, THE MIGHTY DUCKS 26128, THE MUPPET CHRISTMAS CAROL 22911, TO GRANDMOTHER'S HOUSE WE GO 5030, YOUNG GUNS 17195, ZOOKEEPER src, edge_attr, dst 32518, release_year, 24818 32518, starred_actors, 6029 31648, release_year, 38097 31648, release_year, 29424 10743, has_tags, 17280 10743, release_year, 38097 38711, directed_by, 26766 38711, release_year, 24818 19260, has_tags, 6029 19260, release_year, 38097 19260, starred_actors, 6029 15048, directed_by, 26766 15048, release_year, 38097 15048, starred_actors, 6029 15048, written_by, 6029 17931, has_tags, 6029 17931, release_year, 38097 17931, starred_actors, 6029 29997, release_year, 38097 29997, starred_actors, 1153 24724, has_tags, 6029 24724, release_year, 24818 24724, starred_actors, 6029 26128, has_tags, 17280 26128, has_tags, 1153 26128, release_year, 24818 26128, starred_actors, 1153 22911, has_tags, 17280 22911, release_year, 24818 5030, directed_by, 26766 5030, has_tags, 26766 5030, has_tags, 6029 5030, starred_actors, 6029 17195, release_year, 29424 Question: How are THAT WAS THEN... THIS IS NOW, THE MUPPET CHRISTMAS CAROL, and ZOOKEEPER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "THAT WAS THEN... THIS IS NOW", "THE MUPPET CHRISTMAS CAROL", "ZOOKEEPER" ], "valid_edges": [ [ "FREEJACK", "release_year", "1992" ], [ "FREEJACK", "starred_actors", "EMILIO ESTEVEZ" ], [ "FRIGHT NIGHT", "release_year", "1985" ], [ "FRIGHT NIGHT", "release_year", "2011" ], [ "ONE MAGIC CHRISTMAS", "has_tags", "CHRISTMAS" ], [ "ONE MAGIC CHRISTMAS", "release_year", "1985" ], [ "PURE COUNTRY", "directed_by", "CHRISTOPHER CAIN" ], [ "PURE COUNTRY", "release_year", "1992" ], [ "ST. ELMO'S FIRE", "has_tags", "EMILIO ESTEVEZ" ], [ "ST. ELMO'S FIRE", "release_year", "1985" ], [ "ST. ELMO'S FIRE", "starred_actors", "EMILIO ESTEVEZ" ], [ "THAT WAS THEN... THIS IS NOW", "directed_by", "CHRISTOPHER CAIN" ], [ "THAT WAS THEN... THIS IS NOW", "release_year", "1985" ], [ "THAT WAS THEN... THIS IS NOW", "starred_actors", "EMILIO ESTEVEZ" ], [ "THAT WAS THEN... THIS IS NOW", "written_by", "EMILIO ESTEVEZ" ], [ "THE BREAKFAST CLUB", "has_tags", "EMILIO ESTEVEZ" ], [ "THE BREAKFAST CLUB", "release_year", "1985" ], [ "THE BREAKFAST CLUB", "starred_actors", "EMILIO ESTEVEZ" ], [ "THE HOLCROFT COVENANT", "release_year", "1985" ], [ "THE HOLCROFT COVENANT", "starred_actors", "MICHAEL CAINE" ], [ "THE MIGHTY DUCKS", "has_tags", "EMILIO ESTEVEZ" ], [ "THE MIGHTY DUCKS", "release_year", "1992" ], [ "THE MIGHTY DUCKS", "starred_actors", "EMILIO ESTEVEZ" ], [ "THE MUPPET CHRISTMAS CAROL", "has_tags", "CHRISTMAS" ], [ "THE MUPPET CHRISTMAS CAROL", "has_tags", "MICHAEL CAINE" ], [ "THE MUPPET CHRISTMAS CAROL", "release_year", "1992" ], [ "THE MUPPET CHRISTMAS CAROL", "starred_actors", "MICHAEL CAINE" ], [ "TO GRANDMOTHER'S HOUSE WE GO", "has_tags", "CHRISTMAS" ], [ "TO GRANDMOTHER'S HOUSE WE GO", "release_year", "1992" ], [ "YOUNG GUNS", "directed_by", "CHRISTOPHER CAIN" ], [ "YOUNG GUNS", "has_tags", "CHRISTOPHER CAIN" ], [ "YOUNG GUNS", "has_tags", "EMILIO ESTEVEZ" ], [ "YOUNG GUNS", "starred_actors", "EMILIO ESTEVEZ" ], [ "ZOOKEEPER", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9854, BEST DEFENSE 13164, BROADWAY 12903, DISNEY 37267, DREAMGIRLS 31411, EDDIE MURPHY 12956, GENE KELLY 3716, HELLO, DOLLY! 14774, THAT DARN CAT! 7816, THE THREE MUSKETEERS src, edge_attr, dst 9854, has_tags, 31411 9854, starred_actors, 31411 37267, has_tags, 13164 37267, has_tags, 31411 37267, starred_actors, 31411 3716, directed_by, 12956 3716, has_tags, 13164 3716, has_tags, 12956 14774, has_tags, 12903 7816, has_tags, 12903 7816, starred_actors, 12956 Question: In what context are BEST DEFENSE, HELLO, DOLLY!, and THAT DARN CAT! connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BEST DEFENSE", "HELLO, DOLLY!", "THAT DARN CAT!" ], "valid_edges": [ [ "BEST DEFENSE", "has_tags", "EDDIE MURPHY" ], [ "BEST DEFENSE", "starred_actors", "EDDIE MURPHY" ], [ "DREAMGIRLS", "has_tags", "BROADWAY" ], [ "DREAMGIRLS", "has_tags", "EDDIE MURPHY" ], [ "DREAMGIRLS", "starred_actors", "EDDIE MURPHY" ], [ "HELLO, DOLLY!", "directed_by", "GENE KELLY" ], [ "HELLO, DOLLY!", "has_tags", "BROADWAY" ], [ "HELLO, DOLLY!", "has_tags", "GENE KELLY" ], [ "THAT DARN CAT!", "has_tags", "DISNEY" ], [ "THE THREE MUSKETEERS", "has_tags", "DISNEY" ], [ "THE THREE MUSKETEERS", "starred_actors", "GENE KELLY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7698, ANIMATED 2313, BEN-HUR 12903, DISNEY 5191, HAYA HARAREET 23900, LARRY MOREY 23695, MULAN 37497, NATIONAL FILM REGISTRY 25353, ROBERT D. SAN SOUCI 4717, SNOW WHITE AND THE SEVEN DWARFS src, edge_attr, dst 2313, has_tags, 37497 2313, starred_actors, 5191 23695, has_tags, 7698 23695, has_tags, 12903 23695, written_by, 25353 4717, directed_by, 23900 4717, has_tags, 7698 4717, has_tags, 12903 4717, has_tags, 37497 Question: For what reason are HAYA HARAREET, LARRY MOREY, and ROBERT D. SAN SOUCI associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HAYA HARAREET", "LARRY MOREY", "ROBERT D. SAN SOUCI" ], "valid_edges": [ [ "BEN-HUR", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BEN-HUR", "starred_actors", "HAYA HARAREET" ], [ "MULAN", "has_tags", "ANIMATED" ], [ "MULAN", "has_tags", "DISNEY" ], [ "MULAN", "written_by", "ROBERT D. SAN SOUCI" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "directed_by", "LARRY MOREY" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "ANIMATED" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "DISNEY" ], [ "SNOW WHITE AND THE SEVEN DWARFS", "has_tags", "NATIONAL FILM REGISTRY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39646, ALL THE WAY HOME 35689, ANGEL FACE 36212, DRAMA 21425, ELMER GANTRY 38937, JANETTE OKE 25901, JEAN SIMMONS 35948, LOVE COMES SOFTLY 1691, LOVE'S LONG JOURNEY 20042, MICHAEL LANDON JR. 32548, MIGUEL GOMES 27315, MISTER BUDDWING 18335, TABU 22407, THE ACTRESS src, edge_attr, dst 39646, has_genre, 36212 39646, starred_actors, 25901 35689, has_genre, 36212 35689, starred_actors, 25901 21425, has_genre, 36212 21425, starred_actors, 25901 35948, directed_by, 20042 35948, has_genre, 36212 35948, written_by, 38937 35948, written_by, 20042 1691, directed_by, 20042 1691, has_genre, 36212 1691, written_by, 38937 1691, written_by, 20042 27315, has_genre, 36212 27315, starred_actors, 25901 18335, directed_by, 32548 18335, has_genre, 36212 18335, starred_actors, 32548 18335, written_by, 32548 22407, has_genre, 36212 22407, starred_actors, 25901 Question: For what reason are JEAN SIMMONS, MICHAEL LANDON JR., and MIGUEL GOMES associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JEAN SIMMONS", "MICHAEL LANDON JR.", "MIGUEL GOMES" ], "valid_edges": [ [ "ALL THE WAY HOME", "has_genre", "DRAMA" ], [ "ALL THE WAY HOME", "starred_actors", "JEAN SIMMONS" ], [ "ANGEL FACE", "has_genre", "DRAMA" ], [ "ANGEL FACE", "starred_actors", "JEAN SIMMONS" ], [ "ELMER GANTRY", "has_genre", "DRAMA" ], [ "ELMER GANTRY", "starred_actors", "JEAN SIMMONS" ], [ "LOVE COMES SOFTLY", "directed_by", "MICHAEL LANDON JR." ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "written_by", "JANETTE OKE" ], [ "LOVE COMES SOFTLY", "written_by", "MICHAEL LANDON JR." ], [ "LOVE'S LONG JOURNEY", "directed_by", "MICHAEL LANDON JR." ], [ "LOVE'S LONG JOURNEY", "has_genre", "DRAMA" ], [ "LOVE'S LONG JOURNEY", "written_by", "JANETTE OKE" ], [ "LOVE'S LONG JOURNEY", "written_by", "MICHAEL LANDON JR." ], [ "MISTER BUDDWING", "has_genre", "DRAMA" ], [ "MISTER BUDDWING", "starred_actors", "JEAN SIMMONS" ], [ "TABU", "directed_by", "MIGUEL GOMES" ], [ "TABU", "has_genre", "DRAMA" ], [ "TABU", "starred_actors", "MIGUEL GOMES" ], [ "TABU", "written_by", "MIGUEL GOMES" ], [ "THE ACTRESS", "has_genre", "DRAMA" ], [ "THE ACTRESS", "starred_actors", "JEAN SIMMONS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 19220, 21 29273, 7 FACES OF DR. LAO 6965, BLACKJACK 36066, FANTASY 34164, KATE BOSWORTH 26477, NICOLE GARCIA 11599, PLACE VENDÔME 37516, THE WARRIOR'S WAY src, edge_attr, dst 19220, has_tags, 6965 19220, has_tags, 34164 19220, starred_actors, 34164 29273, has_genre, 36066 6965, release_year, 2133 11599, directed_by, 26477 11599, release_year, 2133 11599, written_by, 26477 37516, has_genre, 36066 37516, starred_actors, 34164 Question: In what context are 21, 7 FACES OF DR. LAO, and NICOLE GARCIA connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "21", "7 FACES OF DR. LAO", "NICOLE GARCIA" ], "valid_edges": [ [ "21", "has_tags", "BLACKJACK" ], [ "21", "has_tags", "KATE BOSWORTH" ], [ "21", "starred_actors", "KATE BOSWORTH" ], [ "7 FACES OF DR. LAO", "has_genre", "FANTASY" ], [ "BLACKJACK", "release_year", "1998" ], [ "PLACE VENDÔME", "directed_by", "NICOLE GARCIA" ], [ "PLACE VENDÔME", "release_year", "1998" ], [ "PLACE VENDÔME", "written_by", "NICOLE GARCIA" ], [ "THE WARRIOR'S WAY", "has_genre", "FANTASY" ], [ "THE WARRIOR'S WAY", "starred_actors", "KATE BOSWORTH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26423, 1950 38097, 1985 37484, 2004 20576, A WORLD WITHOUT THIEVES 17521, ACES 'N' EIGHTS 39289, ACTION 35731, ACTION JACKSON 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 36077, AFTER EARTH 33087, AFTER THE SUNSET 16486, AGENT CODY BANKS 39750, ALIENS 38520, ALISON DOODY 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 34104, AMERICAN NINJA 38772, AN AMERICAN HIPPIE IN ISRAEL 35915, ANDREW MARTON 18598, APPLESEED 694, ASSAULT ON PRECINCT 13 10045, BD-R 19552, BEAU GESTE 19826, BLACK DEATH 39895, BLAST 38249, BORN TO FIGHT 22374, BREAKING NEWS 16749, BROKEN ARROW 16659, CASINO ROYALE 31692, CATWOMAN 6261, CELLULAR 30222, CHARLES WINKLER 524, CHARLIE'S ANGELS 5995, CLIFFHANGER 38098, CODE OF SILENCE 9636, COMMANDO 4283, CONAN THE BARBARIAN 16, CONGO 28192, COTTON COMES TO HARLEM 30802, CUTTHROAT ISLAND 22220, D.E.B.S. 8803, DEATH WISH 3 18348, DHOOM 26944, DICK TRACY 27800, DIRECT ACTION 12674, DON PAYNE 27950, ENTER THE DRAGON 5829, FIRE DOWN BELOW 6853, FIREWALKER 819, FIST OF THE NORTH STAR 10550, GALAXY QUEST 30810, GENE QUINTANO 23299, GET CARTER 28778, GOTCHA! 23775, HARD TICKET TO HAWAII 20504, HATARI! 34982, HELLBOY 25951, HIGHWAYMEN 5068, HOT SHOTS! PART DEUX 358, HOWARD THE DUCK 20625, I, ROBOT 22790, INDIANA JONES AND THE LAST CRUSADE 6083, INVASION U.S.A. 19805, J. LEE THOMPSON 20567, JOHN CARTER 38986, JUNGLE BOOK 14017, JURASSIC PARK 37798, JURASSIC PARK III 14156, KING SOLOMON'S MINES 9821, KUNG FU HUSTLE 31678, LE MANS 34533, LOGAN'S RUN 17855, MACGRUBER 31496, MAD MAX BEYOND THUNDERDOME 27174, MAIN HOON NA 22373, MAN ON FIRE 39027, MORTAL KOMBAT 32058, MUPPET TREASURE ISLAND 20433, NEW POLICE STORY 12081, NEXT OF KIN 9504, ON DEADLY GROUND 11031, OUT OF REACH 11796, PAPARAZZI 27541, PARODY 20348, PATHFINDER 26616, PATRICK SWAYZE 16004, PLANET TERROR 38688, POINT BREAK 3705, POLICE STORY 29299, RAIDERS OF THE LOST ARK 9555, RED HEAT 39610, RED SONJA 26663, RETROACTIVE 6512, RETROGRADE 607, RICHARD CHAMBERLAIN 11201, ROAD HOUSE 28221, ROMANCING THE STONE 23813, RUNAWAY TRAIN 35586, SAHARA 27807, SHAFT 38231, SHANGHAI NOON 23192, SHARON STONE 2473, SHOLAY 29005, SIN CITY 27140, SKY CAPTAIN AND THE WORLD OF TOMORROW 14350, SMOKEY AND THE BANDIT 34600, SPIDER-MAN 33904, SPY HARD 28357, ST. IVES 34989, STAR TREK 29830, STREETS OF BLOOD 2237, SUDDEN DEATH 17768, TARZAN AND THE LOST CITY 11699, TARZAN THE APE MAN 39736, TARZAN'S GREATEST ADVENTURE 10732, TAXI 13521, THE ADVENTURES OF FORD FAIRLANE 16103, THE AVENGERS 29403, THE BOURNE SUPREMACY 19351, THE COUNT OF MONTE CRISTO 30857, THE DEFENDER 18263, THE DUKES OF HAZZARD 2878, THE EVIL THAT MEN DO 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 19685, THE FINAL CUT 4068, THE GENERAL 9375, THE GREAT LOCOMOTIVE CHASE 15616, THE GUARDIAN 9166, THE GUNS OF NAVARONE 37902, THE HUNGER GAMES 19104, THE IN-LAWS 7447, THE INCREDIBLES 1443, THE ITALIAN JOB 18150, THE JEWEL OF THE NILE 5567, THE KEEPER 27237, THE LONGEST DAY 13295, THE MARK OF ZORRO 9580, THE PIRATES OF BLOOD RIVER 11498, THE POSEIDON ADVENTURE 19236, THE PROTECTOR 32051, THE PUNISHER 20287, THE SPECIALIST 26575, THOR 20377, THUNDERBIRDS 36584, TORQUE 13259, TOTAL RECALL 37876, TROMA'S WAR 5729, TROY 5560, UNSTOPPABLE 19088, VAN HELSING 25527, VICE 30520, WAKE OF DEATH 34133, WALKING TALL 23537, WHERE EAGLES DARE 36150, WILD GEESE II 5888, YEAR OF THE DRAGON src, edge_attr, dst 20576, has_genre, 39289 20576, release_year, 37484 17521, has_genre, 39289 17521, has_genre, 4763 35731, has_genre, 39289 35731, has_tags, 39289 35731, has_tags, 23192 35731, starred_actors, 23192 16054, has_genre, 39289 16054, has_genre, 4763 16054, has_tags, 4763 16054, has_tags, 10045 36077, has_genre, 39289 36077, has_genre, 4763 33087, has_genre, 39289 33087, release_year, 37484 16486, has_genre, 39289 16486, has_genre, 4763 16486, has_tags, 39289 39750, has_genre, 39289 39750, has_genre, 4763 39750, has_tags, 39289 22412, has_genre, 4763 22412, has_tags, 4763 22412, has_tags, 23192 22412, starred_actors, 607 22412, starred_actors, 23192 34104, has_genre, 39289 34104, has_tags, 39289 34104, release_year, 38097 38772, has_genre, 39289 38772, has_tags, 10045 18598, has_genre, 39289 18598, release_year, 37484 694, has_genre, 39289 694, has_tags, 39289 694, has_tags, 10045 19552, has_genre, 39289 19552, has_genre, 4763 19552, has_tags, 4763 19826, has_genre, 39289 19826, has_tags, 10045 39895, has_genre, 39289 39895, release_year, 37484 38249, has_genre, 39289 38249, release_year, 37484 22374, has_genre, 39289 22374, has_tags, 39289 22374, release_year, 37484 16749, has_genre, 39289 16749, has_tags, 39289 16749, release_year, 26423 16659, has_genre, 39289 16659, has_tags, 10045 31692, release_year, 37484 31692, starred_actors, 23192 6261, has_tags, 39289 6261, release_year, 37484 524, has_genre, 39289 524, has_genre, 4763 5995, has_genre, 39289 5995, has_genre, 4763 5995, has_tags, 39289 38098, has_genre, 39289 38098, release_year, 38097 9636, has_genre, 39289 9636, has_tags, 39289 9636, release_year, 38097 4283, has_genre, 39289 4283, has_genre, 4763 4283, has_tags, 39289 4283, has_tags, 4763 16, has_genre, 39289 16, has_genre, 4763 28192, has_genre, 39289 28192, has_tags, 10045 30802, has_genre, 39289 30802, has_genre, 4763 30802, has_tags, 39289 30802, has_tags, 4763 22220, has_genre, 39289 22220, has_tags, 27541 22220, release_year, 37484 8803, has_genre, 39289 8803, release_year, 38097 18348, has_genre, 39289 18348, release_year, 37484 26944, has_genre, 39289 26944, has_tags, 10045 27800, has_genre, 39289 27800, release_year, 37484 27950, has_genre, 39289 27950, has_tags, 10045 5829, has_genre, 39289 5829, has_genre, 4763 6853, directed_by, 19805 6853, has_genre, 39289 6853, has_genre, 4763 819, has_genre, 39289 819, has_tags, 10045 10550, has_genre, 4763 10550, has_tags, 27541 23299, has_genre, 39289 23299, has_tags, 10045 28778, has_genre, 39289 28778, release_year, 38097 23775, has_genre, 39289 23775, has_genre, 4763 20504, has_genre, 39289 20504, has_genre, 4763 34982, has_genre, 39289 34982, has_tags, 39289 34982, release_year, 37484 25951, has_genre, 39289 25951, release_year, 37484 5068, has_genre, 39289 5068, has_tags, 27541 358, has_genre, 39289 358, has_genre, 4763 358, has_tags, 39289 20625, has_genre, 39289 20625, has_tags, 39289 20625, release_year, 37484 22790, has_genre, 39289 22790, has_genre, 4763 22790, has_tags, 39289 22790, has_tags, 4763 22790, starred_actors, 38520 6083, has_genre, 39289 6083, release_year, 38097 20567, has_genre, 39289 20567, has_genre, 4763 20567, has_tags, 39289 20567, has_tags, 10045 38986, has_genre, 39289 38986, has_genre, 4763 38986, has_tags, 10045 14017, has_genre, 4763 14017, has_tags, 39289 14017, has_tags, 4763 37798, has_genre, 39289 37798, has_genre, 4763 37798, has_tags, 4763 14156, directed_by, 35915 14156, directed_by, 19805 14156, has_genre, 39289 14156, has_genre, 4763 14156, has_tags, 39289 14156, has_tags, 4763 14156, has_tags, 10045 14156, has_tags, 27541 14156, release_year, 26423 14156, release_year, 38097 14156, release_year, 37484 14156, starred_actors, 38520 14156, starred_actors, 26616 14156, starred_actors, 607 14156, starred_actors, 23192 14156, written_by, 30810 9821, has_genre, 39289 9821, has_tags, 39289 9821, release_year, 37484 31678, has_genre, 39289 31678, has_tags, 10045 34533, has_genre, 39289 34533, has_tags, 10045 17855, has_genre, 39289 17855, has_tags, 27541 31496, has_genre, 39289 31496, has_tags, 39289 31496, release_year, 38097 27174, has_genre, 39289 27174, release_year, 37484 22373, has_genre, 39289 22373, has_tags, 39289 22373, release_year, 37484 39027, has_genre, 39289 39027, has_genre, 4763 32058, has_genre, 39289 32058, has_genre, 4763 20433, has_genre, 39289 20433, release_year, 37484 12081, has_genre, 39289 12081, starred_actors, 26616 9504, has_genre, 39289 9504, has_genre, 4763 11031, has_genre, 39289 11031, release_year, 37484 11796, has_genre, 39289 11796, release_year, 37484 20348, has_genre, 39289 20348, has_genre, 4763 16004, has_genre, 39289 16004, has_tags, 10045 38688, has_genre, 39289 38688, has_tags, 26616 38688, starred_actors, 26616 3705, has_genre, 39289 3705, has_tags, 39289 3705, release_year, 38097 29299, has_genre, 39289 29299, has_genre, 4763 29299, has_tags, 39289 29299, has_tags, 4763 9555, has_genre, 39289 9555, has_tags, 39289 9555, release_year, 38097 39610, has_genre, 39289 39610, release_year, 38097 26663, has_genre, 39289 26663, has_genre, 4763 6512, has_genre, 39289 6512, release_year, 37484 11201, has_genre, 39289 11201, starred_actors, 26616 28221, has_genre, 39289 28221, has_genre, 4763 28221, has_tags, 39289 28221, has_tags, 4763 23813, has_genre, 39289 23813, release_year, 38097 35586, has_genre, 39289 35586, has_genre, 4763 35586, has_tags, 39289 35586, has_tags, 10045 27807, has_genre, 39289 27807, has_tags, 10045 38231, has_genre, 39289 38231, has_genre, 4763 2473, has_genre, 39289 2473, has_genre, 4763 29005, has_tags, 39289 29005, has_tags, 10045 27140, has_genre, 39289 27140, has_genre, 4763 27140, release_year, 37484 14350, has_genre, 39289 14350, has_tags, 10045 34600, has_genre, 39289 34600, has_genre, 4763 34600, has_tags, 39289 33904, has_genre, 39289 33904, has_tags, 27541 28357, directed_by, 19805 28357, has_genre, 39289 34989, has_genre, 39289 34989, has_genre, 4763 34989, has_tags, 39289 34989, has_tags, 4763 29830, directed_by, 30222 29830, has_genre, 39289 29830, starred_actors, 23192 2237, has_genre, 39289 2237, has_tags, 39289 2237, written_by, 30810 17768, has_genre, 39289 17768, has_genre, 4763 11699, has_genre, 39289 11699, has_genre, 4763 11699, has_tags, 10045 39736, has_genre, 39289 39736, has_genre, 4763 10732, has_genre, 39289 10732, release_year, 37484 13521, has_genre, 39289 13521, has_genre, 4763 16103, has_genre, 39289 16103, has_tags, 26575 29403, has_genre, 39289 29403, has_tags, 39289 29403, release_year, 37484 19351, has_genre, 39289 19351, has_genre, 4763 19351, has_tags, 4763 30857, has_genre, 39289 30857, release_year, 37484 18263, has_genre, 39289 18263, has_genre, 4763 2878, directed_by, 19805 2878, has_genre, 39289 10344, has_genre, 39289 10344, has_genre, 4763 19685, has_genre, 39289 19685, release_year, 37484 4068, has_genre, 39289 4068, has_genre, 4763 9375, has_genre, 39289 9375, has_genre, 4763 15616, has_genre, 39289 15616, has_genre, 4763 15616, has_tags, 39289 9166, directed_by, 19805 9166, has_genre, 39289 9166, has_genre, 4763 9166, has_tags, 39289 9166, has_tags, 10045 9166, has_tags, 19805 37902, has_genre, 4763 37902, has_tags, 39289 19104, has_genre, 39289 19104, has_tags, 10045 7447, has_tags, 10045 7447, release_year, 37484 1443, has_genre, 39289 1443, has_tags, 39289 1443, has_tags, 10045 18150, has_genre, 39289 18150, has_genre, 4763 18150, has_tags, 4763 18150, release_year, 38097 5567, has_genre, 39289 5567, release_year, 37484 27237, directed_by, 35915 27237, has_genre, 39289 27237, has_tags, 39289 13295, has_genre, 39289 13295, has_genre, 4763 13295, has_tags, 10045 9580, has_genre, 39289 9580, has_tags, 10045 11498, has_genre, 39289 11498, has_genre, 4763 19236, has_genre, 39289 19236, release_year, 38097 32051, has_genre, 39289 32051, has_tags, 39289 32051, release_year, 37484 20287, has_genre, 39289 20287, has_tags, 23192 20287, starred_actors, 23192 26575, written_by, 12674 20377, has_genre, 39289 20377, has_genre, 4763 20377, release_year, 37484 36584, has_genre, 39289 36584, release_year, 37484 13259, has_genre, 39289 13259, has_tags, 39289 13259, has_tags, 23192 13259, starred_actors, 23192 37876, has_genre, 39289 37876, has_genre, 4763 5729, has_genre, 4763 5729, has_tags, 39289 5729, release_year, 37484 5560, has_genre, 39289 5560, release_year, 37484 19088, has_genre, 39289 19088, release_year, 37484 25527, has_genre, 39289 25527, has_genre, 4763 30520, has_genre, 39289 30520, release_year, 37484 34133, has_genre, 39289 34133, release_year, 37484 23537, has_genre, 39289 23537, has_tags, 10045 36150, has_genre, 39289 36150, release_year, 38097 5888, has_genre, 39289 5888, has_tags, 39289 5888, release_year, 38097 Question: For what reason are CHARLES WINKLER, DON PAYNE, and KING SOLOMON'S MINES associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHARLES WINKLER", "DON PAYNE", "KING SOLOMON'S MINES" ], "valid_edges": [ [ "A WORLD WITHOUT THIEVES", "has_genre", "ACTION" ], [ "A WORLD WITHOUT THIEVES", "release_year", "2004" ], [ "ACES 'N' EIGHTS", "has_genre", "ACTION" ], [ "ACES 'N' EIGHTS", "has_genre", "ADVENTURE" ], [ "ACTION JACKSON", "has_genre", "ACTION" ], [ "ACTION JACKSON", "has_tags", "ACTION" ], [ "ACTION JACKSON", "has_tags", "SHARON STONE" ], [ "ACTION JACKSON", "starred_actors", "SHARON STONE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ACTION" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "BD-R" ], [ "AFTER EARTH", "has_genre", "ACTION" ], [ "AFTER EARTH", "has_genre", "ADVENTURE" ], [ "AFTER THE SUNSET", "has_genre", "ACTION" ], [ "AFTER THE SUNSET", "release_year", "2004" ], [ "AGENT CODY BANKS", "has_genre", "ACTION" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_tags", "ACTION" ], [ "ALIENS", "has_genre", "ACTION" ], [ "ALIENS", "has_genre", "ADVENTURE" ], [ "ALIENS", "has_tags", "ACTION" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "SHARON STONE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "starred_actors", "RICHARD CHAMBERLAIN" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "starred_actors", "SHARON STONE" ], [ "AMERICAN NINJA", "has_genre", "ACTION" ], [ "AMERICAN NINJA", "has_tags", "ACTION" ], [ "AMERICAN NINJA", "release_year", "1985" ], [ "AN AMERICAN HIPPIE IN ISRAEL", "has_genre", "ACTION" ], [ "AN AMERICAN HIPPIE IN ISRAEL", "has_tags", "BD-R" ], [ "APPLESEED", "has_genre", "ACTION" ], [ "APPLESEED", "release_year", "2004" ], [ "ASSAULT ON PRECINCT 13", "has_genre", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "ACTION" ], [ "ASSAULT ON PRECINCT 13", "has_tags", "BD-R" ], [ "BEAU GESTE", "has_genre", "ACTION" ], [ "BEAU GESTE", "has_genre", "ADVENTURE" ], [ "BEAU GESTE", "has_tags", "ADVENTURE" ], [ "BLACK DEATH", "has_genre", "ACTION" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLAST", "has_genre", "ACTION" ], [ "BLAST", "release_year", "2004" ], [ "BORN TO FIGHT", "has_genre", "ACTION" ], [ "BORN TO FIGHT", "release_year", "2004" ], [ "BREAKING NEWS", "has_genre", "ACTION" ], [ "BREAKING NEWS", "has_tags", "ACTION" ], [ "BREAKING NEWS", "release_year", "2004" ], [ "BROKEN ARROW", "has_genre", "ACTION" ], [ "BROKEN ARROW", "has_tags", "ACTION" ], [ "BROKEN ARROW", "release_year", "1950" ], [ "CASINO ROYALE", "has_genre", "ACTION" ], [ "CASINO ROYALE", "has_tags", "BD-R" ], [ "CATWOMAN", "release_year", "2004" ], [ "CATWOMAN", "starred_actors", "SHARON STONE" ], [ "CELLULAR", "has_tags", "ACTION" ], [ "CELLULAR", "release_year", "2004" ], [ "CHARLIE'S ANGELS", "has_genre", "ACTION" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CLIFFHANGER", "has_genre", "ACTION" ], [ "CLIFFHANGER", "has_genre", "ADVENTURE" ], [ "CLIFFHANGER", "has_tags", "ACTION" ], [ "CODE OF SILENCE", "has_genre", "ACTION" ], [ "CODE OF SILENCE", "release_year", "1985" ], [ "COMMANDO", "has_genre", "ACTION" ], [ "COMMANDO", "has_tags", "ACTION" ], [ "COMMANDO", "release_year", "1985" ], [ "CONAN THE BARBARIAN", "has_genre", "ACTION" ], [ "CONAN THE BARBARIAN", "has_genre", "ADVENTURE" ], [ "CONAN THE BARBARIAN", "has_tags", "ACTION" ], [ "CONAN THE BARBARIAN", "has_tags", "ADVENTURE" ], [ "CONGO", "has_genre", "ACTION" ], [ "CONGO", "has_genre", "ADVENTURE" ], [ "COTTON COMES TO HARLEM", "has_genre", "ACTION" ], [ "COTTON COMES TO HARLEM", "has_tags", "BD-R" ], [ "CUTTHROAT ISLAND", "has_genre", "ACTION" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_tags", "ACTION" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "D.E.B.S.", "has_genre", "ACTION" ], [ "D.E.B.S.", "has_tags", "PARODY" ], [ "D.E.B.S.", "release_year", "2004" ], [ "DEATH WISH 3", "has_genre", "ACTION" ], [ "DEATH WISH 3", "release_year", "1985" ], [ "DHOOM", "has_genre", "ACTION" ], [ "DHOOM", "release_year", "2004" ], [ "DICK TRACY", "has_genre", "ACTION" ], [ "DICK TRACY", "has_tags", "BD-R" ], [ "DIRECT ACTION", "has_genre", "ACTION" ], [ "DIRECT ACTION", "release_year", "2004" ], [ "ENTER THE DRAGON", "has_genre", "ACTION" ], [ "ENTER THE DRAGON", "has_tags", "BD-R" ], [ "FIRE DOWN BELOW", "has_genre", "ACTION" ], [ "FIRE DOWN BELOW", "has_genre", "ADVENTURE" ], [ "FIREWALKER", "directed_by", "J. LEE THOMPSON" ], [ "FIREWALKER", "has_genre", "ACTION" ], [ "FIREWALKER", "has_genre", "ADVENTURE" ], [ "FIST OF THE NORTH STAR", "has_genre", "ACTION" ], [ "FIST OF THE NORTH STAR", "has_tags", "BD-R" ], [ "GALAXY QUEST", "has_genre", "ADVENTURE" ], [ "GALAXY QUEST", "has_tags", "PARODY" ], [ "GET CARTER", "has_genre", "ACTION" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "GOTCHA!", "has_genre", "ACTION" ], [ "GOTCHA!", "release_year", "1985" ], [ "HARD TICKET TO HAWAII", "has_genre", "ACTION" ], [ "HARD TICKET TO HAWAII", "has_genre", "ADVENTURE" ], [ "HATARI!", "has_genre", "ACTION" ], [ "HATARI!", "has_genre", "ADVENTURE" ], [ "HELLBOY", "has_genre", "ACTION" ], [ "HELLBOY", "has_tags", "ACTION" ], [ "HELLBOY", "release_year", "2004" ], [ "HIGHWAYMEN", "has_genre", "ACTION" ], [ "HIGHWAYMEN", "release_year", "2004" ], [ "HOT SHOTS! PART DEUX", "has_genre", "ACTION" ], [ "HOT SHOTS! PART DEUX", "has_tags", "PARODY" ], [ "HOWARD THE DUCK", "has_genre", "ACTION" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_tags", "ACTION" ], [ "I, ROBOT", "has_genre", "ACTION" ], [ "I, ROBOT", "has_tags", "ACTION" ], [ "I, ROBOT", "release_year", "2004" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_genre", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ACTION" ], [ "INDIANA JONES AND THE LAST CRUSADE", "has_tags", "ADVENTURE" ], [ "INDIANA JONES AND THE LAST CRUSADE", "starred_actors", "ALISON DOODY" ], [ "INVASION U.S.A.", "has_genre", "ACTION" ], [ "INVASION U.S.A.", "release_year", "1985" ], [ "JOHN CARTER", "has_genre", "ACTION" ], [ "JOHN CARTER", "has_genre", "ADVENTURE" ], [ "JOHN CARTER", "has_tags", "ACTION" ], [ "JOHN CARTER", "has_tags", "BD-R" ], [ "JUNGLE BOOK", "has_genre", "ACTION" ], [ "JUNGLE BOOK", "has_genre", "ADVENTURE" ], [ "JUNGLE BOOK", "has_tags", "BD-R" ], [ "JURASSIC PARK", "has_genre", "ADVENTURE" ], [ "JURASSIC PARK", "has_tags", "ACTION" ], [ "JURASSIC PARK", "has_tags", "ADVENTURE" ], [ "JURASSIC PARK III", "has_genre", "ACTION" ], [ "JURASSIC PARK III", "has_genre", "ADVENTURE" ], [ "JURASSIC PARK III", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "directed_by", "ANDREW MARTON" ], [ "KING SOLOMON'S MINES", "directed_by", "J. LEE THOMPSON" ], [ "KING SOLOMON'S MINES", "has_genre", "ACTION" ], [ "KING SOLOMON'S MINES", "has_genre", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "ACTION" ], [ "KING SOLOMON'S MINES", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KING SOLOMON'S MINES", "has_tags", "PARODY" ], [ "KING SOLOMON'S MINES", "release_year", "1950" ], [ "KING SOLOMON'S MINES", "release_year", "1985" ], [ "KING SOLOMON'S MINES", "release_year", "2004" ], [ "KING SOLOMON'S MINES", "starred_actors", "ALISON DOODY" ], [ "KING SOLOMON'S MINES", "starred_actors", "PATRICK SWAYZE" ], [ "KING SOLOMON'S MINES", "starred_actors", "RICHARD CHAMBERLAIN" ], [ "KING SOLOMON'S MINES", "starred_actors", "SHARON STONE" ], [ "KING SOLOMON'S MINES", "written_by", "GENE QUINTANO" ], [ "KUNG FU HUSTLE", "has_genre", "ACTION" ], [ "KUNG FU HUSTLE", "has_tags", "ACTION" ], [ "KUNG FU HUSTLE", "release_year", "2004" ], [ "LE MANS", "has_genre", "ACTION" ], [ "LE MANS", "has_tags", "BD-R" ], [ "LOGAN'S RUN", "has_genre", "ACTION" ], [ "LOGAN'S RUN", "has_tags", "BD-R" ], [ "MACGRUBER", "has_genre", "ACTION" ], [ "MACGRUBER", "has_tags", "PARODY" ], [ "MAD MAX BEYOND THUNDERDOME", "has_genre", "ACTION" ], [ "MAD MAX BEYOND THUNDERDOME", "has_tags", "ACTION" ], [ "MAD MAX BEYOND THUNDERDOME", "release_year", "1985" ], [ "MAIN HOON NA", "has_genre", "ACTION" ], [ "MAIN HOON NA", "release_year", "2004" ], [ "MAN ON FIRE", "has_genre", "ACTION" ], [ "MAN ON FIRE", "has_tags", "ACTION" ], [ "MAN ON FIRE", "release_year", "2004" ], [ "MORTAL KOMBAT", "has_genre", "ACTION" ], [ "MORTAL KOMBAT", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ACTION" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "NEW POLICE STORY", "has_genre", "ACTION" ], [ "NEW POLICE STORY", "release_year", "2004" ], [ "NEXT OF KIN", "has_genre", "ACTION" ], [ "NEXT OF KIN", "starred_actors", "PATRICK SWAYZE" ], [ "ON DEADLY GROUND", "has_genre", "ACTION" ], [ "ON DEADLY GROUND", "has_genre", "ADVENTURE" ], [ "OUT OF REACH", "has_genre", "ACTION" ], [ "OUT OF REACH", "release_year", "2004" ], [ "PAPARAZZI", "has_genre", "ACTION" ], [ "PAPARAZZI", "release_year", "2004" ], [ "PATHFINDER", "has_genre", "ACTION" ], [ "PATHFINDER", "has_genre", "ADVENTURE" ], [ "PLANET TERROR", "has_genre", "ACTION" ], [ "PLANET TERROR", "has_tags", "BD-R" ], [ "POINT BREAK", "has_genre", "ACTION" ], [ "POINT BREAK", "has_tags", "PATRICK SWAYZE" ], [ "POINT BREAK", "starred_actors", "PATRICK SWAYZE" ], [ "POLICE STORY", "has_genre", "ACTION" ], [ "POLICE STORY", "has_tags", "ACTION" ], [ "POLICE STORY", "release_year", "1985" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_genre", "ADVENTURE" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ACTION" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "ADVENTURE" ], [ "RED HEAT", "has_genre", "ACTION" ], [ "RED HEAT", "has_tags", "ACTION" ], [ "RED HEAT", "release_year", "1985" ], [ "RED SONJA", "has_genre", "ACTION" ], [ "RED SONJA", "release_year", "1985" ], [ "RETROACTIVE", "has_genre", "ACTION" ], [ "RETROACTIVE", "has_genre", "ADVENTURE" ], [ "RETROGRADE", "has_genre", "ACTION" ], [ "RETROGRADE", "release_year", "2004" ], [ "ROAD HOUSE", "has_genre", "ACTION" ], [ "ROAD HOUSE", "starred_actors", "PATRICK SWAYZE" ], [ "ROMANCING THE STONE", "has_genre", "ACTION" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_tags", "ACTION" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "RUNAWAY TRAIN", "has_genre", "ACTION" ], [ "RUNAWAY TRAIN", "release_year", "1985" ], [ "SAHARA", "has_genre", "ACTION" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_tags", "ACTION" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SHAFT", "has_genre", "ACTION" ], [ "SHAFT", "has_tags", "BD-R" ], [ "SHANGHAI NOON", "has_genre", "ACTION" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHOLAY", "has_genre", "ACTION" ], [ "SHOLAY", "has_genre", "ADVENTURE" ], [ "SIN CITY", "has_tags", "ACTION" ], [ "SIN CITY", "has_tags", "BD-R" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "has_genre", "ACTION" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "has_genre", "ADVENTURE" ], [ "SKY CAPTAIN AND THE WORLD OF TOMORROW", "release_year", "2004" ], [ "SMOKEY AND THE BANDIT", "has_genre", "ACTION" ], [ "SMOKEY AND THE BANDIT", "has_tags", "BD-R" ], [ "SPIDER-MAN", "has_genre", "ACTION" ], [ "SPIDER-MAN", "has_genre", "ADVENTURE" ], [ "SPIDER-MAN", "has_tags", "ACTION" ], [ "SPY HARD", "has_genre", "ACTION" ], [ "SPY HARD", "has_tags", "PARODY" ], [ "ST. IVES", "directed_by", "J. LEE THOMPSON" ], [ "ST. IVES", "has_genre", "ACTION" ], [ "STAR TREK", "has_genre", "ACTION" ], [ "STAR TREK", "has_genre", "ADVENTURE" ], [ "STAR TREK", "has_tags", "ACTION" ], [ "STAR TREK", "has_tags", "ADVENTURE" ], [ "STREETS OF BLOOD", "directed_by", "CHARLES WINKLER" ], [ "STREETS OF BLOOD", "has_genre", "ACTION" ], [ "STREETS OF BLOOD", "starred_actors", "SHARON STONE" ], [ "SUDDEN DEATH", "has_genre", "ACTION" ], [ "SUDDEN DEATH", "has_tags", "ACTION" ], [ "SUDDEN DEATH", "written_by", "GENE QUINTANO" ], [ "TARZAN AND THE LOST CITY", "has_genre", "ACTION" ], [ "TARZAN AND THE LOST CITY", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_genre", "ACTION" ], [ "TARZAN THE APE MAN", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_tags", "BD-R" ], [ "TARZAN'S GREATEST ADVENTURE", "has_genre", "ACTION" ], [ "TARZAN'S GREATEST ADVENTURE", "has_genre", "ADVENTURE" ], [ "TAXI", "has_genre", "ACTION" ], [ "TAXI", "release_year", "2004" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ACTION" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE AVENGERS", "has_genre", "ACTION" ], [ "THE AVENGERS", "has_tags", "THOR" ], [ "THE BOURNE SUPREMACY", "has_genre", "ACTION" ], [ "THE BOURNE SUPREMACY", "has_tags", "ACTION" ], [ "THE BOURNE SUPREMACY", "release_year", "2004" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ACTION" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "ADVENTURE" ], [ "THE COUNT OF MONTE CRISTO", "has_tags", "ADVENTURE" ], [ "THE DEFENDER", "has_genre", "ACTION" ], [ "THE DEFENDER", "release_year", "2004" ], [ "THE DUKES OF HAZZARD", "has_genre", "ACTION" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE EVIL THAT MEN DO", "directed_by", "J. LEE THOMPSON" ], [ "THE EVIL THAT MEN DO", "has_genre", "ACTION" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "ACTION" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "ADVENTURE" ], [ "THE FINAL CUT", "has_genre", "ACTION" ], [ "THE FINAL CUT", "release_year", "2004" ], [ "THE GENERAL", "has_genre", "ACTION" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GREAT LOCOMOTIVE CHASE", "has_genre", "ACTION" ], [ "THE GREAT LOCOMOTIVE CHASE", "has_genre", "ADVENTURE" ], [ "THE GUARDIAN", "has_genre", "ACTION" ], [ "THE GUARDIAN", "has_genre", "ADVENTURE" ], [ "THE GUARDIAN", "has_tags", "ACTION" ], [ "THE GUNS OF NAVARONE", "directed_by", "J. LEE THOMPSON" ], [ "THE GUNS OF NAVARONE", "has_genre", "ACTION" ], [ "THE GUNS OF NAVARONE", "has_genre", "ADVENTURE" ], [ "THE GUNS OF NAVARONE", "has_tags", "ACTION" ], [ "THE GUNS OF NAVARONE", "has_tags", "BD-R" ], [ "THE GUNS OF NAVARONE", "has_tags", "J. LEE THOMPSON" ], [ "THE HUNGER GAMES", "has_genre", "ADVENTURE" ], [ "THE HUNGER GAMES", "has_tags", "ACTION" ], [ "THE IN-LAWS", "has_genre", "ACTION" ], [ "THE IN-LAWS", "has_tags", "BD-R" ], [ "THE INCREDIBLES", "has_tags", "BD-R" ], [ "THE INCREDIBLES", "release_year", "2004" ], [ "THE ITALIAN JOB", "has_genre", "ACTION" ], [ "THE ITALIAN JOB", "has_tags", "ACTION" ], [ "THE ITALIAN JOB", "has_tags", "BD-R" ], [ "THE JEWEL OF THE NILE", "has_genre", "ACTION" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "release_year", "1985" ], [ "THE KEEPER", "has_genre", "ACTION" ], [ "THE KEEPER", "release_year", "2004" ], [ "THE LONGEST DAY", "directed_by", "ANDREW MARTON" ], [ "THE LONGEST DAY", "has_genre", "ACTION" ], [ "THE LONGEST DAY", "has_tags", "ACTION" ], [ "THE MARK OF ZORRO", "has_genre", "ACTION" ], [ "THE MARK OF ZORRO", "has_genre", "ADVENTURE" ], [ "THE MARK OF ZORRO", "has_tags", "BD-R" ], [ "THE PIRATES OF BLOOD RIVER", "has_genre", "ACTION" ], [ "THE PIRATES OF BLOOD RIVER", "has_tags", "BD-R" ], [ "THE POSEIDON ADVENTURE", "has_genre", "ACTION" ], [ "THE POSEIDON ADVENTURE", "has_genre", "ADVENTURE" ], [ "THE PROTECTOR", "has_genre", "ACTION" ], [ "THE PROTECTOR", "release_year", "1985" ], [ "THE PUNISHER", "has_genre", "ACTION" ], [ "THE PUNISHER", "has_tags", "ACTION" ], [ "THE PUNISHER", "release_year", "2004" ], [ "THE SPECIALIST", "has_genre", "ACTION" ], [ "THE SPECIALIST", "has_tags", "SHARON STONE" ], [ "THE SPECIALIST", "starred_actors", "SHARON STONE" ], [ "THOR", "written_by", "DON PAYNE" ], [ "THUNDERBIRDS", "has_genre", "ACTION" ], [ "THUNDERBIRDS", "has_genre", "ADVENTURE" ], [ "THUNDERBIRDS", "release_year", "2004" ], [ "TORQUE", "has_genre", "ACTION" ], [ "TORQUE", "release_year", "2004" ], [ "TOTAL RECALL", "has_genre", "ACTION" ], [ "TOTAL RECALL", "has_tags", "ACTION" ], [ "TOTAL RECALL", "has_tags", "SHARON STONE" ], [ "TOTAL RECALL", "starred_actors", "SHARON STONE" ], [ "TROMA'S WAR", "has_genre", "ACTION" ], [ "TROMA'S WAR", "has_genre", "ADVENTURE" ], [ "TROY", "has_genre", "ADVENTURE" ], [ "TROY", "has_tags", "ACTION" ], [ "TROY", "release_year", "2004" ], [ "UNSTOPPABLE", "has_genre", "ACTION" ], [ "UNSTOPPABLE", "release_year", "2004" ], [ "VAN HELSING", "has_genre", "ACTION" ], [ "VAN HELSING", "release_year", "2004" ], [ "VICE", "has_genre", "ACTION" ], [ "VICE", "has_genre", "ADVENTURE" ], [ "WAKE OF DEATH", "has_genre", "ACTION" ], [ "WAKE OF DEATH", "release_year", "2004" ], [ "WALKING TALL", "has_genre", "ACTION" ], [ "WALKING TALL", "release_year", "2004" ], [ "WHERE EAGLES DARE", "has_genre", "ACTION" ], [ "WHERE EAGLES DARE", "has_tags", "BD-R" ], [ "WILD GEESE II", "has_genre", "ACTION" ], [ "WILD GEESE II", "release_year", "1985" ], [ "YEAR OF THE DRAGON", "has_genre", "ACTION" ], [ "YEAR OF THE DRAGON", "has_tags", "ACTION" ], [ "YEAR OF THE DRAGON", "release_year", "1985" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8539, 1982 20033, ANGEL 28344, ANGUS 39876, ANNIE 18131, BABE 12144, BAD BOYS 18725, BAREFOOT 20940, BEACHES 29743, BEST FRIENDS 9097, BLADE RUNNER 350, BOYS ON THE SIDE 30463, COMEDY 2171, COUSINS 39230, DAD 39164, DINER 20842, DR. JEKYLL AND MS. HYDE 36212, DRAMA 10941, DRIVING MISS DAISY 24672, EVERSMILE, NEW JERSEY 11065, FATAL INSTINCT 34555, FLAWLESS 6223, FUNNY BONES 2155, GEORGIA RULE 29107, HARLEM NIGHTS 33887, HOME FOR THE HOLIDAYS 2055, LIVING IN OBLIVION 27801, MAN OF THE YEAR 16428, MUMFORD 2654, NOTHING IN COMMON 25824, PARADISE 5023, PARENTHOOD 29620, POLICE 13081, R 5693, RAISING HELEN 27430, ROOMMATES 4689, SABRINA 22312, SAY ANYTHING... 34917, SEAN YOUNG 30536, SHIRLEY VALENTINE 9274, SIX PACK 13768, SLEEPY HOLLOW 20971, SOMETHING TO TALK ABOUT 20689, STARSTRUCK 25135, STAYING TOGETHER 29867, STEEL MAGNOLIAS 18733, STONEWALL 2819, TEMPEST 2633, THE AMERICAN PRESIDENT 4789, THE BROTHERS MCMULLEN 24493, THE FUNERAL 39138, THE GRASS HARP 20291, THE WIZARD 38787, THE WORLD ACCORDING TO GARP 37331, TO DIE FOR 1459, TOO BEAUTIFUL FOR YOU 30585, TWISTER 9183, UNSTRUNG HEROES 17257, WASHINGTON IRVING 18629, YOUNG DOCTORS IN LOVE src, edge_attr, dst 20033, has_genre, 30463 20033, has_genre, 36212 28344, has_genre, 30463 28344, has_genre, 36212 39876, has_genre, 30463 39876, has_genre, 36212 18131, has_genre, 30463 18131, has_genre, 36212 12144, has_genre, 30463 12144, has_genre, 36212 12144, has_tags, 30463 18725, has_genre, 30463 18725, has_genre, 36212 20940, has_genre, 30463 20940, has_genre, 36212 29743, has_genre, 30463 29743, has_genre, 36212 9097, has_tags, 29620 9097, has_tags, 13081 9097, has_tags, 34917 9097, release_year, 8539 9097, starred_actors, 34917 350, has_genre, 30463 350, has_genre, 36212 2171, has_genre, 30463 2171, starred_actors, 34917 39230, has_genre, 30463 39230, has_genre, 36212 39164, has_genre, 30463 39164, has_genre, 36212 20842, has_genre, 30463 20842, starred_actors, 34917 10941, has_genre, 30463 10941, has_genre, 36212 10941, has_tags, 36212 24672, has_genre, 30463 24672, has_genre, 36212 11065, has_genre, 30463 11065, starred_actors, 34917 34555, has_genre, 30463 34555, has_genre, 36212 6223, has_genre, 30463 6223, has_genre, 36212 2155, has_genre, 30463 2155, has_genre, 36212 29107, has_genre, 30463 29107, has_genre, 36212 33887, has_genre, 30463 33887, has_genre, 36212 2055, has_genre, 30463 2055, has_genre, 36212 27801, has_genre, 30463 27801, has_genre, 36212 27801, has_tags, 30463 16428, has_genre, 30463 16428, has_genre, 36212 2654, has_genre, 30463 2654, has_genre, 36212 25824, has_genre, 30463 25824, has_genre, 36212 5023, has_genre, 30463 5023, has_genre, 36212 5023, has_tags, 30463 29620, has_genre, 36212 5693, has_genre, 30463 5693, has_genre, 36212 27430, has_genre, 30463 27430, has_genre, 36212 4689, has_genre, 30463 4689, has_genre, 36212 4689, has_tags, 36212 22312, has_genre, 30463 22312, has_genre, 36212 30536, has_genre, 30463 30536, has_genre, 36212 9274, has_genre, 30463 9274, has_genre, 36212 13768, has_tags, 13081 13768, written_by, 17257 20971, has_genre, 30463 20971, has_genre, 36212 20689, has_genre, 30463 20689, has_genre, 36212 25135, has_genre, 30463 25135, has_genre, 36212 29867, has_genre, 30463 29867, has_genre, 36212 18733, has_genre, 30463 18733, has_genre, 36212 2819, has_genre, 30463 2819, has_genre, 36212 2633, has_genre, 30463 2633, has_genre, 36212 2633, has_tags, 36212 4789, has_genre, 30463 4789, has_genre, 36212 24493, has_genre, 30463 24493, has_genre, 36212 39138, has_genre, 30463 39138, has_genre, 36212 20291, has_genre, 30463 20291, has_genre, 36212 38787, has_genre, 30463 38787, has_genre, 36212 37331, has_genre, 30463 37331, has_genre, 36212 1459, has_genre, 30463 1459, has_genre, 36212 30585, has_genre, 30463 30585, has_genre, 36212 9183, has_genre, 30463 9183, has_genre, 36212 18629, has_genre, 30463 18629, release_year, 8539 18629, starred_actors, 34917 Question: For what reason are BAREFOOT, SEAN YOUNG, and WASHINGTON IRVING associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BAREFOOT", "SEAN YOUNG", "WASHINGTON IRVING" ], "valid_edges": [ [ "ANGEL", "has_genre", "COMEDY" ], [ "ANGEL", "has_genre", "DRAMA" ], [ "ANGUS", "has_genre", "COMEDY" ], [ "ANGUS", "has_genre", "DRAMA" ], [ "ANNIE", "has_genre", "COMEDY" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "BABE", "has_genre", "COMEDY" ], [ "BABE", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_genre", "COMEDY" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_tags", "COMEDY" ], [ "BAREFOOT", "has_genre", "COMEDY" ], [ "BAREFOOT", "has_genre", "DRAMA" ], [ "BEACHES", "has_genre", "COMEDY" ], [ "BEACHES", "has_genre", "DRAMA" ], [ "BEST FRIENDS", "has_genre", "COMEDY" ], [ "BEST FRIENDS", "has_genre", "DRAMA" ], [ "BLADE RUNNER", "has_tags", "POLICE" ], [ "BLADE RUNNER", "has_tags", "R" ], [ "BLADE RUNNER", "has_tags", "SEAN YOUNG" ], [ "BLADE RUNNER", "release_year", "1982" ], [ "BLADE RUNNER", "starred_actors", "SEAN YOUNG" ], [ "BOYS ON THE SIDE", "has_genre", "COMEDY" ], [ "BOYS ON THE SIDE", "has_genre", "DRAMA" ], [ "COUSINS", "has_genre", "COMEDY" ], [ "COUSINS", "starred_actors", "SEAN YOUNG" ], [ "DAD", "has_genre", "COMEDY" ], [ "DAD", "has_genre", "DRAMA" ], [ "DINER", "has_genre", "COMEDY" ], [ "DINER", "has_genre", "DRAMA" ], [ "DR. JEKYLL AND MS. HYDE", "has_genre", "COMEDY" ], [ "DR. JEKYLL AND MS. HYDE", "starred_actors", "SEAN YOUNG" ], [ "DRIVING MISS DAISY", "has_genre", "COMEDY" ], [ "DRIVING MISS DAISY", "has_genre", "DRAMA" ], [ "DRIVING MISS DAISY", "has_tags", "DRAMA" ], [ "EVERSMILE, NEW JERSEY", "has_genre", "COMEDY" ], [ "EVERSMILE, NEW JERSEY", "has_genre", "DRAMA" ], [ "FATAL INSTINCT", "has_genre", "COMEDY" ], [ "FATAL INSTINCT", "starred_actors", "SEAN YOUNG" ], [ "FLAWLESS", "has_genre", "COMEDY" ], [ "FLAWLESS", "has_genre", "DRAMA" ], [ "FUNNY BONES", "has_genre", "COMEDY" ], [ "FUNNY BONES", "has_genre", "DRAMA" ], [ "GEORGIA RULE", "has_genre", "COMEDY" ], [ "GEORGIA RULE", "has_genre", "DRAMA" ], [ "HARLEM NIGHTS", "has_genre", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "DRAMA" ], [ "HOME FOR THE HOLIDAYS", "has_genre", "COMEDY" ], [ "HOME FOR THE HOLIDAYS", "has_genre", "DRAMA" ], [ "LIVING IN OBLIVION", "has_genre", "COMEDY" ], [ "LIVING IN OBLIVION", "has_genre", "DRAMA" ], [ "MAN OF THE YEAR", "has_genre", "COMEDY" ], [ "MAN OF THE YEAR", "has_genre", "DRAMA" ], [ "MAN OF THE YEAR", "has_tags", "COMEDY" ], [ "MUMFORD", "has_genre", "COMEDY" ], [ "MUMFORD", "has_genre", "DRAMA" ], [ "NOTHING IN COMMON", "has_genre", "COMEDY" ], [ "NOTHING IN COMMON", "has_genre", "DRAMA" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_genre", "COMEDY" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "COMEDY" ], [ "POLICE", "has_genre", "DRAMA" ], [ "RAISING HELEN", "has_genre", "COMEDY" ], [ "RAISING HELEN", "has_genre", "DRAMA" ], [ "ROOMMATES", "has_genre", "COMEDY" ], [ "ROOMMATES", "has_genre", "DRAMA" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "has_genre", "DRAMA" ], [ "SABRINA", "has_tags", "DRAMA" ], [ "SAY ANYTHING...", "has_genre", "COMEDY" ], [ "SAY ANYTHING...", "has_genre", "DRAMA" ], [ "SHIRLEY VALENTINE", "has_genre", "COMEDY" ], [ "SHIRLEY VALENTINE", "has_genre", "DRAMA" ], [ "SIX PACK", "has_genre", "COMEDY" ], [ "SIX PACK", "has_genre", "DRAMA" ], [ "SLEEPY HOLLOW", "has_tags", "R" ], [ "SLEEPY HOLLOW", "written_by", "WASHINGTON IRVING" ], [ "SOMETHING TO TALK ABOUT", "has_genre", "COMEDY" ], [ "SOMETHING TO TALK ABOUT", "has_genre", "DRAMA" ], [ "STARSTRUCK", "has_genre", "COMEDY" ], [ "STARSTRUCK", "has_genre", "DRAMA" ], [ "STAYING TOGETHER", "has_genre", "COMEDY" ], [ "STAYING TOGETHER", "has_genre", "DRAMA" ], [ "STEEL MAGNOLIAS", "has_genre", "COMEDY" ], [ "STEEL MAGNOLIAS", "has_genre", "DRAMA" ], [ "STONEWALL", "has_genre", "COMEDY" ], [ "STONEWALL", "has_genre", "DRAMA" ], [ "TEMPEST", "has_genre", "COMEDY" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_genre", "COMEDY" ], [ "THE AMERICAN PRESIDENT", "has_genre", "DRAMA" ], [ "THE AMERICAN PRESIDENT", "has_tags", "DRAMA" ], [ "THE BROTHERS MCMULLEN", "has_genre", "COMEDY" ], [ "THE BROTHERS MCMULLEN", "has_genre", "DRAMA" ], [ "THE FUNERAL", "has_genre", "COMEDY" ], [ "THE FUNERAL", "has_genre", "DRAMA" ], [ "THE GRASS HARP", "has_genre", "COMEDY" ], [ "THE GRASS HARP", "has_genre", "DRAMA" ], [ "THE WIZARD", "has_genre", "COMEDY" ], [ "THE WIZARD", "has_genre", "DRAMA" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "COMEDY" ], [ "THE WORLD ACCORDING TO GARP", "has_genre", "DRAMA" ], [ "TO DIE FOR", "has_genre", "COMEDY" ], [ "TO DIE FOR", "has_genre", "DRAMA" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "COMEDY" ], [ "TOO BEAUTIFUL FOR YOU", "has_genre", "DRAMA" ], [ "TWISTER", "has_genre", "COMEDY" ], [ "TWISTER", "has_genre", "DRAMA" ], [ "UNSTRUNG HEROES", "has_genre", "COMEDY" ], [ "UNSTRUNG HEROES", "has_genre", "DRAMA" ], [ "YOUNG DOCTORS IN LOVE", "has_genre", "COMEDY" ], [ "YOUNG DOCTORS IN LOVE", "release_year", "1982" ], [ "YOUNG DOCTORS IN LOVE", "starred_actors", "SEAN YOUNG" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 35798, 2010 17939, BURT REYNOLDS 32334, CANNONBALL RUN II 32696, CITY HEAT 28094, DELIVERANCE 26473, FRANCE NUYEN 1646, RAPE 20882, REMEMBER ME 25348, SATAN NEVER SLEEPS src, edge_attr, dst 35798, release_year, 24525 32334, release_year, 24525 32334, starred_actors, 17939 32696, release_year, 24525 32696, starred_actors, 17939 28094, has_tags, 17939 28094, has_tags, 1646 28094, starred_actors, 17939 20882, release_year, 35798 25348, has_tags, 1646 25348, starred_actors, 26473 Question: How are BURT REYNOLDS, FRANCE NUYEN, and REMEMBER ME related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BURT REYNOLDS", "FRANCE NUYEN", "REMEMBER ME" ], "valid_edges": [ [ "2010", "release_year", "1984" ], [ "CANNONBALL RUN II", "release_year", "1984" ], [ "CANNONBALL RUN II", "starred_actors", "BURT REYNOLDS" ], [ "CITY HEAT", "release_year", "1984" ], [ "CITY HEAT", "starred_actors", "BURT REYNOLDS" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "has_tags", "RAPE" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "REMEMBER ME", "release_year", "2010" ], [ "SATAN NEVER SLEEPS", "has_tags", "RAPE" ], [ "SATAN NEVER SLEEPS", "starred_actors", "FRANCE NUYEN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 24447, A PURE FORMALITY 34157, BLINK 20616, CALLAN 13659, DISCLOSURE 6730, ERIC PORTER 30921, MUTE WITNESS 12972, NIGHT WATCH 20417, NIGHTWATCH 25419, PENN BADGLEY 34601, RUSSIA 6524, THE GETAWAY 35993, THE STEPFATHER 24811, THRILLER 8334, TRANSSIBERIAN 18233, TRIAL BY JURY src, edge_attr, dst 24447, has_genre, 24811 24447, release_year, 26257 34157, has_tags, 24811 34157, release_year, 26257 20616, has_genre, 24811 20616, starred_actors, 6730 13659, has_genre, 24811 13659, release_year, 26257 30921, has_genre, 24811 30921, has_tags, 34601 30921, release_year, 26257 12972, has_genre, 24811 12972, has_tags, 34601 20417, has_genre, 24811 20417, release_year, 26257 6524, has_genre, 24811 6524, release_year, 26257 35993, has_genre, 24811 35993, starred_actors, 25419 8334, has_tags, 34601 8334, has_tags, 24811 18233, has_genre, 24811 18233, release_year, 26257 Question: In what context are ERIC PORTER, MUTE WITNESS, and PENN BADGLEY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ERIC PORTER", "MUTE WITNESS", "PENN BADGLEY" ], "valid_edges": [ [ "A PURE FORMALITY", "has_genre", "THRILLER" ], [ "A PURE FORMALITY", "release_year", "1994" ], [ "BLINK", "has_tags", "THRILLER" ], [ "BLINK", "release_year", "1994" ], [ "CALLAN", "has_genre", "THRILLER" ], [ "CALLAN", "starred_actors", "ERIC PORTER" ], [ "DISCLOSURE", "has_genre", "THRILLER" ], [ "DISCLOSURE", "release_year", "1994" ], [ "MUTE WITNESS", "has_genre", "THRILLER" ], [ "MUTE WITNESS", "has_tags", "RUSSIA" ], [ "MUTE WITNESS", "release_year", "1994" ], [ "NIGHT WATCH", "has_genre", "THRILLER" ], [ "NIGHT WATCH", "has_tags", "RUSSIA" ], [ "NIGHTWATCH", "has_genre", "THRILLER" ], [ "NIGHTWATCH", "release_year", "1994" ], [ "THE GETAWAY", "has_genre", "THRILLER" ], [ "THE GETAWAY", "release_year", "1994" ], [ "THE STEPFATHER", "has_genre", "THRILLER" ], [ "THE STEPFATHER", "starred_actors", "PENN BADGLEY" ], [ "TRANSSIBERIAN", "has_tags", "RUSSIA" ], [ "TRANSSIBERIAN", "has_tags", "THRILLER" ], [ "TRIAL BY JURY", "has_genre", "THRILLER" ], [ "TRIAL BY JURY", "release_year", "1994" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 39289, ACTION 17256, DONNIE YEN 36212, DRAMA 13091, FLASH POINT 10121, IP MAN 38168, IP MAN 2 11564, JOEL BISSONNETTE 26301, MARTIAL ARTS 26904, PASSENGER SIDE 1398, SCOT ARMSTRONG 19595, THE HEARTBREAK KID 15676, WILSON YIP 5052, WING CHUN src, edge_attr, dst 13091, directed_by, 15676 13091, has_genre, 39289 13091, release_year, 17315 13091, starred_actors, 17256 10121, directed_by, 15676 10121, has_genre, 39289 10121, has_tags, 39289 10121, has_tags, 17256 10121, has_tags, 10121 10121, has_tags, 26301 10121, has_tags, 15676 10121, has_tags, 5052 10121, starred_actors, 17256 38168, directed_by, 15676 38168, has_genre, 36212 38168, has_tags, 17256 38168, has_tags, 10121 38168, has_tags, 26301 38168, has_tags, 15676 38168, has_tags, 5052 38168, starred_actors, 17256 26904, has_genre, 36212 26904, starred_actors, 11564 19595, release_year, 17315 19595, written_by, 1398 Question: How are JOEL BISSONNETTE, SCOT ARMSTRONG, and WILSON YIP related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOEL BISSONNETTE", "SCOT ARMSTRONG", "WILSON YIP" ], "valid_edges": [ [ "FLASH POINT", "directed_by", "WILSON YIP" ], [ "FLASH POINT", "has_genre", "ACTION" ], [ "FLASH POINT", "release_year", "2007" ], [ "FLASH POINT", "starred_actors", "DONNIE YEN" ], [ "IP MAN", "directed_by", "WILSON YIP" ], [ "IP MAN", "has_genre", "ACTION" ], [ "IP MAN", "has_tags", "ACTION" ], [ "IP MAN", "has_tags", "DONNIE YEN" ], [ "IP MAN", "has_tags", "IP MAN" ], [ "IP MAN", "has_tags", "MARTIAL ARTS" ], [ "IP MAN", "has_tags", "WILSON YIP" ], [ "IP MAN", "has_tags", "WING CHUN" ], [ "IP MAN", "starred_actors", "DONNIE YEN" ], [ "IP MAN 2", "directed_by", "WILSON YIP" ], [ "IP MAN 2", "has_genre", "DRAMA" ], [ "IP MAN 2", "has_tags", "DONNIE YEN" ], [ "IP MAN 2", "has_tags", "IP MAN" ], [ "IP MAN 2", "has_tags", "MARTIAL ARTS" ], [ "IP MAN 2", "has_tags", "WILSON YIP" ], [ "IP MAN 2", "has_tags", "WING CHUN" ], [ "IP MAN 2", "starred_actors", "DONNIE YEN" ], [ "PASSENGER SIDE", "has_genre", "DRAMA" ], [ "PASSENGER SIDE", "starred_actors", "JOEL BISSONNETTE" ], [ "THE HEARTBREAK KID", "release_year", "2007" ], [ "THE HEARTBREAK KID", "written_by", "SCOT ARMSTRONG" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18239, A RAISIN IN THE SUN 36212, DRAMA 7333, KAREN JOY FOWLER 36092, TEN NORTH FREDERICK 12191, THE JANE AUSTEN BOOK CLUB src, edge_attr, dst 18239, has_genre, 36212 36092, has_genre, 36212 12191, has_genre, 36212 12191, written_by, 7333 Question: In what context are A RAISIN IN THE SUN, KAREN JOY FOWLER, and TEN NORTH FREDERICK connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A RAISIN IN THE SUN", "KAREN JOY FOWLER", "TEN NORTH FREDERICK" ], "valid_edges": [ [ "A RAISIN IN THE SUN", "has_genre", "DRAMA" ], [ "TEN NORTH FREDERICK", "has_genre", "DRAMA" ], [ "THE JANE AUSTEN BOOK CLUB", "has_genre", "DRAMA" ], [ "THE JANE AUSTEN BOOK CLUB", "written_by", "KAREN JOY FOWLER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 1421, 2013 13546, ACTING 33132, ARNOLD SCHWARZENEGGER 22349, CRAWLSPACE 8491, ESCAPE PLAN 35533, GENERATION IRON 1897, OBLIVION 8342, OSCAR REDDING 23588, PROMETHEUS 24173, THE EXPENDABLES 2 14665, THE LAST STAND 32701, THE SEASONING HOUSE 13259, TOTAL RECALL 16793, VAN DIEMEN'S LAND src, edge_attr, dst 658, release_year, 27261 22349, release_year, 658 22349, release_year, 1421 8491, has_tags, 33132 8491, release_year, 1421 8491, starred_actors, 33132 35533, release_year, 1421 35533, starred_actors, 33132 1897, has_tags, 13546 1897, release_year, 1421 23588, has_tags, 13546 23588, release_year, 658 24173, has_tags, 33132 24173, release_year, 658 14665, has_tags, 13546 14665, has_tags, 33132 14665, release_year, 1421 14665, starred_actors, 33132 32701, release_year, 658 13259, has_tags, 33132 13259, release_year, 658 13259, starred_actors, 33132 16793, release_year, 27261 16793, starred_actors, 8342 16793, written_by, 8342 Question: In what context are OSCAR REDDING, THE LAST STAND, and THE SEASONING HOUSE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "OSCAR REDDING", "THE LAST STAND", "THE SEASONING HOUSE" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "CRAWLSPACE", "release_year", "2012" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "ESCAPE PLAN", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "ESCAPE PLAN", "release_year", "2013" ], [ "ESCAPE PLAN", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "GENERATION IRON", "release_year", "2013" ], [ "GENERATION IRON", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "OBLIVION", "has_tags", "ACTING" ], [ "OBLIVION", "release_year", "2013" ], [ "PROMETHEUS", "has_tags", "ACTING" ], [ "PROMETHEUS", "release_year", "2012" ], [ "THE EXPENDABLES 2", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "THE EXPENDABLES 2", "release_year", "2012" ], [ "THE LAST STAND", "has_tags", "ACTING" ], [ "THE LAST STAND", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "THE LAST STAND", "release_year", "2013" ], [ "THE LAST STAND", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "THE SEASONING HOUSE", "release_year", "2012" ], [ "TOTAL RECALL", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "TOTAL RECALL", "release_year", "2012" ], [ "TOTAL RECALL", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "VAN DIEMEN'S LAND", "release_year", "2009" ], [ "VAN DIEMEN'S LAND", "starred_actors", "OSCAR REDDING" ], [ "VAN DIEMEN'S LAND", "written_by", "OSCAR REDDING" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8783, 1977 7841, 1987 27261, 2009 658, 2012 1421, 2013 22078, ARBITRAGE 33105, BRIDE OF BOOGEDY 30463, COMEDY 10816, DEAD MAN WALKING 36212, DRAMA 37496, ELIZABETHTOWN 880, IRRESISTIBLE 37830, JEFF, WHO LIVES AT HOME 35629, JOE 17903, LEAVES OF GRASS 16441, LIGHT SLEEPER 6706, MARK JACOBSON 31735, MIDDLE OF NOWHERE 37353, NOEL 3564, OZ SCOTT 12008, PRETTY BABY 17353, SAFE PASSAGE 36442, SNITCH 33439, STEPMOM 38238, SUSAN SARANDON 2819, TEMPEST 267, THE BELIEVER 8847, THE GREAT WALDO PEPPER 33198, THE GREATEST 21326, THE LAST OF ROBIN HOOD 26894, THE LOVELY BONES 14975, THE OTHER SIDE OF MIDNIGHT 14621, THE WITCHES OF EASTWICK 9364, WHITE PALACE src, edge_attr, dst 22078, has_genre, 36212 22078, has_tags, 38238 22078, release_year, 658 22078, starred_actors, 38238 33105, directed_by, 3564 33105, release_year, 7841 10816, has_genre, 36212 10816, has_tags, 36212 10816, has_tags, 38238 10816, starred_actors, 38238 37496, has_genre, 30463 37496, has_genre, 36212 37496, has_tags, 38238 37496, starred_actors, 38238 880, has_genre, 36212 880, starred_actors, 38238 37830, has_genre, 30463 37830, has_genre, 36212 37830, starred_actors, 38238 35629, has_genre, 36212 35629, release_year, 1421 35629, starred_actors, 38238 17903, has_genre, 30463 17903, has_genre, 36212 17903, has_tags, 38238 17903, release_year, 27261 16441, has_genre, 36212 16441, starred_actors, 38238 31735, has_genre, 30463 31735, has_genre, 36212 31735, release_year, 658 31735, starred_actors, 38238 37353, has_genre, 36212 37353, has_tags, 36212 37353, starred_actors, 38238 12008, has_genre, 36212 12008, starred_actors, 38238 17353, has_genre, 36212 17353, starred_actors, 38238 36442, has_genre, 36212 36442, release_year, 1421 36442, starred_actors, 38238 33439, has_genre, 30463 33439, has_genre, 36212 33439, has_tags, 38238 33439, starred_actors, 38238 2819, has_genre, 30463 2819, has_genre, 36212 2819, starred_actors, 38238 267, has_genre, 36212 267, written_by, 6706 8847, has_genre, 36212 8847, starred_actors, 38238 33198, has_genre, 36212 33198, has_tags, 38238 33198, release_year, 8783 33198, release_year, 27261 33198, starred_actors, 38238 21326, has_genre, 36212 21326, release_year, 1421 21326, starred_actors, 38238 26894, has_genre, 36212 26894, has_tags, 38238 26894, release_year, 27261 26894, starred_actors, 38238 14975, has_genre, 36212 14975, release_year, 8783 14975, starred_actors, 38238 14621, has_genre, 30463 14621, release_year, 7841 14621, starred_actors, 38238 9364, has_genre, 36212 9364, starred_actors, 38238 Question: How are MARK JACOBSON, OZ SCOTT, and SUSAN SARANDON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MARK JACOBSON", "OZ SCOTT", "SUSAN SARANDON" ], "valid_edges": [ [ "ARBITRAGE", "has_genre", "DRAMA" ], [ "ARBITRAGE", "has_tags", "SUSAN SARANDON" ], [ "ARBITRAGE", "release_year", "2012" ], [ "ARBITRAGE", "starred_actors", "SUSAN SARANDON" ], [ "BRIDE OF BOOGEDY", "directed_by", "OZ SCOTT" ], [ "BRIDE OF BOOGEDY", "release_year", "1987" ], [ "DEAD MAN WALKING", "has_genre", "DRAMA" ], [ "DEAD MAN WALKING", "has_tags", "DRAMA" ], [ "DEAD MAN WALKING", "has_tags", "SUSAN SARANDON" ], [ "DEAD MAN WALKING", "starred_actors", "SUSAN SARANDON" ], [ "ELIZABETHTOWN", "has_genre", "COMEDY" ], [ "ELIZABETHTOWN", "has_genre", "DRAMA" ], [ "ELIZABETHTOWN", "has_tags", "SUSAN SARANDON" ], [ "ELIZABETHTOWN", "starred_actors", "SUSAN SARANDON" ], [ "IRRESISTIBLE", "has_genre", "DRAMA" ], [ "IRRESISTIBLE", "starred_actors", "SUSAN SARANDON" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "COMEDY" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "DRAMA" ], [ "JEFF, WHO LIVES AT HOME", "starred_actors", "SUSAN SARANDON" ], [ "JOE", "has_genre", "DRAMA" ], [ "JOE", "release_year", "2013" ], [ "JOE", "starred_actors", "SUSAN SARANDON" ], [ "LEAVES OF GRASS", "has_genre", "COMEDY" ], [ "LEAVES OF GRASS", "has_genre", "DRAMA" ], [ "LEAVES OF GRASS", "has_tags", "SUSAN SARANDON" ], [ "LEAVES OF GRASS", "release_year", "2009" ], [ "LIGHT SLEEPER", "has_genre", "DRAMA" ], [ "LIGHT SLEEPER", "starred_actors", "SUSAN SARANDON" ], [ "MIDDLE OF NOWHERE", "has_genre", "COMEDY" ], [ "MIDDLE OF NOWHERE", "has_genre", "DRAMA" ], [ "MIDDLE OF NOWHERE", "release_year", "2012" ], [ "MIDDLE OF NOWHERE", "starred_actors", "SUSAN SARANDON" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "NOEL", "starred_actors", "SUSAN SARANDON" ], [ "PRETTY BABY", "has_genre", "DRAMA" ], [ "PRETTY BABY", "starred_actors", "SUSAN SARANDON" ], [ "SAFE PASSAGE", "has_genre", "DRAMA" ], [ "SAFE PASSAGE", "starred_actors", "SUSAN SARANDON" ], [ "SNITCH", "has_genre", "DRAMA" ], [ "SNITCH", "release_year", "2013" ], [ "SNITCH", "starred_actors", "SUSAN SARANDON" ], [ "STEPMOM", "has_genre", "COMEDY" ], [ "STEPMOM", "has_genre", "DRAMA" ], [ "STEPMOM", "has_tags", "SUSAN SARANDON" ], [ "STEPMOM", "starred_actors", "SUSAN SARANDON" ], [ "TEMPEST", "has_genre", "COMEDY" ], [ "TEMPEST", "has_genre", "DRAMA" ], [ "TEMPEST", "starred_actors", "SUSAN SARANDON" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "written_by", "MARK JACOBSON" ], [ "THE GREAT WALDO PEPPER", "has_genre", "DRAMA" ], [ "THE GREAT WALDO PEPPER", "starred_actors", "SUSAN SARANDON" ], [ "THE GREATEST", "has_genre", "DRAMA" ], [ "THE GREATEST", "has_tags", "SUSAN SARANDON" ], [ "THE GREATEST", "release_year", "1977" ], [ "THE GREATEST", "release_year", "2009" ], [ "THE GREATEST", "starred_actors", "SUSAN SARANDON" ], [ "THE LAST OF ROBIN HOOD", "has_genre", "DRAMA" ], [ "THE LAST OF ROBIN HOOD", "release_year", "2013" ], [ "THE LAST OF ROBIN HOOD", "starred_actors", "SUSAN SARANDON" ], [ "THE LOVELY BONES", "has_genre", "DRAMA" ], [ "THE LOVELY BONES", "has_tags", "SUSAN SARANDON" ], [ "THE LOVELY BONES", "release_year", "2009" ], [ "THE LOVELY BONES", "starred_actors", "SUSAN SARANDON" ], [ "THE OTHER SIDE OF MIDNIGHT", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF MIDNIGHT", "release_year", "1977" ], [ "THE OTHER SIDE OF MIDNIGHT", "starred_actors", "SUSAN SARANDON" ], [ "THE WITCHES OF EASTWICK", "has_genre", "COMEDY" ], [ "THE WITCHES OF EASTWICK", "release_year", "1987" ], [ "THE WITCHES OF EASTWICK", "starred_actors", "SUSAN SARANDON" ], [ "WHITE PALACE", "has_genre", "DRAMA" ], [ "WHITE PALACE", "starred_actors", "SUSAN SARANDON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 18243, A SCANNER DARKLY 24177, ANIMATION 2795, PENGUINS OF MADAGASCAR 36862, PHILIP K. DICK 34922, PK 34199, SANJAY DUTT 23344, SIMON J. SMITH src, edge_attr, dst 18243, has_genre, 24177 18243, has_tags, 24177 18243, has_tags, 36862 18243, written_by, 36862 2795, directed_by, 23344 2795, has_genre, 24177 2795, has_tags, 24177 2795, release_year, 9377 34922, release_year, 9377 34922, starred_actors, 34199 Question: For what reason are PHILIP K. DICK, SANJAY DUTT, and SIMON J. SMITH associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "PHILIP K. DICK", "SANJAY DUTT", "SIMON J. SMITH" ], "valid_edges": [ [ "A SCANNER DARKLY", "has_genre", "ANIMATION" ], [ "A SCANNER DARKLY", "has_tags", "ANIMATION" ], [ "A SCANNER DARKLY", "has_tags", "PHILIP K. DICK" ], [ "A SCANNER DARKLY", "written_by", "PHILIP K. DICK" ], [ "PENGUINS OF MADAGASCAR", "directed_by", "SIMON J. SMITH" ], [ "PENGUINS OF MADAGASCAR", "has_genre", "ANIMATION" ], [ "PENGUINS OF MADAGASCAR", "has_tags", "ANIMATION" ], [ "PENGUINS OF MADAGASCAR", "release_year", "2014" ], [ "PK", "release_year", "2014" ], [ "PK", "starred_actors", "SANJAY DUTT" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7841, 1987 10702, 1991 4713, A RETURN TO SALEM'S LOT 25905, ANGEL HEART 6748, ANGUISH 12844, BAD KARMA 34587, BAD TASTE 36593, BLACK CHRISTMAS 16020, BODY PARTS 32401, CAST A DEADLY SPELL 37126, CASTLE FREAK 32780, CHILDREN OF THE NIGHT 19984, CREEPSHOW 2 4824, DAGON 23612, DOLLS 6158, EDGAR ALLAN POE 16661, EVIL DEAD II 3270, FROM BEYOND 12498, HELLRAISER 5870, HORROR 10955, HOUSE OF USHER 3995, KEIR DULLEA 36631, MUNCHIES 18744, MURDERS IN THE RUE MORGUE 14237, NEAR DARK 15661, NEKROMANTIK 38235, NEKROMANTIK 2 38962, OPERA 24431, PHANTOM OF THE RUE MORGUE 284, POISON 8138, POPCORN 4323, PRINCE OF DARKNESS 39358, RE-ANIMATOR 9184, RETURN TO HORROR HIGH 18856, ROCK 'N' ROLL NIGHTMARE 11041, SILENT NIGHT, DEADLY NIGHT PART 2 8436, SPIRITS OF THE DEAD 18809, STUART GORDON 20148, SUBSPECIES 26202, TALES OF TERROR 28739, THE BELIEVERS 27437, THE BLACK CAT 11327, THE BORROWER 10194, THE BRAVE LITTLE TOASTER 8063, THE CURSE 16105, THE DEAD 23699, THE DENTIST 17646, THE FALL OF THE HOUSE OF USHER 38230, THE GATE 25175, THE HAUNTED PALACE 3318, THE LOST BOYS 11243, THE MASQUE OF THE RED DEATH 33993, THE MONSTER SQUAD 36578, THE PEOPLE UNDER THE STAIRS 37211, THE PIT AND THE PENDULUM 18162, THE RAVEN 27836, THE SILENCE OF THE LAMBS 35993, THE STEPFATHER 21559, THE TOMB OF LIGEIA 37650, TWO EVIL EYES 8589, WICKED CITY 6037, WITCHFINDER GENERAL src, edge_attr, dst 4713, has_genre, 5870 4713, release_year, 7841 25905, has_genre, 5870 25905, release_year, 7841 6748, has_genre, 5870 6748, release_year, 7841 12844, has_genre, 5870 12844, release_year, 10702 34587, has_genre, 5870 34587, release_year, 7841 36593, has_genre, 5870 36593, has_tags, 5870 36593, starred_actors, 3995 16020, has_genre, 5870 16020, release_year, 10702 32401, has_genre, 5870 32401, release_year, 10702 37126, directed_by, 18809 37126, has_genre, 5870 37126, written_by, 18809 32780, has_genre, 5870 32780, release_year, 10702 19984, has_genre, 5870 19984, release_year, 7841 4824, directed_by, 18809 4824, has_genre, 5870 23612, directed_by, 18809 23612, has_genre, 5870 23612, release_year, 7841 16661, has_genre, 5870 16661, has_tags, 5870 16661, release_year, 7841 3270, directed_by, 18809 3270, has_genre, 5870 3270, written_by, 18809 12498, has_genre, 5870 12498, has_tags, 5870 12498, release_year, 7841 10955, has_genre, 5870 10955, has_tags, 6158 10955, has_tags, 5870 10955, written_by, 6158 36631, has_genre, 5870 36631, release_year, 7841 18744, has_genre, 5870 18744, has_tags, 6158 18744, written_by, 6158 14237, has_genre, 5870 14237, release_year, 7841 15661, has_genre, 5870 15661, release_year, 7841 38235, has_genre, 5870 38235, release_year, 10702 38962, has_genre, 5870 38962, release_year, 7841 24431, has_genre, 5870 24431, written_by, 6158 284, has_genre, 5870 284, release_year, 10702 8138, has_genre, 5870 8138, release_year, 10702 4323, has_genre, 5870 4323, release_year, 7841 39358, directed_by, 18809 39358, has_genre, 5870 39358, has_tags, 5870 39358, written_by, 18809 9184, has_genre, 5870 9184, release_year, 7841 18856, has_genre, 5870 18856, release_year, 7841 11041, has_genre, 5870 11041, release_year, 7841 8436, has_genre, 5870 8436, has_tags, 6158 8436, written_by, 6158 20148, has_genre, 5870 20148, release_year, 10702 26202, has_genre, 5870 26202, has_tags, 6158 26202, written_by, 6158 28739, has_genre, 5870 28739, release_year, 7841 27437, has_genre, 5870 27437, has_tags, 6158 27437, written_by, 6158 11327, has_genre, 5870 11327, release_year, 10702 10194, release_year, 7841 8063, has_genre, 5870 8063, release_year, 7841 16105, has_genre, 5870 16105, release_year, 7841 23699, has_genre, 5870 23699, written_by, 18809 17646, has_genre, 5870 17646, has_tags, 6158 17646, written_by, 6158 38230, has_genre, 5870 38230, release_year, 7841 25175, has_genre, 5870 25175, has_tags, 6158 25175, written_by, 6158 3318, has_genre, 5870 3318, has_tags, 5870 3318, release_year, 7841 11243, has_genre, 5870 11243, has_tags, 6158 11243, written_by, 6158 33993, has_tags, 5870 33993, release_year, 7841 36578, has_genre, 5870 36578, release_year, 10702 37211, directed_by, 18809 37211, has_genre, 5870 37211, has_tags, 6158 37211, release_year, 10702 37211, written_by, 6158 18162, has_genre, 5870 18162, has_tags, 6158 18162, has_tags, 5870 18162, written_by, 6158 27836, has_tags, 5870 27836, release_year, 10702 35993, has_genre, 5870 35993, release_year, 7841 21559, has_genre, 5870 21559, has_tags, 6158 21559, has_tags, 5870 21559, written_by, 6158 37650, has_genre, 5870 37650, has_tags, 6158 37650, written_by, 6158 8589, has_genre, 5870 8589, release_year, 7841 6037, has_genre, 5870 6037, has_tags, 6158 Question: How are KEIR DULLEA, THE BRAVE LITTLE TOASTER, and THE PIT AND THE PENDULUM related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KEIR DULLEA", "THE BRAVE LITTLE TOASTER", "THE PIT AND THE PENDULUM" ], "valid_edges": [ [ "A RETURN TO SALEM'S LOT", "has_genre", "HORROR" ], [ "A RETURN TO SALEM'S LOT", "release_year", "1987" ], [ "ANGEL HEART", "has_genre", "HORROR" ], [ "ANGEL HEART", "release_year", "1987" ], [ "ANGUISH", "has_genre", "HORROR" ], [ "ANGUISH", "release_year", "1987" ], [ "BAD KARMA", "has_genre", "HORROR" ], [ "BAD KARMA", "release_year", "1991" ], [ "BAD TASTE", "has_genre", "HORROR" ], [ "BAD TASTE", "release_year", "1987" ], [ "BLACK CHRISTMAS", "has_genre", "HORROR" ], [ "BLACK CHRISTMAS", "has_tags", "HORROR" ], [ "BLACK CHRISTMAS", "starred_actors", "KEIR DULLEA" ], [ "BODY PARTS", "has_genre", "HORROR" ], [ "BODY PARTS", "release_year", "1991" ], [ "CAST A DEADLY SPELL", "has_genre", "HORROR" ], [ "CAST A DEADLY SPELL", "release_year", "1991" ], [ "CASTLE FREAK", "directed_by", "STUART GORDON" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "written_by", "STUART GORDON" ], [ "CHILDREN OF THE NIGHT", "has_genre", "HORROR" ], [ "CHILDREN OF THE NIGHT", "release_year", "1991" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "release_year", "1987" ], [ "DAGON", "directed_by", "STUART GORDON" ], [ "DAGON", "has_genre", "HORROR" ], [ "DOLLS", "directed_by", "STUART GORDON" ], [ "DOLLS", "has_genre", "HORROR" ], [ "DOLLS", "release_year", "1987" ], [ "EVIL DEAD II", "has_genre", "HORROR" ], [ "EVIL DEAD II", "has_tags", "HORROR" ], [ "EVIL DEAD II", "release_year", "1987" ], [ "FROM BEYOND", "directed_by", "STUART GORDON" ], [ "FROM BEYOND", "has_genre", "HORROR" ], [ "FROM BEYOND", "written_by", "STUART GORDON" ], [ "HELLRAISER", "has_genre", "HORROR" ], [ "HELLRAISER", "has_tags", "HORROR" ], [ "HELLRAISER", "release_year", "1987" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "EDGAR ALLAN POE" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF USHER", "written_by", "EDGAR ALLAN POE" ], [ "MUNCHIES", "has_genre", "HORROR" ], [ "MUNCHIES", "release_year", "1987" ], [ "MURDERS IN THE RUE MORGUE", "has_genre", "HORROR" ], [ "MURDERS IN THE RUE MORGUE", "has_tags", "EDGAR ALLAN POE" ], [ "MURDERS IN THE RUE MORGUE", "written_by", "EDGAR ALLAN POE" ], [ "NEAR DARK", "has_genre", "HORROR" ], [ "NEAR DARK", "release_year", "1987" ], [ "NEKROMANTIK", "has_genre", "HORROR" ], [ "NEKROMANTIK", "release_year", "1987" ], [ "NEKROMANTIK 2", "has_genre", "HORROR" ], [ "NEKROMANTIK 2", "release_year", "1991" ], [ "OPERA", "has_genre", "HORROR" ], [ "OPERA", "release_year", "1987" ], [ "PHANTOM OF THE RUE MORGUE", "has_genre", "HORROR" ], [ "PHANTOM OF THE RUE MORGUE", "written_by", "EDGAR ALLAN POE" ], [ "POISON", "has_genre", "HORROR" ], [ "POISON", "release_year", "1991" ], [ "POPCORN", "has_genre", "HORROR" ], [ "POPCORN", "release_year", "1991" ], [ "PRINCE OF DARKNESS", "has_genre", "HORROR" ], [ "PRINCE OF DARKNESS", "release_year", "1987" ], [ "RE-ANIMATOR", "directed_by", "STUART GORDON" ], [ "RE-ANIMATOR", "has_genre", "HORROR" ], [ "RE-ANIMATOR", "has_tags", "HORROR" ], [ "RE-ANIMATOR", "written_by", "STUART GORDON" ], [ "RETURN TO HORROR HIGH", "has_genre", "HORROR" ], [ "RETURN TO HORROR HIGH", "release_year", "1987" ], [ "ROCK 'N' ROLL NIGHTMARE", "has_genre", "HORROR" ], [ "ROCK 'N' ROLL NIGHTMARE", "release_year", "1987" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "has_genre", "HORROR" ], [ "SILENT NIGHT, DEADLY NIGHT PART 2", "release_year", "1987" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "EDGAR ALLAN POE" ], [ "SPIRITS OF THE DEAD", "written_by", "EDGAR ALLAN POE" ], [ "SUBSPECIES", "has_genre", "HORROR" ], [ "SUBSPECIES", "release_year", "1991" ], [ "TALES OF TERROR", "has_genre", "HORROR" ], [ "TALES OF TERROR", "has_tags", "EDGAR ALLAN POE" ], [ "TALES OF TERROR", "written_by", "EDGAR ALLAN POE" ], [ "THE BELIEVERS", "has_genre", "HORROR" ], [ "THE BELIEVERS", "release_year", "1987" ], [ "THE BLACK CAT", "has_genre", "HORROR" ], [ "THE BLACK CAT", "has_tags", "EDGAR ALLAN POE" ], [ "THE BLACK CAT", "written_by", "EDGAR ALLAN POE" ], [ "THE BORROWER", "has_genre", "HORROR" ], [ "THE BORROWER", "release_year", "1991" ], [ "THE BRAVE LITTLE TOASTER", "release_year", "1987" ], [ "THE CURSE", "has_genre", "HORROR" ], [ "THE CURSE", "release_year", "1987" ], [ "THE DEAD", "has_genre", "HORROR" ], [ "THE DEAD", "release_year", "1987" ], [ "THE DENTIST", "has_genre", "HORROR" ], [ "THE DENTIST", "written_by", "STUART GORDON" ], [ "THE FALL OF THE HOUSE OF USHER", "has_genre", "HORROR" ], [ "THE FALL OF THE HOUSE OF USHER", "has_tags", "EDGAR ALLAN POE" ], [ "THE FALL OF THE HOUSE OF USHER", "written_by", "EDGAR ALLAN POE" ], [ "THE GATE", "has_genre", "HORROR" ], [ "THE GATE", "release_year", "1987" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "EDGAR ALLAN POE" ], [ "THE HAUNTED PALACE", "written_by", "EDGAR ALLAN POE" ], [ "THE LOST BOYS", "has_genre", "HORROR" ], [ "THE LOST BOYS", "has_tags", "HORROR" ], [ "THE LOST BOYS", "release_year", "1987" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "EDGAR ALLAN POE" ], [ "THE MASQUE OF THE RED DEATH", "written_by", "EDGAR ALLAN POE" ], [ "THE MONSTER SQUAD", "has_tags", "HORROR" ], [ "THE MONSTER SQUAD", "release_year", "1987" ], [ "THE PEOPLE UNDER THE STAIRS", "has_genre", "HORROR" ], [ "THE PEOPLE UNDER THE STAIRS", "release_year", "1991" ], [ "THE PIT AND THE PENDULUM", "directed_by", "STUART GORDON" ], [ "THE PIT AND THE PENDULUM", "has_genre", "HORROR" ], [ "THE PIT AND THE PENDULUM", "has_tags", "EDGAR ALLAN POE" ], [ "THE PIT AND THE PENDULUM", "release_year", "1991" ], [ "THE PIT AND THE PENDULUM", "written_by", "EDGAR ALLAN POE" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "EDGAR ALLAN POE" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE RAVEN", "written_by", "EDGAR ALLAN POE" ], [ "THE SILENCE OF THE LAMBS", "has_tags", "HORROR" ], [ "THE SILENCE OF THE LAMBS", "release_year", "1991" ], [ "THE STEPFATHER", "has_genre", "HORROR" ], [ "THE STEPFATHER", "release_year", "1987" ], [ "THE TOMB OF LIGEIA", "has_genre", "HORROR" ], [ "THE TOMB OF LIGEIA", "has_tags", "EDGAR ALLAN POE" ], [ "THE TOMB OF LIGEIA", "has_tags", "HORROR" ], [ "THE TOMB OF LIGEIA", "written_by", "EDGAR ALLAN POE" ], [ "TWO EVIL EYES", "has_genre", "HORROR" ], [ "TWO EVIL EYES", "has_tags", "EDGAR ALLAN POE" ], [ "TWO EVIL EYES", "written_by", "EDGAR ALLAN POE" ], [ "WICKED CITY", "has_genre", "HORROR" ], [ "WICKED CITY", "release_year", "1987" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "EDGAR ALLAN POE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18656, 1944 2133, 1998 26163, 20,000 YEARS IN SING SING 37484, 2004 6139, A STOLEN LIFE 22709, ALL ABOUT EVE 4617, ALL THIS, AND HEAVEN TOO 26158, ANOTHER MAN'S POISON 37608, AUSTRALIA 9367, BETTE DAVIS 11929, CASABLANCA 21072, CLAUDE RAINS 1968, COBRA WOMAN 19193, DANGEROUS 37778, DARK VICTORY 20161, DECEPTION 18074, DRAGON SEED 36212, DRAMA 26366, EDWARD NORTON 18210, FOUR DAUGHTERS 39145, FURY 8612, GEORGE COULOURIS 25033, GOING MY WAY 35248, HARRIET CRAIG 3259, I'LL BE SEEING YOU 34341, IN THIS OUR LIFE 26372, JERRY SPRINGER 29848, JEZEBEL 19209, JOHN CURRAN 18688, MARKED WOMAN 10202, MOONTIDE 37704, MR. SKEFFINGTON 26086, MR. SMITH GOES TO WASHINGTON 36406, MRS. PARKINGTON 18389, NOW, VOYAGER 4435, OF HUMAN BONDAGE 18256, OLD ACQUAINTANCE 9090, PRAISE 24415, RINGMASTER 4504, STONE 10358, STORM CENTER 15199, THE CABIN IN THE COTTON 31280, THE CATERED AFFAIR 14219, THE CHILDREN ARE WATCHING US 39333, THE CLAIRVOYANT 32516, THE CORN IS GREEN 30857, THE DEFENDER 4610, THE GREAT LIE 32102, THE HARD WAY 33948, THE LETTER 15492, THE MASK OF DIMITRIOS 23084, THE PAINTED VEIL 12160, THE PRIVATE LIVES OF ELIZABETH AND ESSEX 279, THE VERDICT 39634, THE VIRGIN QUEEN 36275, THE WAY AHEAD 6138, THE WOLF MAN 16460, THE YOUNG PHILADELPHIANS 873, THEY MADE ME A CRIMINAL 14471, THIS HAPPY BREED 18596, THREE ON A MATCH 35615, TRACKS 31737, VINCENT SHERMAN 40060, WALTER ABEL 30597, WATCH ON THE RHINE 37859, WE DON'T LIVE HERE ANYMORE 29044, WHERE LOVE HAS GONE 26049, WHITE BANNERS 11934, WILSON src, edge_attr, dst 26163, has_genre, 36212 26163, starred_actors, 9367 6139, has_genre, 36212 6139, starred_actors, 9367 22709, has_genre, 36212 22709, has_tags, 9367 22709, starred_actors, 9367 4617, has_genre, 36212 4617, starred_actors, 9367 26158, has_genre, 36212 26158, starred_actors, 9367 37608, has_genre, 36212 11929, has_genre, 36212 11929, has_tags, 21072 11929, has_tags, 36212 11929, starred_actors, 21072 1968, has_genre, 36212 1968, release_year, 18656 19193, has_genre, 36212 19193, starred_actors, 9367 37778, has_genre, 36212 37778, has_tags, 9367 37778, starred_actors, 9367 20161, has_genre, 36212 20161, starred_actors, 9367 20161, starred_actors, 21072 18074, has_genre, 36212 18074, release_year, 18656 18210, has_genre, 36212 18210, starred_actors, 21072 39145, has_genre, 36212 39145, starred_actors, 40060 25033, has_genre, 36212 25033, release_year, 18656 35248, directed_by, 31737 35248, has_genre, 36212 35248, has_tags, 31737 3259, has_genre, 36212 3259, release_year, 18656 34341, has_genre, 36212 34341, starred_actors, 9367 29848, has_genre, 36212 29848, has_tags, 9367 29848, starred_actors, 9367 18688, has_genre, 36212 18688, has_tags, 9367 18688, starred_actors, 9367 10202, has_genre, 36212 10202, starred_actors, 21072 37704, directed_by, 31737 37704, has_genre, 36212 37704, has_tags, 31737 37704, release_year, 18656 37704, starred_actors, 9367 37704, starred_actors, 21072 37704, starred_actors, 8612 37704, starred_actors, 40060 26086, has_genre, 36212 26086, has_tags, 21072 26086, has_tags, 36212 26086, starred_actors, 21072 36406, has_genre, 36212 36406, release_year, 18656 18389, has_genre, 36212 18389, has_tags, 9367 18389, has_tags, 21072 18389, starred_actors, 9367 18389, starred_actors, 21072 4435, has_genre, 36212 4435, has_tags, 9367 4435, starred_actors, 9367 18256, directed_by, 31737 18256, has_genre, 36212 18256, has_tags, 9367 18256, has_tags, 31737 18256, starred_actors, 9367 9090, directed_by, 19209 9090, has_tags, 19209 9090, release_year, 2133 24415, release_year, 2133 24415, starred_actors, 26372 4504, directed_by, 19209 4504, starred_actors, 26366 10358, has_genre, 36212 10358, starred_actors, 9367 15199, has_genre, 36212 15199, starred_actors, 9367 31280, has_genre, 36212 31280, starred_actors, 9367 14219, has_genre, 36212 14219, release_year, 18656 39333, has_genre, 36212 39333, starred_actors, 21072 32516, has_genre, 36212 32516, starred_actors, 9367 30857, release_year, 37484 30857, starred_actors, 26372 4610, has_genre, 36212 4610, starred_actors, 9367 32102, directed_by, 31737 32102, has_genre, 36212 32102, has_tags, 31737 33948, has_genre, 36212 33948, has_tags, 9367 33948, starred_actors, 9367 15492, has_genre, 36212 15492, release_year, 18656 23084, directed_by, 19209 23084, has_genre, 36212 23084, has_tags, 26366 23084, has_tags, 19209 12160, has_genre, 36212 12160, has_tags, 9367 12160, starred_actors, 9367 279, has_genre, 36212 279, starred_actors, 8612 39634, has_genre, 36212 39634, starred_actors, 9367 36275, has_genre, 36212 36275, release_year, 18656 6138, has_genre, 36212 6138, starred_actors, 21072 16460, directed_by, 31737 16460, has_genre, 36212 16460, has_tags, 31737 873, has_genre, 36212 873, starred_actors, 21072 14471, has_genre, 36212 14471, release_year, 18656 18596, has_genre, 36212 18596, has_tags, 9367 35615, directed_by, 19209 35615, has_genre, 36212 35615, has_tags, 37608 35615, has_tags, 19209 30597, has_genre, 36212 30597, starred_actors, 9367 37859, directed_by, 19209 37859, has_genre, 36212 37859, release_year, 37484 29044, has_genre, 36212 29044, starred_actors, 9367 26049, has_genre, 36212 26049, starred_actors, 21072 11934, has_genre, 36212 11934, release_year, 18656 Question: In what context are JERRY SPRINGER, JOHN CURRAN, and MR. SKEFFINGTON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JERRY SPRINGER", "JOHN CURRAN", "MR. SKEFFINGTON" ], "valid_edges": [ [ "20,000 YEARS IN SING SING", "has_genre", "DRAMA" ], [ "20,000 YEARS IN SING SING", "starred_actors", "BETTE DAVIS" ], [ "A STOLEN LIFE", "has_genre", "DRAMA" ], [ "A STOLEN LIFE", "starred_actors", "BETTE DAVIS" ], [ "ALL ABOUT EVE", "has_genre", "DRAMA" ], [ "ALL ABOUT EVE", "has_tags", "BETTE DAVIS" ], [ "ALL ABOUT EVE", "starred_actors", "BETTE DAVIS" ], [ "ALL THIS, AND HEAVEN TOO", "has_genre", "DRAMA" ], [ "ALL THIS, AND HEAVEN TOO", "starred_actors", "BETTE DAVIS" ], [ "ANOTHER MAN'S POISON", "has_genre", "DRAMA" ], [ "ANOTHER MAN'S POISON", "starred_actors", "BETTE DAVIS" ], [ "AUSTRALIA", "has_genre", "DRAMA" ], [ "CASABLANCA", "has_genre", "DRAMA" ], [ "CASABLANCA", "has_tags", "CLAUDE RAINS" ], [ "CASABLANCA", "has_tags", "DRAMA" ], [ "CASABLANCA", "starred_actors", "CLAUDE RAINS" ], [ "COBRA WOMAN", "has_genre", "DRAMA" ], [ "COBRA WOMAN", "release_year", "1944" ], [ "DANGEROUS", "has_genre", "DRAMA" ], [ "DANGEROUS", "starred_actors", "BETTE DAVIS" ], [ "DARK VICTORY", "has_genre", "DRAMA" ], [ "DARK VICTORY", "has_tags", "BETTE DAVIS" ], [ "DARK VICTORY", "starred_actors", "BETTE DAVIS" ], [ "DECEPTION", "has_genre", "DRAMA" ], [ "DECEPTION", "starred_actors", "BETTE DAVIS" ], [ "DECEPTION", "starred_actors", "CLAUDE RAINS" ], [ "DRAGON SEED", "has_genre", "DRAMA" ], [ "DRAGON SEED", "release_year", "1944" ], [ "FOUR DAUGHTERS", "has_genre", "DRAMA" ], [ "FOUR DAUGHTERS", "starred_actors", "CLAUDE RAINS" ], [ "FURY", "has_genre", "DRAMA" ], [ "FURY", "starred_actors", "WALTER ABEL" ], [ "GOING MY WAY", "has_genre", "DRAMA" ], [ "GOING MY WAY", "release_year", "1944" ], [ "HARRIET CRAIG", "directed_by", "VINCENT SHERMAN" ], [ "HARRIET CRAIG", "has_genre", "DRAMA" ], [ "HARRIET CRAIG", "has_tags", "VINCENT SHERMAN" ], [ "I'LL BE SEEING YOU", "has_genre", "DRAMA" ], [ "I'LL BE SEEING YOU", "release_year", "1944" ], [ "IN THIS OUR LIFE", "has_genre", "DRAMA" ], [ "IN THIS OUR LIFE", "starred_actors", "BETTE DAVIS" ], [ "JEZEBEL", "has_genre", "DRAMA" ], [ "JEZEBEL", "has_tags", "BETTE DAVIS" ], [ "JEZEBEL", "starred_actors", "BETTE DAVIS" ], [ "MARKED WOMAN", "has_genre", "DRAMA" ], [ "MARKED WOMAN", "has_tags", "BETTE DAVIS" ], [ "MARKED WOMAN", "starred_actors", "BETTE DAVIS" ], [ "MOONTIDE", "has_genre", "DRAMA" ], [ "MOONTIDE", "starred_actors", "CLAUDE RAINS" ], [ "MR. SKEFFINGTON", "directed_by", "VINCENT SHERMAN" ], [ "MR. SKEFFINGTON", "has_genre", "DRAMA" ], [ "MR. SKEFFINGTON", "has_tags", "VINCENT SHERMAN" ], [ "MR. SKEFFINGTON", "release_year", "1944" ], [ "MR. SKEFFINGTON", "starred_actors", "BETTE DAVIS" ], [ "MR. SKEFFINGTON", "starred_actors", "CLAUDE RAINS" ], [ "MR. SKEFFINGTON", "starred_actors", "GEORGE COULOURIS" ], [ "MR. SKEFFINGTON", "starred_actors", "WALTER ABEL" ], [ "MR. SMITH GOES TO WASHINGTON", "has_genre", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "CLAUDE RAINS" ], [ "MR. SMITH GOES TO WASHINGTON", "has_tags", "DRAMA" ], [ "MR. SMITH GOES TO WASHINGTON", "starred_actors", "CLAUDE RAINS" ], [ "MRS. PARKINGTON", "has_genre", "DRAMA" ], [ "MRS. PARKINGTON", "release_year", "1944" ], [ "NOW, VOYAGER", "has_genre", "DRAMA" ], [ "NOW, VOYAGER", "has_tags", "BETTE DAVIS" ], [ "NOW, VOYAGER", "has_tags", "CLAUDE RAINS" ], [ "NOW, VOYAGER", "starred_actors", "BETTE DAVIS" ], [ "NOW, VOYAGER", "starred_actors", "CLAUDE RAINS" ], [ "OF HUMAN BONDAGE", "has_genre", "DRAMA" ], [ "OF HUMAN BONDAGE", "has_tags", "BETTE DAVIS" ], [ "OF HUMAN BONDAGE", "starred_actors", "BETTE DAVIS" ], [ "OLD ACQUAINTANCE", "directed_by", "VINCENT SHERMAN" ], [ "OLD ACQUAINTANCE", "has_genre", "DRAMA" ], [ "OLD ACQUAINTANCE", "has_tags", "BETTE DAVIS" ], [ "OLD ACQUAINTANCE", "has_tags", "VINCENT SHERMAN" ], [ "OLD ACQUAINTANCE", "starred_actors", "BETTE DAVIS" ], [ "PRAISE", "directed_by", "JOHN CURRAN" ], [ "PRAISE", "has_tags", "JOHN CURRAN" ], [ "PRAISE", "release_year", "1998" ], [ "RINGMASTER", "release_year", "1998" ], [ "RINGMASTER", "starred_actors", "JERRY SPRINGER" ], [ "STONE", "directed_by", "JOHN CURRAN" ], [ "STONE", "starred_actors", "EDWARD NORTON" ], [ "STORM CENTER", "has_genre", "DRAMA" ], [ "STORM CENTER", "starred_actors", "BETTE DAVIS" ], [ "THE CABIN IN THE COTTON", "has_genre", "DRAMA" ], [ "THE CABIN IN THE COTTON", "starred_actors", "BETTE DAVIS" ], [ "THE CATERED AFFAIR", "has_genre", "DRAMA" ], [ "THE CATERED AFFAIR", "starred_actors", "BETTE DAVIS" ], [ "THE CHILDREN ARE WATCHING US", "has_genre", "DRAMA" ], [ "THE CHILDREN ARE WATCHING US", "release_year", "1944" ], [ "THE CLAIRVOYANT", "has_genre", "DRAMA" ], [ "THE CLAIRVOYANT", "starred_actors", "CLAUDE RAINS" ], [ "THE CORN IS GREEN", "has_genre", "DRAMA" ], [ "THE CORN IS GREEN", "starred_actors", "BETTE DAVIS" ], [ "THE DEFENDER", "release_year", "2004" ], [ "THE DEFENDER", "starred_actors", "JERRY SPRINGER" ], [ "THE GREAT LIE", "has_genre", "DRAMA" ], [ "THE GREAT LIE", "starred_actors", "BETTE DAVIS" ], [ "THE HARD WAY", "directed_by", "VINCENT SHERMAN" ], [ "THE HARD WAY", "has_genre", "DRAMA" ], [ "THE HARD WAY", "has_tags", "VINCENT SHERMAN" ], [ "THE LETTER", "has_genre", "DRAMA" ], [ "THE LETTER", "has_tags", "BETTE DAVIS" ], [ "THE LETTER", "starred_actors", "BETTE DAVIS" ], [ "THE MASK OF DIMITRIOS", "has_genre", "DRAMA" ], [ "THE MASK OF DIMITRIOS", "release_year", "1944" ], [ "THE PAINTED VEIL", "directed_by", "JOHN CURRAN" ], [ "THE PAINTED VEIL", "has_genre", "DRAMA" ], [ "THE PAINTED VEIL", "has_tags", "EDWARD NORTON" ], [ "THE PAINTED VEIL", "has_tags", "JOHN CURRAN" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_genre", "DRAMA" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "has_tags", "BETTE DAVIS" ], [ "THE PRIVATE LIVES OF ELIZABETH AND ESSEX", "starred_actors", "BETTE DAVIS" ], [ "THE VERDICT", "has_genre", "DRAMA" ], [ "THE VERDICT", "starred_actors", "GEORGE COULOURIS" ], [ "THE VIRGIN QUEEN", "has_genre", "DRAMA" ], [ "THE VIRGIN QUEEN", "starred_actors", "BETTE DAVIS" ], [ "THE WAY AHEAD", "has_genre", "DRAMA" ], [ "THE WAY AHEAD", "release_year", "1944" ], [ "THE WOLF MAN", "has_genre", "DRAMA" ], [ "THE WOLF MAN", "starred_actors", "CLAUDE RAINS" ], [ "THE YOUNG PHILADELPHIANS", "directed_by", "VINCENT SHERMAN" ], [ "THE YOUNG PHILADELPHIANS", "has_genre", "DRAMA" ], [ "THE YOUNG PHILADELPHIANS", "has_tags", "VINCENT SHERMAN" ], [ "THEY MADE ME A CRIMINAL", "has_genre", "DRAMA" ], [ "THEY MADE ME A CRIMINAL", "starred_actors", "CLAUDE RAINS" ], [ "THIS HAPPY BREED", "has_genre", "DRAMA" ], [ "THIS HAPPY BREED", "release_year", "1944" ], [ "THREE ON A MATCH", "has_genre", "DRAMA" ], [ "THREE ON A MATCH", "has_tags", "BETTE DAVIS" ], [ "TRACKS", "directed_by", "JOHN CURRAN" ], [ "TRACKS", "has_genre", "DRAMA" ], [ "TRACKS", "has_tags", "AUSTRALIA" ], [ "TRACKS", "has_tags", "JOHN CURRAN" ], [ "WATCH ON THE RHINE", "has_genre", "DRAMA" ], [ "WATCH ON THE RHINE", "starred_actors", "BETTE DAVIS" ], [ "WE DON'T LIVE HERE ANYMORE", "directed_by", "JOHN CURRAN" ], [ "WE DON'T LIVE HERE ANYMORE", "has_genre", "DRAMA" ], [ "WE DON'T LIVE HERE ANYMORE", "release_year", "2004" ], [ "WHERE LOVE HAS GONE", "has_genre", "DRAMA" ], [ "WHERE LOVE HAS GONE", "starred_actors", "BETTE DAVIS" ], [ "WHITE BANNERS", "has_genre", "DRAMA" ], [ "WHITE BANNERS", "starred_actors", "CLAUDE RAINS" ], [ "WILSON", "has_genre", "DRAMA" ], [ "WILSON", "release_year", "1944" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38097, 1985 37987, A ROOM WITH A VIEW 6594, AGNES OF GOD 23412, ALAMO BAY 30265, BRAZIL 3757, COLONEL REDL 25285, COME AND SEE 31143, DANCE WITH A STRANGER 6806, DEATH OF A SALESMAN 2890, DESERT HEARTS 2382, DESPERATELY SEEKING SUSAN 36212, DRAMA 28373, DREAMCHILD 30833, DÉJÀ VU 21621, ENEMY MINE 27266, FANDANGO 33902, FOOL FOR LOVE 35540, HEAVEN HELP US 33488, INSIGNIFICANCE 33821, KING DAVID 39574, KISS OF THE SPIDER WOMAN 39046, MASK 125, MY BEAUTIFUL LAUNDRETTE 31562, MY LIFE AS A DOG 34938, OUT OF AFRICA 24355, PERFECT 17206, PLENTY 29620, POLICE 27191, RENDEZ-VOUS 10832, REVOLUTION 6016, SEANN WILLIAM SCOTT 3856, SMOOTH TALK 39270, SUBWAY 15048, THAT WAS THEN... THIS IS NOW 6439, THE AVIATOR 17931, THE BREAKFAST CLUB 6882, THE COLOR PURPLE 4802, THE OFFICIAL STORY 18926, THE RUNDOWN 2986, THE YEAR MY VOICE BROKE 18355, TUFF TURF 37279, TURTLE DIARY 12294, VAGABOND 33060, VISION QUEST 30879, WETHERBY 17271, WHEN FATHER WAS AWAY ON BUSINESS 28023, WHITE NIGHTS 5888, YEAR OF THE DRAGON 3398, ZONE TROOPERS src, edge_attr, dst 37987, has_genre, 36212 37987, release_year, 38097 6594, has_genre, 36212 6594, has_tags, 36212 6594, release_year, 38097 23412, has_genre, 36212 23412, release_year, 38097 30265, release_year, 38097 3757, has_genre, 36212 3757, release_year, 38097 25285, has_genre, 36212 25285, release_year, 38097 31143, has_genre, 36212 31143, release_year, 38097 6806, has_genre, 36212 6806, release_year, 38097 2890, has_genre, 36212 2890, release_year, 38097 2382, has_genre, 36212 2382, release_year, 38097 28373, has_genre, 36212 28373, release_year, 38097 30833, has_genre, 36212 30833, release_year, 38097 21621, has_genre, 36212 21621, release_year, 38097 27266, has_genre, 36212 27266, release_year, 38097 33902, has_genre, 36212 33902, release_year, 38097 35540, has_genre, 36212 35540, release_year, 38097 33488, has_genre, 36212 33488, release_year, 38097 33821, has_genre, 36212 33821, release_year, 38097 39574, has_genre, 36212 39574, release_year, 38097 39046, has_genre, 36212 39046, release_year, 38097 125, has_genre, 36212 125, release_year, 38097 31562, has_genre, 36212 31562, release_year, 38097 34938, has_genre, 36212 34938, has_tags, 36212 34938, release_year, 38097 24355, has_genre, 36212 24355, release_year, 38097 17206, has_genre, 36212 17206, release_year, 38097 29620, has_genre, 36212 29620, release_year, 38097 27191, has_genre, 36212 27191, release_year, 38097 10832, has_genre, 36212 10832, release_year, 38097 3856, has_genre, 36212 3856, release_year, 38097 39270, has_genre, 36212 39270, release_year, 38097 15048, has_genre, 36212 15048, release_year, 38097 6439, has_genre, 36212 6439, has_tags, 36212 6439, release_year, 38097 17931, has_genre, 36212 17931, has_tags, 36212 17931, release_year, 38097 6882, has_genre, 36212 6882, release_year, 38097 4802, has_genre, 36212 4802, release_year, 38097 18926, has_tags, 30265 18926, has_tags, 6016 18926, starred_actors, 6016 2986, has_genre, 36212 18355, has_genre, 36212 18355, release_year, 38097 37279, has_genre, 36212 37279, release_year, 38097 12294, has_genre, 36212 12294, release_year, 38097 33060, has_genre, 36212 33060, release_year, 38097 30879, has_genre, 36212 30879, release_year, 38097 17271, has_genre, 36212 17271, release_year, 38097 28023, has_genre, 36212 28023, release_year, 38097 5888, has_genre, 36212 5888, release_year, 38097 3398, release_year, 38097 Question: How are SEANN WILLIAM SCOTT, THE YEAR MY VOICE BROKE, and ZONE TROOPERS related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "SEANN WILLIAM SCOTT", "THE YEAR MY VOICE BROKE", "ZONE TROOPERS" ], "valid_edges": [ [ "A ROOM WITH A VIEW", "has_genre", "DRAMA" ], [ "A ROOM WITH A VIEW", "release_year", "1985" ], [ "AGNES OF GOD", "has_genre", "DRAMA" ], [ "AGNES OF GOD", "has_tags", "DRAMA" ], [ "AGNES OF GOD", "release_year", "1985" ], [ "ALAMO BAY", "has_genre", "DRAMA" ], [ "ALAMO BAY", "release_year", "1985" ], [ "BRAZIL", "release_year", "1985" ], [ "COLONEL REDL", "has_genre", "DRAMA" ], [ "COLONEL REDL", "release_year", "1985" ], [ "COME AND SEE", "has_genre", "DRAMA" ], [ "COME AND SEE", "release_year", "1985" ], [ "DANCE WITH A STRANGER", "has_genre", "DRAMA" ], [ "DANCE WITH A STRANGER", "release_year", "1985" ], [ "DEATH OF A SALESMAN", "has_genre", "DRAMA" ], [ "DEATH OF A SALESMAN", "release_year", "1985" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "release_year", "1985" ], [ "DESPERATELY SEEKING SUSAN", "has_genre", "DRAMA" ], [ "DESPERATELY SEEKING SUSAN", "release_year", "1985" ], [ "DREAMCHILD", "has_genre", "DRAMA" ], [ "DREAMCHILD", "release_year", "1985" ], [ "DÉJÀ VU", "has_genre", "DRAMA" ], [ "DÉJÀ VU", "release_year", "1985" ], [ "ENEMY MINE", "has_genre", "DRAMA" ], [ "ENEMY MINE", "release_year", "1985" ], [ "FANDANGO", "has_genre", "DRAMA" ], [ "FANDANGO", "release_year", "1985" ], [ "FOOL FOR LOVE", "has_genre", "DRAMA" ], [ "FOOL FOR LOVE", "release_year", "1985" ], [ "HEAVEN HELP US", "has_genre", "DRAMA" ], [ "HEAVEN HELP US", "release_year", "1985" ], [ "INSIGNIFICANCE", "has_genre", "DRAMA" ], [ "INSIGNIFICANCE", "release_year", "1985" ], [ "KING DAVID", "has_genre", "DRAMA" ], [ "KING DAVID", "release_year", "1985" ], [ "KISS OF THE SPIDER WOMAN", "has_genre", "DRAMA" ], [ "KISS OF THE SPIDER WOMAN", "release_year", "1985" ], [ "MASK", "has_genre", "DRAMA" ], [ "MASK", "release_year", "1985" ], [ "MY BEAUTIFUL LAUNDRETTE", "has_genre", "DRAMA" ], [ "MY BEAUTIFUL LAUNDRETTE", "release_year", "1985" ], [ "MY LIFE AS A DOG", "has_genre", "DRAMA" ], [ "MY LIFE AS A DOG", "release_year", "1985" ], [ "OUT OF AFRICA", "has_genre", "DRAMA" ], [ "OUT OF AFRICA", "has_tags", "DRAMA" ], [ "OUT OF AFRICA", "release_year", "1985" ], [ "PERFECT", "has_genre", "DRAMA" ], [ "PERFECT", "release_year", "1985" ], [ "PLENTY", "has_genre", "DRAMA" ], [ "PLENTY", "release_year", "1985" ], [ "POLICE", "has_genre", "DRAMA" ], [ "POLICE", "release_year", "1985" ], [ "RENDEZ-VOUS", "has_genre", "DRAMA" ], [ "RENDEZ-VOUS", "release_year", "1985" ], [ "REVOLUTION", "has_genre", "DRAMA" ], [ "REVOLUTION", "release_year", "1985" ], [ "SMOOTH TALK", "has_genre", "DRAMA" ], [ "SMOOTH TALK", "release_year", "1985" ], [ "SUBWAY", "has_genre", "DRAMA" ], [ "SUBWAY", "release_year", "1985" ], [ "THAT WAS THEN... THIS IS NOW", "has_genre", "DRAMA" ], [ "THAT WAS THEN... THIS IS NOW", "release_year", "1985" ], [ "THE AVIATOR", "has_genre", "DRAMA" ], [ "THE AVIATOR", "has_tags", "DRAMA" ], [ "THE AVIATOR", "release_year", "1985" ], [ "THE BREAKFAST CLUB", "has_genre", "DRAMA" ], [ "THE BREAKFAST CLUB", "has_tags", "DRAMA" ], [ "THE BREAKFAST CLUB", "release_year", "1985" ], [ "THE COLOR PURPLE", "has_genre", "DRAMA" ], [ "THE COLOR PURPLE", "release_year", "1985" ], [ "THE OFFICIAL STORY", "has_genre", "DRAMA" ], [ "THE OFFICIAL STORY", "release_year", "1985" ], [ "THE RUNDOWN", "has_tags", "BRAZIL" ], [ "THE RUNDOWN", "has_tags", "SEANN WILLIAM SCOTT" ], [ "THE RUNDOWN", "starred_actors", "SEANN WILLIAM SCOTT" ], [ "THE YEAR MY VOICE BROKE", "has_genre", "DRAMA" ], [ "TUFF TURF", "has_genre", "DRAMA" ], [ "TUFF TURF", "release_year", "1985" ], [ "TURTLE DIARY", "has_genre", "DRAMA" ], [ "TURTLE DIARY", "release_year", "1985" ], [ "VAGABOND", "has_genre", "DRAMA" ], [ "VAGABOND", "release_year", "1985" ], [ "VISION QUEST", "has_genre", "DRAMA" ], [ "VISION QUEST", "release_year", "1985" ], [ "WETHERBY", "has_genre", "DRAMA" ], [ "WETHERBY", "release_year", "1985" ], [ "WHEN FATHER WAS AWAY ON BUSINESS", "has_genre", "DRAMA" ], [ "WHEN FATHER WAS AWAY ON BUSINESS", "release_year", "1985" ], [ "WHITE NIGHTS", "has_genre", "DRAMA" ], [ "WHITE NIGHTS", "release_year", "1985" ], [ "YEAR OF THE DRAGON", "has_genre", "DRAMA" ], [ "YEAR OF THE DRAGON", "release_year", "1985" ], [ "ZONE TROOPERS", "release_year", "1985" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 24525, 1984 21004, A CRY IN THE NIGHT 21151, AGAINST ALL ODDS 31137, ALEX KARRAS 30463, COMEDY 15253, COMIC BOOK 36212, DRAMA 12359, KICK-ASS 25894, KICK-ASS 2 20996, MARK MILLAR 36867, PAPER LION 2980, SUPERHERO 12438, WRITTEN ON THE WIND src, edge_attr, dst 24525, release_year, 9177 21004, has_genre, 36212 21004, release_year, 9177 21151, release_year, 24525 21151, starred_actors, 31137 12359, has_genre, 30463 12359, has_tags, 15253 12359, has_tags, 2980 12359, written_by, 20996 25894, has_genre, 30463 25894, has_tags, 15253 25894, has_tags, 2980 25894, written_by, 20996 36867, has_genre, 30463 36867, starred_actors, 31137 12438, has_genre, 36212 12438, release_year, 9177 Question: In what context are ALEX KARRAS, MARK MILLAR, and WRITTEN ON THE WIND connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALEX KARRAS", "MARK MILLAR", "WRITTEN ON THE WIND" ], "valid_edges": [ [ "1984", "release_year", "1956" ], [ "A CRY IN THE NIGHT", "has_genre", "DRAMA" ], [ "A CRY IN THE NIGHT", "release_year", "1956" ], [ "AGAINST ALL ODDS", "release_year", "1984" ], [ "AGAINST ALL ODDS", "starred_actors", "ALEX KARRAS" ], [ "KICK-ASS", "has_genre", "COMEDY" ], [ "KICK-ASS", "has_tags", "COMIC BOOK" ], [ "KICK-ASS", "has_tags", "SUPERHERO" ], [ "KICK-ASS", "written_by", "MARK MILLAR" ], [ "KICK-ASS 2", "has_genre", "COMEDY" ], [ "KICK-ASS 2", "has_tags", "COMIC BOOK" ], [ "KICK-ASS 2", "has_tags", "SUPERHERO" ], [ "KICK-ASS 2", "written_by", "MARK MILLAR" ], [ "PAPER LION", "has_genre", "COMEDY" ], [ "PAPER LION", "starred_actors", "ALEX KARRAS" ], [ "WRITTEN ON THE WIND", "has_genre", "DRAMA" ], [ "WRITTEN ON THE WIND", "release_year", "1956" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1097, 2003 27261, 2009 12914, A DANGEROUS MAN 11454, AGAINST THE DARK 1822, AWAY WE GO 14839, BELLY OF THE BEAST 2856, BROTHERS 34645, CROSSING OVER 6052, DRIVEN TO KILL 30179, I CAPTURE THE CASTLE 34072, I'M NOT SCARED 16560, INGLOURIOUS BASTERDS 11898, JON GUNN 19474, KEONI WAXMAN 27212, KONTROLL 25587, LIKE DANDELION DUST 15814, LOST IN TRANSLATION 13672, LOVE ACTUALLY 3876, MELVIN GOES TO DINNER 5641, MONSIEUR IBRAHIM 12944, MY LIFE WITHOUT ME 21889, OLD SCHOOL 32954, OLDBOY 9357, OUT FOR A KILL 13081, R 14589, S. DARKO 3416, SARABAND 38596, SPREAD 11177, STEVEN SEAGAL 38965, THE BARBARIAN INVASIONS 12623, THE BEST OF YOUTH 39110, THE FOREIGNER 21338, THE GIRL WHO PLAYED WITH FIRE 7240, THE GIRL WITH THE DRAGON TATTOO 29952, THE INTERNATIONAL 5567, THE KEEPER 28024, THE MEN WHO STARE AT GOATS 37148, THE SECRET IN THEIR EYES 38108, THE STATION AGENT 22820, THE UNITED STATES OF LELAND 26758, THICK AS THIEVES 1411, THIRTEEN 25406, UP IN THE AIR 22588, WANTED 20465, WATCHMEN src, edge_attr, dst 12914, directed_by, 19474 12914, release_year, 27261 12914, starred_actors, 11177 12914, written_by, 19474 11454, has_tags, 11177 11454, release_year, 27261 11454, starred_actors, 11177 1822, has_tags, 13081 1822, release_year, 27261 14839, release_year, 1097 14839, starred_actors, 11177 2856, has_tags, 13081 2856, release_year, 27261 34645, has_tags, 13081 34645, release_year, 27261 6052, release_year, 27261 6052, starred_actors, 11177 30179, has_tags, 13081 30179, release_year, 1097 34072, has_tags, 13081 34072, release_year, 1097 16560, has_tags, 13081 16560, release_year, 27261 27212, has_tags, 13081 27212, release_year, 1097 25587, directed_by, 11898 25587, release_year, 27261 15814, has_tags, 13081 15814, release_year, 1097 13672, has_tags, 13081 13672, release_year, 1097 3876, has_tags, 13081 3876, release_year, 1097 5641, has_tags, 13081 5641, release_year, 1097 12944, has_tags, 13081 12944, release_year, 1097 21889, has_tags, 13081 21889, release_year, 1097 32954, has_tags, 13081 32954, release_year, 1097 9357, release_year, 1097 9357, starred_actors, 11177 14589, has_tags, 13081 14589, release_year, 27261 3416, has_tags, 13081 3416, release_year, 1097 38596, has_tags, 13081 38596, release_year, 27261 38965, has_tags, 13081 38965, release_year, 1097 12623, has_tags, 13081 12623, release_year, 1097 39110, release_year, 1097 39110, starred_actors, 11177 21338, has_tags, 13081 21338, release_year, 27261 7240, has_tags, 13081 7240, release_year, 27261 29952, has_tags, 13081 29952, release_year, 27261 5567, directed_by, 19474 5567, release_year, 27261 5567, starred_actors, 11177 28024, has_tags, 13081 28024, release_year, 27261 37148, has_tags, 13081 37148, release_year, 27261 38108, has_tags, 13081 38108, release_year, 1097 22820, has_tags, 13081 22820, release_year, 1097 26758, has_tags, 13081 26758, release_year, 27261 1411, has_tags, 13081 1411, release_year, 1097 25406, has_tags, 13081 25406, release_year, 27261 22588, has_tags, 13081 22588, release_year, 27261 20465, has_tags, 13081 20465, release_year, 27261 Question: In what context are A DANGEROUS MAN, JON GUNN, and THE STATION AGENT connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A DANGEROUS MAN", "JON GUNN", "THE STATION AGENT" ], "valid_edges": [ [ "A DANGEROUS MAN", "directed_by", "KEONI WAXMAN" ], [ "A DANGEROUS MAN", "release_year", "2009" ], [ "A DANGEROUS MAN", "starred_actors", "STEVEN SEAGAL" ], [ "A DANGEROUS MAN", "written_by", "KEONI WAXMAN" ], [ "AGAINST THE DARK", "has_tags", "STEVEN SEAGAL" ], [ "AGAINST THE DARK", "release_year", "2009" ], [ "AGAINST THE DARK", "starred_actors", "STEVEN SEAGAL" ], [ "AWAY WE GO", "has_tags", "R" ], [ "AWAY WE GO", "release_year", "2009" ], [ "BELLY OF THE BEAST", "release_year", "2003" ], [ "BELLY OF THE BEAST", "starred_actors", "STEVEN SEAGAL" ], [ "BROTHERS", "has_tags", "R" ], [ "BROTHERS", "release_year", "2009" ], [ "CROSSING OVER", "has_tags", "R" ], [ "CROSSING OVER", "release_year", "2009" ], [ "DRIVEN TO KILL", "release_year", "2009" ], [ "DRIVEN TO KILL", "starred_actors", "STEVEN SEAGAL" ], [ "I CAPTURE THE CASTLE", "has_tags", "R" ], [ "I CAPTURE THE CASTLE", "release_year", "2003" ], [ "I'M NOT SCARED", "has_tags", "R" ], [ "I'M NOT SCARED", "release_year", "2003" ], [ "INGLOURIOUS BASTERDS", "has_tags", "R" ], [ "INGLOURIOUS BASTERDS", "release_year", "2009" ], [ "KONTROLL", "has_tags", "R" ], [ "KONTROLL", "release_year", "2003" ], [ "LIKE DANDELION DUST", "directed_by", "JON GUNN" ], [ "LIKE DANDELION DUST", "release_year", "2009" ], [ "LOST IN TRANSLATION", "has_tags", "R" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE ACTUALLY", "has_tags", "R" ], [ "LOVE ACTUALLY", "release_year", "2003" ], [ "MELVIN GOES TO DINNER", "has_tags", "R" ], [ "MELVIN GOES TO DINNER", "release_year", "2003" ], [ "MONSIEUR IBRAHIM", "has_tags", "R" ], [ "MONSIEUR IBRAHIM", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_tags", "R" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "OLD SCHOOL", "has_tags", "R" ], [ "OLD SCHOOL", "release_year", "2003" ], [ "OLDBOY", "has_tags", "R" ], [ "OLDBOY", "release_year", "2003" ], [ "OUT FOR A KILL", "release_year", "2003" ], [ "OUT FOR A KILL", "starred_actors", "STEVEN SEAGAL" ], [ "S. DARKO", "has_tags", "R" ], [ "S. DARKO", "release_year", "2009" ], [ "SARABAND", "has_tags", "R" ], [ "SARABAND", "release_year", "2003" ], [ "SPREAD", "has_tags", "R" ], [ "SPREAD", "release_year", "2009" ], [ "THE BARBARIAN INVASIONS", "has_tags", "R" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BEST OF YOUTH", "has_tags", "R" ], [ "THE BEST OF YOUTH", "release_year", "2003" ], [ "THE FOREIGNER", "release_year", "2003" ], [ "THE FOREIGNER", "starred_actors", "STEVEN SEAGAL" ], [ "THE GIRL WHO PLAYED WITH FIRE", "has_tags", "R" ], [ "THE GIRL WHO PLAYED WITH FIRE", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "R" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE INTERNATIONAL", "has_tags", "R" ], [ "THE INTERNATIONAL", "release_year", "2009" ], [ "THE KEEPER", "directed_by", "KEONI WAXMAN" ], [ "THE KEEPER", "release_year", "2009" ], [ "THE KEEPER", "starred_actors", "STEVEN SEAGAL" ], [ "THE MEN WHO STARE AT GOATS", "has_tags", "R" ], [ "THE MEN WHO STARE AT GOATS", "release_year", "2009" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE SECRET IN THEIR EYES", "release_year", "2009" ], [ "THE STATION AGENT", "has_tags", "R" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_tags", "R" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THICK AS THIEVES", "has_tags", "R" ], [ "THICK AS THIEVES", "release_year", "2009" ], [ "THIRTEEN", "has_tags", "R" ], [ "THIRTEEN", "release_year", "2003" ], [ "UP IN THE AIR", "has_tags", "R" ], [ "UP IN THE AIR", "release_year", "2009" ], [ "WANTED", "has_tags", "R" ], [ "WANTED", "release_year", "2009" ], [ "WATCHMEN", "has_tags", "R" ], [ "WATCHMEN", "release_year", "2009" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 25611, 4 FOR TEXAS 17505, A LOW DOWN DIRTY SHAME 431, A MAN OF NO IMPORTANCE 36629, A MILLION TO JUAN 39864, A MILLION WAYS TO DIE IN THE WEST 29838, A SIMPLE TWIST OF FATE 10110, A TIME FOR KILLING 7687, ADVANCE TO THE REAR 8841, AIR AMERICA 8837, AIRHEADS 39641, ALONG CAME JONES 27410, ANGELS IN THE OUTFIELD 24704, ANGIE 35639, BABY'S DAY OUT 23899, BAD COMPANY 1868, BARCELONA 10890, BEVERLY HILLS COP III 29301, BLANK CHECK 24639, BLANKMAN 12492, BLAZING SADDLES 34318, CABIN BOY 22539, CAR 54, WHERE ARE YOU? 6588, CAT BALLOU 26883, CEMETERY MAN 16350, CHASERS 38333, CHRIS EIGEMAN 14442, CHRISTOPHER ROBBINS 26781, CIMARRON 15585, CITY SLICKERS 35468, CLEAN SLATE 35351, CLERKS 9387, CLIFFORD 30463, COMEDY 18170, COWBOY 21391, CRACKERJACK 10316, DAMSELS IN DISTRESS 25978, DEADLY ADVICE 19009, DEAR HEART 13424, DON'T DRINK THE WATER 31475, DON'T GO NEAR THE WATER 3893, ED WOOD 26709, ERNEST GOES TO SCHOOL 34967, EVIL ROY SLADE 20441, EXIT TO EDEN 24028, FLOUNDERING 22371, FORREST GUMP 6215, FOUR WEDDINGS AND A FUNERAL 36927, FROM BEIJING WITH LOVE 34775, GETTING EVEN WITH DAD 9142, GETTING IN 25442, GLENN FORD 25721, GOIN' SOUTH 10519, GOLD RAIDERS 5585, GREEDY 34489, GUARDING TESS 25670, HAIL CAESAR 35856, HEARTS OF THE WEST 20990, HOLY MATRIMONY 34412, I LIKE IT LIKE THAT 13163, I LOVE TROUBLE 18096, I.Q. 24832, IN THE ARMY NOW 14341, IT COULD HAPPEN TO YOU 39987, IT RUNS IN THE FAMILY 37202, IT'S PAT 8819, JUBAL 29404, JUNIOR 14878, KABHI HAAN KABHI NAA 18648, LEPRECHAUN 2 19862, LIGHTNING JACK 33575, LITTLE BIG MAN 16780, LITTLE GIANTS 6417, LUST FOR GOLD 25283, MAVERICK 7495, MCLINTOCK! 12620, MILK MONEY 17491, MIRA SORVINO 12371, MIXED NUTS 9817, MONKEY TROUBLE 25796, MURIEL'S WEDDING 28963, MY GIRL 2 24611, MY LITTLE CHICKADEE 4398, NOBODY'S FOOL 32358, NORTH 36883, ONLY YOU 24732, PCU 30595, POCKETFUL OF MIRACLES 11042, PRINCESS CARABOO 26174, PULP FICTION 22395, RADIOLAND MURDERS 34930, RANCHO DELUXE 18664, RANGO 26180, REALITY BITES 25577, RENAISSANCE MAN 14913, ROMY AND MICHELE'S HIGH SCHOOL REUNION 11370, RUSTLERS' RHAPSODY 24642, SERIAL MOM 6468, SKIN GAME 1374, SLEEP WITH ME 16907, SON OF PALEFACE 24664, SPAIN 6144, SPANKING THE MONKEY 7010, SPEECHLESS 35026, STAGGERED 38038, STRAIGHT TO HELL 20877, SWIMMING WITH SHARKS 2567, TAMMY AND THE T-REX 15063, TAMPOPO 7585, TEXAS 34235, TEXAS ACROSS THE RIVER 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 30090, THE AIR UP THERE 13685, THE CHASE 7763, THE CHEYENNE SOCIAL CLUB 37288, THE COURTSHIP OF EDDIE'S FATHER 22164, THE COWBOY WAY 18466, THE DESPERADOES 10084, THE FASTEST GUN ALIVE 9215, THE FAVOR 17956, THE FLINTSTONES 28510, THE FRISCO KID 10878, THE HUDSUCKER PROXY 38210, THE INKWELL 9059, THE LAST DAYS OF DISCO 38550, THE LITTLE RASCALS 35340, THE MAN FROM THE ALAMO 23802, THE MASK 32, THE MATING OF MILLIE 29233, THE MONSTER 17513, THE PALEFACE 33982, THE PAPER 26061, THE REF 13917, THE ROAD TO WELLVILLE 17314, THE SANTA CLAUSE 36289, THE SCOUT 33905, THE SEARCH FOR ONE-EYE JIMMY 28829, THE SECRET OF CONVICT LAKE 33083, THE SHAKIEST GUN IN THE WEST 5394, THE SHEEPMAN 4767, THE SUM OF US 14580, THE TREATMENT 37184, THE TRIUMPH OF LOVE 30942, THE VIOLENT MEN 7342, THEY CALL ME TRINITY 16762, THREESOME 18195, TRAPPED IN PARADISE 12860, TRUE LIES 33767, TWIN SITTERS 36026, WESTERN 9006, WHIT STILLMAN 1790, WILD WILD WEST 39623, WITH HONORS 28489, ZINDAGI NA MILEGI DOBARA 33462, ¡THREE AMIGOS! src, edge_attr, dst 25611, has_genre, 30463 25611, has_genre, 36026 17505, has_genre, 30463 17505, release_year, 26257 431, has_genre, 30463 431, release_year, 26257 36629, has_genre, 30463 36629, release_year, 26257 39864, has_genre, 30463 39864, has_genre, 36026 29838, has_genre, 30463 29838, release_year, 26257 10110, has_genre, 36026 10110, starred_actors, 25442 7687, has_genre, 30463 7687, has_genre, 36026 7687, starred_actors, 25442 8841, has_genre, 30463 8841, written_by, 14442 8837, has_genre, 30463 8837, has_tags, 30463 8837, release_year, 26257 39641, has_genre, 30463 39641, has_genre, 36026 27410, has_genre, 30463 27410, release_year, 26257 24704, has_genre, 30463 24704, release_year, 26257 35639, has_genre, 30463 35639, release_year, 26257 23899, has_genre, 30463 23899, has_genre, 36026 1868, directed_by, 9006 1868, has_genre, 30463 1868, has_tags, 1868 1868, has_tags, 24664 1868, has_tags, 9006 1868, release_year, 26257 1868, starred_actors, 38333 1868, starred_actors, 17491 1868, written_by, 9006 10890, has_genre, 30463 10890, has_tags, 30463 10890, release_year, 26257 29301, has_genre, 30463 29301, release_year, 26257 24639, has_genre, 30463 24639, release_year, 26257 12492, has_genre, 30463 12492, has_genre, 36026 12492, has_tags, 30463 12492, has_tags, 36026 34318, has_genre, 30463 34318, release_year, 26257 22539, has_genre, 30463 22539, release_year, 26257 6588, has_genre, 30463 6588, has_genre, 36026 26883, has_genre, 30463 26883, release_year, 26257 16350, has_genre, 30463 16350, release_year, 26257 26781, has_genre, 36026 26781, starred_actors, 25442 15585, has_genre, 30463 15585, has_genre, 36026 35468, has_genre, 30463 35468, release_year, 26257 35351, has_genre, 30463 35351, has_tags, 30463 35351, release_year, 26257 9387, has_genre, 30463 9387, release_year, 26257 18170, has_genre, 36026 18170, starred_actors, 25442 21391, has_genre, 30463 21391, release_year, 26257 10316, directed_by, 9006 10316, has_genre, 30463 10316, has_tags, 9006 10316, written_by, 9006 25978, has_genre, 30463 25978, release_year, 26257 19009, has_genre, 30463 19009, starred_actors, 25442 13424, has_genre, 30463 13424, release_year, 26257 31475, has_genre, 30463 31475, starred_actors, 25442 3893, has_genre, 30463 3893, release_year, 26257 26709, has_genre, 30463 26709, release_year, 26257 34967, has_genre, 30463 34967, has_genre, 36026 20441, has_genre, 30463 20441, release_year, 26257 24028, has_genre, 30463 24028, release_year, 26257 22371, has_tags, 30463 22371, release_year, 26257 6215, has_genre, 30463 6215, has_tags, 30463 6215, release_year, 26257 36927, has_genre, 30463 36927, release_year, 26257 34775, has_genre, 30463 34775, release_year, 26257 9142, has_genre, 30463 9142, release_year, 26257 25721, has_genre, 30463 25721, has_genre, 36026 10519, has_genre, 30463 10519, has_genre, 36026 5585, has_genre, 30463 5585, release_year, 26257 34489, has_genre, 30463 34489, release_year, 26257 25670, has_genre, 30463 25670, release_year, 26257 35856, has_genre, 30463 35856, has_genre, 36026 20990, has_genre, 30463 20990, release_year, 26257 34412, has_genre, 30463 34412, release_year, 26257 13163, has_genre, 30463 13163, release_year, 26257 18096, has_genre, 30463 18096, release_year, 26257 24832, has_genre, 30463 24832, release_year, 26257 14341, has_genre, 30463 14341, has_tags, 30463 14341, release_year, 26257 39987, has_genre, 30463 39987, release_year, 26257 37202, has_genre, 30463 37202, release_year, 26257 8819, has_genre, 36026 8819, starred_actors, 25442 29404, has_genre, 30463 29404, release_year, 26257 14878, has_genre, 30463 14878, release_year, 26257 18648, has_genre, 30463 18648, release_year, 26257 19862, has_genre, 30463 19862, has_genre, 36026 19862, release_year, 26257 33575, has_genre, 30463 33575, has_genre, 36026 16780, has_genre, 30463 16780, release_year, 26257 6417, has_genre, 36026 6417, starred_actors, 25442 25283, has_genre, 30463 25283, has_tags, 30463 25283, has_tags, 36026 25283, release_year, 26257 7495, has_genre, 30463 7495, has_genre, 36026 12620, has_genre, 30463 12620, release_year, 26257 12371, has_genre, 30463 12371, release_year, 26257 9817, has_genre, 30463 9817, release_year, 26257 25796, has_genre, 30463 25796, has_tags, 30463 25796, release_year, 26257 28963, has_genre, 30463 28963, release_year, 26257 24611, has_genre, 30463 24611, has_genre, 36026 4398, has_genre, 30463 4398, release_year, 26257 32358, has_genre, 30463 32358, release_year, 26257 36883, has_genre, 30463 36883, release_year, 26257 24732, has_genre, 30463 24732, release_year, 26257 30595, has_genre, 30463 30595, has_tags, 30463 30595, starred_actors, 25442 11042, has_genre, 30463 11042, release_year, 26257 26174, has_tags, 30463 26174, release_year, 26257 22395, has_genre, 30463 22395, release_year, 26257 34930, has_genre, 30463 34930, has_genre, 36026 18664, has_genre, 30463 18664, has_tags, 36026 26180, has_genre, 30463 26180, release_year, 26257 25577, has_genre, 30463 25577, release_year, 26257 14913, has_genre, 30463 14913, has_tags, 30463 14913, has_tags, 17491 14913, starred_actors, 17491 11370, has_genre, 30463 11370, has_genre, 36026 24642, has_genre, 30463 24642, has_tags, 30463 24642, release_year, 26257 6468, has_genre, 30463 6468, has_genre, 36026 1374, has_genre, 30463 1374, release_year, 26257 16907, has_genre, 30463 16907, has_genre, 36026 6144, has_genre, 30463 6144, release_year, 26257 7010, has_genre, 30463 7010, release_year, 26257 35026, has_genre, 30463 35026, release_year, 26257 38038, has_genre, 30463 38038, has_genre, 36026 20877, has_genre, 30463 20877, release_year, 26257 2567, has_genre, 30463 2567, release_year, 26257 15063, has_genre, 30463 15063, has_genre, 36026 7585, has_genre, 36026 7585, starred_actors, 25442 34235, has_genre, 30463 34235, has_genre, 36026 25270, has_genre, 30463 25270, release_year, 26257 30090, has_genre, 30463 30090, has_tags, 30463 30090, release_year, 26257 13685, has_genre, 30463 13685, release_year, 26257 7763, has_genre, 30463 7763, has_genre, 36026 37288, has_genre, 30463 37288, starred_actors, 25442 22164, has_genre, 30463 22164, release_year, 26257 18466, has_genre, 36026 18466, starred_actors, 25442 10084, has_genre, 36026 10084, starred_actors, 25442 9215, has_genre, 30463 9215, release_year, 26257 17956, has_genre, 30463 17956, has_tags, 30463 17956, release_year, 26257 28510, has_genre, 30463 28510, has_genre, 36026 10878, has_genre, 30463 10878, has_tags, 30463 10878, release_year, 26257 38210, has_genre, 30463 38210, release_year, 26257 9059, directed_by, 9006 9059, has_genre, 30463 9059, has_tags, 9006 9059, written_by, 9006 38550, has_genre, 30463 38550, release_year, 26257 35340, has_genre, 36026 35340, starred_actors, 25442 23802, has_genre, 30463 23802, has_tags, 30463 23802, release_year, 26257 32, has_genre, 30463 32, starred_actors, 25442 29233, has_genre, 30463 29233, has_tags, 30463 29233, release_year, 26257 17513, has_genre, 30463 17513, has_genre, 36026 33982, has_genre, 30463 33982, release_year, 26257 26061, has_genre, 30463 26061, has_tags, 30463 26061, release_year, 26257 13917, has_genre, 30463 13917, release_year, 26257 17314, has_genre, 30463 17314, release_year, 26257 36289, has_genre, 30463 36289, release_year, 26257 33905, has_genre, 30463 33905, release_year, 26257 28829, has_genre, 36026 28829, starred_actors, 25442 33083, has_genre, 30463 33083, has_genre, 36026 33083, has_tags, 36026 5394, has_genre, 36026 5394, starred_actors, 25442 4767, has_genre, 30463 4767, release_year, 26257 14580, has_genre, 30463 14580, starred_actors, 38333 37184, has_genre, 30463 37184, starred_actors, 17491 30942, has_genre, 36026 30942, starred_actors, 25442 7342, has_genre, 30463 7342, has_genre, 36026 16762, has_genre, 30463 16762, has_tags, 30463 16762, release_year, 26257 18195, has_genre, 30463 18195, release_year, 26257 12860, has_genre, 30463 12860, has_tags, 30463 12860, release_year, 26257 33767, has_genre, 30463 33767, release_year, 26257 1790, has_genre, 30463 1790, has_genre, 36026 1790, has_tags, 30463 39623, has_genre, 30463 39623, release_year, 26257 28489, has_genre, 30463 28489, has_tags, 24664 33462, has_genre, 30463 33462, has_genre, 36026 33462, has_tags, 30463 Question: How are BARCELONA, CHRISTOPHER ROBBINS, and COWBOY related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BARCELONA", "CHRISTOPHER ROBBINS", "COWBOY" ], "valid_edges": [ [ "4 FOR TEXAS", "has_genre", "COMEDY" ], [ "4 FOR TEXAS", "has_genre", "WESTERN" ], [ "A LOW DOWN DIRTY SHAME", "has_genre", "COMEDY" ], [ "A LOW DOWN DIRTY SHAME", "release_year", "1994" ], [ "A MAN OF NO IMPORTANCE", "has_genre", "COMEDY" ], [ "A MAN OF NO IMPORTANCE", "release_year", "1994" ], [ "A MILLION TO JUAN", "has_genre", "COMEDY" ], [ "A MILLION TO JUAN", "release_year", "1994" ], [ "A MILLION WAYS TO DIE IN THE WEST", "has_genre", "COMEDY" ], [ "A MILLION WAYS TO DIE IN THE WEST", "has_genre", "WESTERN" ], [ "A SIMPLE TWIST OF FATE", "has_genre", "COMEDY" ], [ "A SIMPLE TWIST OF FATE", "release_year", "1994" ], [ "A TIME FOR KILLING", "has_genre", "WESTERN" ], [ "A TIME FOR KILLING", "starred_actors", "GLENN FORD" ], [ "ADVANCE TO THE REAR", "has_genre", "COMEDY" ], [ "ADVANCE TO THE REAR", "has_genre", "WESTERN" ], [ "ADVANCE TO THE REAR", "starred_actors", "GLENN FORD" ], [ "AIR AMERICA", "has_genre", "COMEDY" ], [ "AIR AMERICA", "written_by", "CHRISTOPHER ROBBINS" ], [ "AIRHEADS", "has_genre", "COMEDY" ], [ "AIRHEADS", "has_tags", "COMEDY" ], [ "AIRHEADS", "release_year", "1994" ], [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "has_genre", "WESTERN" ], [ "ANGELS IN THE OUTFIELD", "has_genre", "COMEDY" ], [ "ANGELS IN THE OUTFIELD", "release_year", "1994" ], [ "ANGIE", "has_genre", "COMEDY" ], [ "ANGIE", "release_year", "1994" ], [ "BABY'S DAY OUT", "has_genre", "COMEDY" ], [ "BABY'S DAY OUT", "release_year", "1994" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "has_genre", "WESTERN" ], [ "BARCELONA", "directed_by", "WHIT STILLMAN" ], [ "BARCELONA", "has_genre", "COMEDY" ], [ "BARCELONA", "has_tags", "BARCELONA" ], [ "BARCELONA", "has_tags", "SPAIN" ], [ "BARCELONA", "has_tags", "WHIT STILLMAN" ], [ "BARCELONA", "release_year", "1994" ], [ "BARCELONA", "starred_actors", "CHRIS EIGEMAN" ], [ "BARCELONA", "starred_actors", "MIRA SORVINO" ], [ "BARCELONA", "written_by", "WHIT STILLMAN" ], [ "BEVERLY HILLS COP III", "has_genre", "COMEDY" ], [ "BEVERLY HILLS COP III", "has_tags", "COMEDY" ], [ "BEVERLY HILLS COP III", "release_year", "1994" ], [ "BLANK CHECK", "has_genre", "COMEDY" ], [ "BLANK CHECK", "release_year", "1994" ], [ "BLANKMAN", "has_genre", "COMEDY" ], [ "BLANKMAN", "release_year", "1994" ], [ "BLAZING SADDLES", "has_genre", "COMEDY" ], [ "BLAZING SADDLES", "has_genre", "WESTERN" ], [ "BLAZING SADDLES", "has_tags", "COMEDY" ], [ "BLAZING SADDLES", "has_tags", "WESTERN" ], [ "CABIN BOY", "has_genre", "COMEDY" ], [ "CABIN BOY", "release_year", "1994" ], [ "CAR 54, WHERE ARE YOU?", "has_genre", "COMEDY" ], [ "CAR 54, WHERE ARE YOU?", "release_year", "1994" ], [ "CAT BALLOU", "has_genre", "COMEDY" ], [ "CAT BALLOU", "has_genre", "WESTERN" ], [ "CEMETERY MAN", "has_genre", "COMEDY" ], [ "CEMETERY MAN", "release_year", "1994" ], [ "CHASERS", "has_genre", "COMEDY" ], [ "CHASERS", "release_year", "1994" ], [ "CIMARRON", "has_genre", "WESTERN" ], [ "CIMARRON", "starred_actors", "GLENN FORD" ], [ "CITY SLICKERS", "has_genre", "COMEDY" ], [ "CITY SLICKERS", "has_genre", "WESTERN" ], [ "CLEAN SLATE", "has_genre", "COMEDY" ], [ "CLEAN SLATE", "release_year", "1994" ], [ "CLERKS", "has_genre", "COMEDY" ], [ "CLERKS", "has_tags", "COMEDY" ], [ "CLERKS", "release_year", "1994" ], [ "CLIFFORD", "has_genre", "COMEDY" ], [ "CLIFFORD", "release_year", "1994" ], [ "COWBOY", "has_genre", "WESTERN" ], [ "COWBOY", "starred_actors", "GLENN FORD" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "1994" ], [ "DAMSELS IN DISTRESS", "directed_by", "WHIT STILLMAN" ], [ "DAMSELS IN DISTRESS", "has_genre", "COMEDY" ], [ "DAMSELS IN DISTRESS", "has_tags", "WHIT STILLMAN" ], [ "DAMSELS IN DISTRESS", "written_by", "WHIT STILLMAN" ], [ "DEADLY ADVICE", "has_genre", "COMEDY" ], [ "DEADLY ADVICE", "release_year", "1994" ], [ "DEAR HEART", "has_genre", "COMEDY" ], [ "DEAR HEART", "starred_actors", "GLENN FORD" ], [ "DON'T DRINK THE WATER", "has_genre", "COMEDY" ], [ "DON'T DRINK THE WATER", "release_year", "1994" ], [ "DON'T GO NEAR THE WATER", "has_genre", "COMEDY" ], [ "DON'T GO NEAR THE WATER", "starred_actors", "GLENN FORD" ], [ "ED WOOD", "has_genre", "COMEDY" ], [ "ED WOOD", "release_year", "1994" ], [ "ERNEST GOES TO SCHOOL", "has_genre", "COMEDY" ], [ "ERNEST GOES TO SCHOOL", "release_year", "1994" ], [ "EVIL ROY SLADE", "has_genre", "COMEDY" ], [ "EVIL ROY SLADE", "has_genre", "WESTERN" ], [ "EXIT TO EDEN", "has_genre", "COMEDY" ], [ "EXIT TO EDEN", "release_year", "1994" ], [ "FLOUNDERING", "has_genre", "COMEDY" ], [ "FLOUNDERING", "release_year", "1994" ], [ "FORREST GUMP", "has_tags", "COMEDY" ], [ "FORREST GUMP", "release_year", "1994" ], [ "FOUR WEDDINGS AND A FUNERAL", "has_genre", "COMEDY" ], [ "FOUR WEDDINGS AND A FUNERAL", "has_tags", "COMEDY" ], [ "FOUR WEDDINGS AND A FUNERAL", "release_year", "1994" ], [ "FROM BEIJING WITH LOVE", "has_genre", "COMEDY" ], [ "FROM BEIJING WITH LOVE", "release_year", "1994" ], [ "GETTING EVEN WITH DAD", "has_genre", "COMEDY" ], [ "GETTING EVEN WITH DAD", "release_year", "1994" ], [ "GETTING IN", "has_genre", "COMEDY" ], [ "GETTING IN", "release_year", "1994" ], [ "GOIN' SOUTH", "has_genre", "COMEDY" ], [ "GOIN' SOUTH", "has_genre", "WESTERN" ], [ "GOLD RAIDERS", "has_genre", "COMEDY" ], [ "GOLD RAIDERS", "has_genre", "WESTERN" ], [ "GREEDY", "has_genre", "COMEDY" ], [ "GREEDY", "release_year", "1994" ], [ "GUARDING TESS", "has_genre", "COMEDY" ], [ "GUARDING TESS", "release_year", "1994" ], [ "HAIL CAESAR", "has_genre", "COMEDY" ], [ "HAIL CAESAR", "release_year", "1994" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_genre", "WESTERN" ], [ "HOLY MATRIMONY", "has_genre", "COMEDY" ], [ "HOLY MATRIMONY", "release_year", "1994" ], [ "I LIKE IT LIKE THAT", "has_genre", "COMEDY" ], [ "I LIKE IT LIKE THAT", "release_year", "1994" ], [ "I LOVE TROUBLE", "has_genre", "COMEDY" ], [ "I LOVE TROUBLE", "release_year", "1994" ], [ "I.Q.", "has_genre", "COMEDY" ], [ "I.Q.", "release_year", "1994" ], [ "IN THE ARMY NOW", "has_genre", "COMEDY" ], [ "IN THE ARMY NOW", "release_year", "1994" ], [ "IT COULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "release_year", "1994" ], [ "IT RUNS IN THE FAMILY", "has_genre", "COMEDY" ], [ "IT RUNS IN THE FAMILY", "release_year", "1994" ], [ "IT'S PAT", "has_genre", "COMEDY" ], [ "IT'S PAT", "release_year", "1994" ], [ "JUBAL", "has_genre", "WESTERN" ], [ "JUBAL", "starred_actors", "GLENN FORD" ], [ "JUNIOR", "has_genre", "COMEDY" ], [ "JUNIOR", "release_year", "1994" ], [ "KABHI HAAN KABHI NAA", "has_genre", "COMEDY" ], [ "KABHI HAAN KABHI NAA", "release_year", "1994" ], [ "LEPRECHAUN 2", "has_genre", "COMEDY" ], [ "LEPRECHAUN 2", "release_year", "1994" ], [ "LIGHTNING JACK", "has_genre", "COMEDY" ], [ "LIGHTNING JACK", "has_genre", "WESTERN" ], [ "LIGHTNING JACK", "release_year", "1994" ], [ "LITTLE BIG MAN", "has_genre", "COMEDY" ], [ "LITTLE BIG MAN", "has_genre", "WESTERN" ], [ "LITTLE GIANTS", "has_genre", "COMEDY" ], [ "LITTLE GIANTS", "release_year", "1994" ], [ "LUST FOR GOLD", "has_genre", "WESTERN" ], [ "LUST FOR GOLD", "starred_actors", "GLENN FORD" ], [ "MAVERICK", "has_genre", "COMEDY" ], [ "MAVERICK", "has_tags", "COMEDY" ], [ "MAVERICK", "has_tags", "WESTERN" ], [ "MAVERICK", "release_year", "1994" ], [ "MCLINTOCK!", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_genre", "WESTERN" ], [ "MILK MONEY", "has_genre", "COMEDY" ], [ "MILK MONEY", "release_year", "1994" ], [ "MIXED NUTS", "has_genre", "COMEDY" ], [ "MIXED NUTS", "release_year", "1994" ], [ "MONKEY TROUBLE", "has_genre", "COMEDY" ], [ "MONKEY TROUBLE", "release_year", "1994" ], [ "MURIEL'S WEDDING", "has_genre", "COMEDY" ], [ "MURIEL'S WEDDING", "has_tags", "COMEDY" ], [ "MURIEL'S WEDDING", "release_year", "1994" ], [ "MY GIRL 2", "has_genre", "COMEDY" ], [ "MY GIRL 2", "release_year", "1994" ], [ "MY LITTLE CHICKADEE", "has_genre", "COMEDY" ], [ "MY LITTLE CHICKADEE", "has_genre", "WESTERN" ], [ "NOBODY'S FOOL", "has_genre", "COMEDY" ], [ "NOBODY'S FOOL", "release_year", "1994" ], [ "NORTH", "has_genre", "COMEDY" ], [ "NORTH", "release_year", "1994" ], [ "ONLY YOU", "has_genre", "COMEDY" ], [ "ONLY YOU", "release_year", "1994" ], [ "PCU", "has_genre", "COMEDY" ], [ "PCU", "release_year", "1994" ], [ "POCKETFUL OF MIRACLES", "has_genre", "COMEDY" ], [ "POCKETFUL OF MIRACLES", "has_tags", "COMEDY" ], [ "POCKETFUL OF MIRACLES", "starred_actors", "GLENN FORD" ], [ "PRINCESS CARABOO", "has_genre", "COMEDY" ], [ "PRINCESS CARABOO", "release_year", "1994" ], [ "PULP FICTION", "has_tags", "COMEDY" ], [ "PULP FICTION", "release_year", "1994" ], [ "RADIOLAND MURDERS", "has_genre", "COMEDY" ], [ "RADIOLAND MURDERS", "release_year", "1994" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "has_genre", "WESTERN" ], [ "RANGO", "has_genre", "COMEDY" ], [ "RANGO", "has_tags", "WESTERN" ], [ "REALITY BITES", "has_genre", "COMEDY" ], [ "REALITY BITES", "release_year", "1994" ], [ "RENAISSANCE MAN", "has_genre", "COMEDY" ], [ "RENAISSANCE MAN", "release_year", "1994" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_genre", "COMEDY" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_tags", "COMEDY" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "has_tags", "MIRA SORVINO" ], [ "ROMY AND MICHELE'S HIGH SCHOOL REUNION", "starred_actors", "MIRA SORVINO" ], [ "RUSTLERS' RHAPSODY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_genre", "WESTERN" ], [ "SERIAL MOM", "has_genre", "COMEDY" ], [ "SERIAL MOM", "has_tags", "COMEDY" ], [ "SERIAL MOM", "release_year", "1994" ], [ "SKIN GAME", "has_genre", "COMEDY" ], [ "SKIN GAME", "has_genre", "WESTERN" ], [ "SLEEP WITH ME", "has_genre", "COMEDY" ], [ "SLEEP WITH ME", "release_year", "1994" ], [ "SON OF PALEFACE", "has_genre", "COMEDY" ], [ "SON OF PALEFACE", "has_genre", "WESTERN" ], [ "SPANKING THE MONKEY", "has_genre", "COMEDY" ], [ "SPANKING THE MONKEY", "release_year", "1994" ], [ "SPEECHLESS", "has_genre", "COMEDY" ], [ "SPEECHLESS", "release_year", "1994" ], [ "STAGGERED", "has_genre", "COMEDY" ], [ "STAGGERED", "release_year", "1994" ], [ "STRAIGHT TO HELL", "has_genre", "COMEDY" ], [ "STRAIGHT TO HELL", "has_genre", "WESTERN" ], [ "SWIMMING WITH SHARKS", "has_genre", "COMEDY" ], [ "SWIMMING WITH SHARKS", "release_year", "1994" ], [ "TAMMY AND THE T-REX", "has_genre", "COMEDY" ], [ "TAMMY AND THE T-REX", "release_year", "1994" ], [ "TAMPOPO", "has_genre", "COMEDY" ], [ "TAMPOPO", "has_genre", "WESTERN" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "TEXAS", "starred_actors", "GLENN FORD" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "COMEDY" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "WESTERN" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "release_year", "1994" ], [ "THE AIR UP THERE", "has_genre", "COMEDY" ], [ "THE AIR UP THERE", "has_tags", "COMEDY" ], [ "THE AIR UP THERE", "release_year", "1994" ], [ "THE CHASE", "has_genre", "COMEDY" ], [ "THE CHASE", "release_year", "1994" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "COMEDY" ], [ "THE CHEYENNE SOCIAL CLUB", "has_genre", "WESTERN" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "has_genre", "COMEDY" ], [ "THE COURTSHIP OF EDDIE'S FATHER", "starred_actors", "GLENN FORD" ], [ "THE COWBOY WAY", "has_genre", "COMEDY" ], [ "THE COWBOY WAY", "release_year", "1994" ], [ "THE DESPERADOES", "has_genre", "WESTERN" ], [ "THE DESPERADOES", "starred_actors", "GLENN FORD" ], [ "THE FASTEST GUN ALIVE", "has_genre", "WESTERN" ], [ "THE FASTEST GUN ALIVE", "starred_actors", "GLENN FORD" ], [ "THE FAVOR", "has_genre", "COMEDY" ], [ "THE FAVOR", "release_year", "1994" ], [ "THE FLINTSTONES", "has_genre", "COMEDY" ], [ "THE FLINTSTONES", "has_tags", "COMEDY" ], [ "THE FLINTSTONES", "release_year", "1994" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "has_genre", "WESTERN" ], [ "THE HUDSUCKER PROXY", "has_genre", "COMEDY" ], [ "THE HUDSUCKER PROXY", "has_tags", "COMEDY" ], [ "THE HUDSUCKER PROXY", "release_year", "1994" ], [ "THE INKWELL", "has_genre", "COMEDY" ], [ "THE INKWELL", "release_year", "1994" ], [ "THE LAST DAYS OF DISCO", "directed_by", "WHIT STILLMAN" ], [ "THE LAST DAYS OF DISCO", "has_genre", "COMEDY" ], [ "THE LAST DAYS OF DISCO", "has_tags", "WHIT STILLMAN" ], [ "THE LAST DAYS OF DISCO", "written_by", "WHIT STILLMAN" ], [ "THE LITTLE RASCALS", "has_genre", "COMEDY" ], [ "THE LITTLE RASCALS", "release_year", "1994" ], [ "THE MAN FROM THE ALAMO", "has_genre", "WESTERN" ], [ "THE MAN FROM THE ALAMO", "starred_actors", "GLENN FORD" ], [ "THE MASK", "has_genre", "COMEDY" ], [ "THE MASK", "has_tags", "COMEDY" ], [ "THE MASK", "release_year", "1994" ], [ "THE MATING OF MILLIE", "has_genre", "COMEDY" ], [ "THE MATING OF MILLIE", "starred_actors", "GLENN FORD" ], [ "THE MONSTER", "has_genre", "COMEDY" ], [ "THE MONSTER", "has_tags", "COMEDY" ], [ "THE MONSTER", "release_year", "1994" ], [ "THE PALEFACE", "has_genre", "COMEDY" ], [ "THE PALEFACE", "has_genre", "WESTERN" ], [ "THE PAPER", "has_genre", "COMEDY" ], [ "THE PAPER", "release_year", "1994" ], [ "THE REF", "has_genre", "COMEDY" ], [ "THE REF", "has_tags", "COMEDY" ], [ "THE REF", "release_year", "1994" ], [ "THE ROAD TO WELLVILLE", "has_genre", "COMEDY" ], [ "THE ROAD TO WELLVILLE", "release_year", "1994" ], [ "THE SANTA CLAUSE", "has_genre", "COMEDY" ], [ "THE SANTA CLAUSE", "release_year", "1994" ], [ "THE SCOUT", "has_genre", "COMEDY" ], [ "THE SCOUT", "release_year", "1994" ], [ "THE SEARCH FOR ONE-EYE JIMMY", "has_genre", "COMEDY" ], [ "THE SEARCH FOR ONE-EYE JIMMY", "release_year", "1994" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "starred_actors", "GLENN FORD" ], [ "THE SHAKIEST GUN IN THE WEST", "has_genre", "COMEDY" ], [ "THE SHAKIEST GUN IN THE WEST", "has_genre", "WESTERN" ], [ "THE SHAKIEST GUN IN THE WEST", "has_tags", "WESTERN" ], [ "THE SHEEPMAN", "has_genre", "WESTERN" ], [ "THE SHEEPMAN", "starred_actors", "GLENN FORD" ], [ "THE SUM OF US", "has_genre", "COMEDY" ], [ "THE SUM OF US", "release_year", "1994" ], [ "THE TREATMENT", "has_genre", "COMEDY" ], [ "THE TREATMENT", "starred_actors", "CHRIS EIGEMAN" ], [ "THE TRIUMPH OF LOVE", "has_genre", "COMEDY" ], [ "THE TRIUMPH OF LOVE", "starred_actors", "MIRA SORVINO" ], [ "THE VIOLENT MEN", "has_genre", "WESTERN" ], [ "THE VIOLENT MEN", "starred_actors", "GLENN FORD" ], [ "THEY CALL ME TRINITY", "has_genre", "COMEDY" ], [ "THEY CALL ME TRINITY", "has_genre", "WESTERN" ], [ "THREESOME", "has_genre", "COMEDY" ], [ "THREESOME", "has_tags", "COMEDY" ], [ "THREESOME", "release_year", "1994" ], [ "TRAPPED IN PARADISE", "has_genre", "COMEDY" ], [ "TRAPPED IN PARADISE", "release_year", "1994" ], [ "TRUE LIES", "has_genre", "COMEDY" ], [ "TRUE LIES", "has_tags", "COMEDY" ], [ "TRUE LIES", "release_year", "1994" ], [ "TWIN SITTERS", "has_genre", "COMEDY" ], [ "TWIN SITTERS", "release_year", "1994" ], [ "WILD WILD WEST", "has_genre", "COMEDY" ], [ "WILD WILD WEST", "has_genre", "WESTERN" ], [ "WILD WILD WEST", "has_tags", "COMEDY" ], [ "WITH HONORS", "has_genre", "COMEDY" ], [ "WITH HONORS", "release_year", "1994" ], [ "ZINDAGI NA MILEGI DOBARA", "has_genre", "COMEDY" ], [ "ZINDAGI NA MILEGI DOBARA", "has_tags", "SPAIN" ], [ "¡THREE AMIGOS!", "has_genre", "COMEDY" ], [ "¡THREE AMIGOS!", "has_genre", "WESTERN" ], [ "¡THREE AMIGOS!", "has_tags", "COMEDY" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 34380, AARON KWOK 27587, ADRIAN SHERGOLD 32539, BREAKFAST WITH SCOT 800, CLAPHAM JUNCTION 23589, EVAN GOLDBERG 15855, GAY 12825, PERSUASION 23152, PRIDE 14802, SAVE ME 26129, SHELTER 35875, SUPERBAD 4175, THE DETECTIVE src, edge_attr, dst 32539, has_tags, 15855 32539, release_year, 17315 800, directed_by, 27587 800, has_tags, 15855 800, release_year, 17315 12825, directed_by, 27587 12825, release_year, 17315 23152, has_tags, 15855 23152, release_year, 17315 14802, has_tags, 15855 14802, release_year, 17315 26129, has_tags, 15855 26129, release_year, 17315 35875, release_year, 17315 35875, written_by, 23589 4175, release_year, 17315 4175, starred_actors, 34380 Question: How are AARON KWOK, CLAPHAM JUNCTION, and EVAN GOLDBERG related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AARON KWOK", "CLAPHAM JUNCTION", "EVAN GOLDBERG" ], "valid_edges": [ [ "BREAKFAST WITH SCOT", "has_tags", "GAY" ], [ "BREAKFAST WITH SCOT", "release_year", "2007" ], [ "CLAPHAM JUNCTION", "directed_by", "ADRIAN SHERGOLD" ], [ "CLAPHAM JUNCTION", "has_tags", "GAY" ], [ "CLAPHAM JUNCTION", "release_year", "2007" ], [ "PERSUASION", "directed_by", "ADRIAN SHERGOLD" ], [ "PERSUASION", "release_year", "2007" ], [ "PRIDE", "has_tags", "GAY" ], [ "PRIDE", "release_year", "2007" ], [ "SAVE ME", "has_tags", "GAY" ], [ "SAVE ME", "release_year", "2007" ], [ "SHELTER", "has_tags", "GAY" ], [ "SHELTER", "release_year", "2007" ], [ "SUPERBAD", "release_year", "2007" ], [ "SUPERBAD", "written_by", "EVAN GOLDBERG" ], [ "THE DETECTIVE", "release_year", "2007" ], [ "THE DETECTIVE", "starred_actors", "AARON KWOK" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25221, 1981 27261, 2009 658, 2012 739, 2081 4020, ARMIE HAMMER 13085, HANDSOME HARRY 424, MIRROR MIRROR 7181, NIGHTHAWKS 10371, SAINT JOHN OF LAS VEGAS 36325, STALLONE 33193, STEVE BUSCEMI 28292, THE MESSENGER 12576, YOUTH IN REVOLT src, edge_attr, dst 25221, release_year, 27261 658, release_year, 27261 739, release_year, 27261 739, starred_actors, 4020 13085, release_year, 27261 13085, starred_actors, 33193 424, release_year, 658 424, starred_actors, 4020 7181, has_tags, 36325 7181, release_year, 25221 10371, release_year, 27261 10371, starred_actors, 33193 28292, has_tags, 33193 28292, release_year, 27261 12576, has_tags, 33193 12576, release_year, 27261 Question: For what reason are ARMIE HAMMER, HANDSOME HARRY, and STALLONE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ARMIE HAMMER", "HANDSOME HARRY", "STALLONE" ], "valid_edges": [ [ "1981", "release_year", "2009" ], [ "2012", "release_year", "2009" ], [ "2081", "release_year", "2009" ], [ "2081", "starred_actors", "ARMIE HAMMER" ], [ "HANDSOME HARRY", "release_year", "2009" ], [ "HANDSOME HARRY", "starred_actors", "STEVE BUSCEMI" ], [ "MIRROR MIRROR", "release_year", "2012" ], [ "MIRROR MIRROR", "starred_actors", "ARMIE HAMMER" ], [ "NIGHTHAWKS", "has_tags", "STALLONE" ], [ "NIGHTHAWKS", "release_year", "1981" ], [ "SAINT JOHN OF LAS VEGAS", "release_year", "2009" ], [ "SAINT JOHN OF LAS VEGAS", "starred_actors", "STEVE BUSCEMI" ], [ "THE MESSENGER", "has_tags", "STEVE BUSCEMI" ], [ "THE MESSENGER", "release_year", "2009" ], [ "YOUTH IN REVOLT", "has_tags", "STEVE BUSCEMI" ], [ "YOUTH IN REVOLT", "release_year", "2009" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 9594, ALZHEIMER'S DISEASE 20038, IRIS 35621, MILLENNIUM ACTRESS 29096, MONSOON WEDDING 20096, SABRINA DHAWAN 18935, SATOSHI KON src, edge_attr, dst 20038, has_tags, 9594 20038, release_year, 13408 35621, directed_by, 18935 35621, has_tags, 18935 35621, release_year, 13408 35621, written_by, 18935 29096, release_year, 13408 29096, written_by, 20096 Question: In what context are ALZHEIMER'S DISEASE, SABRINA DHAWAN, and SATOSHI KON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALZHEIMER'S DISEASE", "SABRINA DHAWAN", "SATOSHI KON" ], "valid_edges": [ [ "IRIS", "has_tags", "ALZHEIMER'S DISEASE" ], [ "IRIS", "release_year", "2001" ], [ "MILLENNIUM ACTRESS", "directed_by", "SATOSHI KON" ], [ "MILLENNIUM ACTRESS", "has_tags", "SATOSHI KON" ], [ "MILLENNIUM ACTRESS", "release_year", "2001" ], [ "MILLENNIUM ACTRESS", "written_by", "SATOSHI KON" ], [ "MONSOON WEDDING", "release_year", "2001" ], [ "MONSOON WEDDING", "written_by", "SABRINA DHAWAN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 23409, AN IDEAL HUSBAND 2297, CHRISTMAS EVE 30463, COMEDY 20519, FRONT PAGE WOMAN 12053, HONEYMOON 14226, IT HAPPENED ON FIFTH AVENUE 38412, LIFE WITH FATHER 27297, MAGIC TOWN 13889, MICHAEL CURTIZ 30166, MONSIEUR VERDOUX 26612, MY FAVORITE BRUNETTE 31713, ROAD TO RIO 31600, RUBIN AND ED 10804, SOMETHING IN THE WIND 18711, SON OF FLUBBER 35507, SONG OF THE THIN MAN 8318, THE BACHELOR AND THE BOBBY-SOXER 28719, THE BISHOP'S WIFE 17991, THE EGG AND I 25837, THE PERILS OF PAULINE 30746, THE SECRET LIFE OF WALTER MITTY 15558, THE SIN OF HAROLD DIDDLEBOCK 262, THE UNSUSPECTED 7486, THIS IS THE ARMY 22241, WE'RE NO ANGELS src, edge_attr, dst 23409, has_genre, 30463 23409, has_tags, 30463 23409, release_year, 26310 2297, has_genre, 30463 2297, release_year, 26310 20519, directed_by, 13889 20519, has_genre, 30463 20519, has_tags, 13889 12053, has_genre, 30463 12053, release_year, 26310 14226, has_genre, 30463 14226, release_year, 26310 38412, has_genre, 30463 38412, release_year, 26310 27297, has_genre, 30463 27297, release_year, 26310 30166, has_genre, 30463 30166, release_year, 26310 26612, has_genre, 30463 26612, release_year, 26310 31713, has_genre, 30463 31713, release_year, 26310 31600, has_genre, 30463 10804, has_genre, 30463 10804, release_year, 26310 18711, has_genre, 30463 35507, has_genre, 30463 35507, release_year, 26310 8318, has_genre, 30463 8318, release_year, 26310 28719, has_genre, 30463 28719, release_year, 26310 17991, has_genre, 30463 17991, release_year, 26310 25837, has_genre, 30463 25837, release_year, 26310 30746, has_genre, 30463 30746, release_year, 26310 15558, has_genre, 30463 15558, release_year, 26310 262, directed_by, 13889 262, has_tags, 13889 262, release_year, 26310 7486, directed_by, 13889 7486, has_genre, 30463 22241, directed_by, 13889 22241, has_genre, 30463 22241, has_tags, 30463 22241, has_tags, 13889 Question: In what context are RUBIN AND ED, SON OF FLUBBER, and THE UNSUSPECTED connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "RUBIN AND ED", "SON OF FLUBBER", "THE UNSUSPECTED" ], "valid_edges": [ [ "AN IDEAL HUSBAND", "has_genre", "COMEDY" ], [ "AN IDEAL HUSBAND", "has_tags", "COMEDY" ], [ "AN IDEAL HUSBAND", "release_year", "1947" ], [ "CHRISTMAS EVE", "has_genre", "COMEDY" ], [ "CHRISTMAS EVE", "release_year", "1947" ], [ "FRONT PAGE WOMAN", "directed_by", "MICHAEL CURTIZ" ], [ "FRONT PAGE WOMAN", "has_genre", "COMEDY" ], [ "FRONT PAGE WOMAN", "has_tags", "MICHAEL CURTIZ" ], [ "HONEYMOON", "has_genre", "COMEDY" ], [ "HONEYMOON", "release_year", "1947" ], [ "IT HAPPENED ON FIFTH AVENUE", "has_genre", "COMEDY" ], [ "IT HAPPENED ON FIFTH AVENUE", "release_year", "1947" ], [ "LIFE WITH FATHER", "has_genre", "COMEDY" ], [ "LIFE WITH FATHER", "release_year", "1947" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MAGIC TOWN", "release_year", "1947" ], [ "MONSIEUR VERDOUX", "has_genre", "COMEDY" ], [ "MONSIEUR VERDOUX", "release_year", "1947" ], [ "MY FAVORITE BRUNETTE", "has_genre", "COMEDY" ], [ "MY FAVORITE BRUNETTE", "release_year", "1947" ], [ "ROAD TO RIO", "has_genre", "COMEDY" ], [ "ROAD TO RIO", "release_year", "1947" ], [ "RUBIN AND ED", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "has_genre", "COMEDY" ], [ "SOMETHING IN THE WIND", "release_year", "1947" ], [ "SON OF FLUBBER", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "has_genre", "COMEDY" ], [ "SONG OF THE THIN MAN", "release_year", "1947" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "has_genre", "COMEDY" ], [ "THE BACHELOR AND THE BOBBY-SOXER", "release_year", "1947" ], [ "THE BISHOP'S WIFE", "has_genre", "COMEDY" ], [ "THE BISHOP'S WIFE", "release_year", "1947" ], [ "THE EGG AND I", "has_genre", "COMEDY" ], [ "THE EGG AND I", "release_year", "1947" ], [ "THE PERILS OF PAULINE", "has_genre", "COMEDY" ], [ "THE PERILS OF PAULINE", "release_year", "1947" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "has_genre", "COMEDY" ], [ "THE SIN OF HAROLD DIDDLEBOCK", "release_year", "1947" ], [ "THE UNSUSPECTED", "directed_by", "MICHAEL CURTIZ" ], [ "THE UNSUSPECTED", "has_tags", "MICHAEL CURTIZ" ], [ "THE UNSUSPECTED", "release_year", "1947" ], [ "THIS IS THE ARMY", "directed_by", "MICHAEL CURTIZ" ], [ "THIS IS THE ARMY", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "directed_by", "MICHAEL CURTIZ" ], [ "WE'RE NO ANGELS", "has_genre", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "COMEDY" ], [ "WE'RE NO ANGELS", "has_tags", "MICHAEL CURTIZ" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26310, 1947 1421, 2013 3536, ASS BACKWARDS 17215, FIRE IN THE BLOOD 30746, THE SECRET LIFE OF WALTER MITTY 18315, THE UNFAITHFUL 19852, ZACKIE ACHMAT src, edge_attr, dst 3536, release_year, 1421 17215, release_year, 1421 17215, starred_actors, 19852 30746, release_year, 26310 30746, release_year, 1421 18315, release_year, 26310 Question: How are ASS BACKWARDS, THE UNFAITHFUL, and ZACKIE ACHMAT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ASS BACKWARDS", "THE UNFAITHFUL", "ZACKIE ACHMAT" ], "valid_edges": [ [ "ASS BACKWARDS", "release_year", "2013" ], [ "FIRE IN THE BLOOD", "release_year", "2013" ], [ "FIRE IN THE BLOOD", "starred_actors", "ZACKIE ACHMAT" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "1947" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "2013" ], [ "THE UNFAITHFUL", "release_year", "1947" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4058, 16 YEARS OF ALCOHOL 8779, 1945 1097, 2003 31345, 21 GRAMS 26501, ALILA 39500, ALL THE REAL GIRLS 16391, AMERICAN SPLENDOR 30281, ANA AND THE OTHERS 12144, BAD BOYS 33140, BAGHBAN 2419, BEYOND BORDERS 18822, BIG FISH 39878, BRIGHT FUTURE 22639, BRIGHT YOUNG THINGS 29448, CARANDIRU 19510, CLEOPATRA 4890, COLD MOUNTAIN 28659, DEAD END 28862, DOGVILLE 23182, DOPAMINE 36212, DRAMA 34486, EILA 14257, ELEPHANT 9048, EVIL 7866, FLYWHEEL 24226, FREDDY VS. JASON 39946, GACY 3674, GAMES OF LOVE AND CHANCE 7599, GIRL WITH A PEARL EARRING 25324, HER HIGHNESS AND THE BELLBOY 27350, HITCHCOCK 39494, HOLES 35319, HOPE SPRINGS 20309, HOUSE OF SAND AND FOG 19839, I ACCUSE 6684, I'LL SLEEP WHEN I'M DEAD 21437, IN THE CITY 31900, INCANTATO 39987, IT RUNS IN THE FAMILY 6425, IT'S ALL ABOUT LOVE 21614, JAPANESE STORY 8844, JONNY VANG 31245, KAL HO NAA HO 26853, LATTER DAYS 13296, LEVITY 15814, LOST IN TRANSLATION 35948, LOVE COMES SOFTLY 2088, MAIN PREM KI DIWANI HOON 11334, MASKED AND ANONYMOUS 18198, MATCHSTICK MEN 25936, MONA LISA SMILE 27827, MONSTER 12944, MY LIFE WITHOUT ME 25424, MY SON JOHN 9343, MYSTIC RIVER 37329, NATHALIE... 34705, NORMAL 21446, OFF THE MAP 10789, OPEN WATER 35341, ORFEU 34120, OSAMA 23553, OUR TOWN 24769, OUT OF THE ASHES 23801, PARTY MONSTER 26350, PIECES OF APRIL 29357, RECONSTRUCTION 16708, ROADS TO KOKTEBEL 12932, ROBERT WALKER 16356, ROBOT STORIES 5145, SAINTS AND SOLDIERS 3416, SARABAND 39821, SECONDHAND LIONS 4027, SHARA 38114, SHATTERED GLASS 5710, SOLDIER'S GIRL 19971, SPIN 40046, STRANGERS ON A TRAIN 6323, STRAYED 16954, SYLVIA 7985, SYMMETRY 11605, TAKE MY EYES 38965, THE BARBARIAN INVASIONS 38410, THE BATTLE OF SHAKER HEIGHTS 5144, THE BIG EMPTY 16923, THE CLOCK 25461, THE COOLER 21345, THE DREAMERS 12047, THE EVENT 20929, THE FIGHTING TEMPTATIONS 12447, THE HUMAN STAIN 32030, THE LOST PRINCE 24434, THE MUDGE BOY 28919, THE RETURN 30906, THE ROOM 38858, THE SHAPE OF THINGS 12883, THE SLEEPING DICTIONARY 2259, THE STATEMENT 38108, THE STATION AGENT 39036, THE STORY OF MARIE AND JULIEN 39883, THE STORY OF THE WEEPING CAMEL 22820, THE UNITED STATES OF LELAND 1411, THIRTEEN 10628, TIME OF THE WOLF 35264, TWO DAYS 11544, UNDER THE TUSCAN SUN 14956, VOICES OF A DISTANT STAR 31862, WONDERLAND 27708, WUTHERING HEIGHTS 39834, YOUNG ADAM src, edge_attr, dst 4058, has_genre, 36212 4058, release_year, 1097 31345, has_genre, 36212 31345, has_tags, 36212 31345, release_year, 1097 26501, has_genre, 36212 26501, release_year, 1097 39500, has_genre, 36212 39500, release_year, 1097 16391, has_genre, 36212 16391, release_year, 1097 30281, has_genre, 36212 30281, release_year, 1097 12144, has_genre, 36212 12144, release_year, 1097 33140, has_genre, 36212 33140, release_year, 1097 2419, has_genre, 36212 2419, release_year, 1097 18822, has_genre, 36212 18822, release_year, 1097 39878, has_genre, 36212 39878, release_year, 1097 22639, has_genre, 36212 22639, release_year, 1097 29448, has_genre, 36212 29448, release_year, 1097 19510, has_genre, 36212 19510, release_year, 1097 4890, has_genre, 36212 4890, has_tags, 36212 4890, release_year, 1097 28659, has_genre, 36212 28659, release_year, 1097 28862, has_genre, 36212 28862, has_tags, 36212 28862, release_year, 1097 23182, has_genre, 36212 23182, release_year, 1097 34486, has_genre, 36212 34486, release_year, 1097 14257, has_genre, 36212 14257, release_year, 1097 9048, has_genre, 36212 9048, release_year, 1097 7866, has_genre, 36212 7866, release_year, 1097 24226, release_year, 1097 39946, has_genre, 36212 39946, release_year, 1097 3674, has_genre, 36212 3674, release_year, 1097 7599, has_genre, 36212 7599, has_tags, 36212 7599, release_year, 1097 25324, release_year, 8779 25324, starred_actors, 12932 27350, has_genre, 36212 39494, has_genre, 36212 39494, release_year, 1097 35319, has_genre, 36212 35319, release_year, 1097 20309, has_genre, 36212 20309, release_year, 1097 19839, has_genre, 36212 19839, release_year, 1097 6684, has_genre, 36212 6684, release_year, 1097 21437, has_genre, 36212 21437, release_year, 1097 31900, has_genre, 36212 31900, release_year, 1097 39987, has_genre, 36212 39987, release_year, 1097 6425, has_genre, 36212 6425, release_year, 1097 21614, has_genre, 36212 21614, release_year, 1097 8844, has_genre, 36212 8844, release_year, 1097 31245, has_genre, 36212 31245, release_year, 1097 26853, has_genre, 36212 26853, release_year, 1097 13296, has_genre, 36212 13296, release_year, 1097 15814, has_genre, 36212 15814, release_year, 1097 35948, has_genre, 36212 35948, release_year, 1097 2088, has_genre, 36212 2088, release_year, 1097 11334, has_genre, 36212 11334, release_year, 1097 18198, has_genre, 36212 18198, has_tags, 36212 18198, release_year, 1097 25936, has_genre, 36212 25936, release_year, 1097 27827, has_genre, 36212 27827, has_tags, 36212 27827, release_year, 1097 12944, has_genre, 36212 12944, release_year, 1097 25424, has_genre, 36212 25424, starred_actors, 12932 9343, has_genre, 36212 9343, has_tags, 36212 9343, release_year, 1097 37329, has_genre, 36212 37329, release_year, 1097 34705, has_genre, 36212 34705, release_year, 1097 21446, has_genre, 36212 21446, has_tags, 36212 21446, release_year, 1097 10789, has_genre, 36212 10789, release_year, 1097 35341, has_genre, 36212 34120, has_genre, 36212 34120, release_year, 1097 23553, has_genre, 36212 23553, release_year, 1097 24769, has_genre, 36212 24769, release_year, 1097 23801, has_genre, 36212 23801, release_year, 1097 26350, has_genre, 36212 26350, release_year, 1097 29357, has_genre, 36212 29357, release_year, 1097 16708, has_genre, 36212 16708, release_year, 1097 16356, has_genre, 36212 16356, release_year, 1097 5145, has_genre, 36212 5145, release_year, 1097 3416, has_genre, 36212 3416, has_tags, 36212 3416, release_year, 1097 39821, has_genre, 36212 39821, release_year, 1097 4027, has_genre, 36212 4027, release_year, 1097 38114, has_genre, 36212 38114, release_year, 1097 5710, has_genre, 36212 5710, release_year, 1097 19971, has_genre, 36212 19971, release_year, 1097 40046, has_tags, 27350 40046, starred_actors, 12932 6323, has_genre, 36212 6323, release_year, 1097 16954, has_genre, 36212 16954, release_year, 1097 7985, has_genre, 36212 7985, release_year, 1097 11605, has_genre, 36212 11605, release_year, 1097 38965, has_genre, 36212 38965, release_year, 1097 38410, has_genre, 36212 38410, release_year, 1097 5144, has_genre, 36212 5144, release_year, 1097 16923, has_genre, 36212 16923, release_year, 8779 16923, starred_actors, 12932 25461, has_genre, 36212 25461, release_year, 1097 21345, has_genre, 36212 21345, release_year, 1097 12047, has_genre, 36212 12047, release_year, 1097 20929, has_genre, 36212 20929, release_year, 1097 12447, has_genre, 36212 12447, release_year, 1097 32030, has_genre, 36212 32030, release_year, 1097 24434, has_genre, 36212 24434, release_year, 1097 28919, has_genre, 36212 28919, release_year, 1097 30906, has_genre, 36212 30906, release_year, 1097 38858, has_genre, 36212 38858, release_year, 1097 12883, has_genre, 36212 12883, release_year, 1097 2259, has_genre, 36212 2259, release_year, 1097 38108, has_genre, 36212 38108, release_year, 1097 39036, has_genre, 36212 39036, release_year, 1097 39883, has_genre, 36212 39883, release_year, 1097 22820, has_genre, 36212 22820, release_year, 1097 1411, has_genre, 36212 1411, has_tags, 36212 1411, release_year, 1097 10628, has_genre, 36212 10628, release_year, 1097 35264, has_genre, 36212 35264, release_year, 1097 11544, has_genre, 36212 11544, release_year, 1097 14956, has_genre, 36212 14956, release_year, 1097 31862, has_genre, 36212 31862, release_year, 1097 27708, has_genre, 36212 27708, release_year, 1097 39834, has_genre, 36212 39834, release_year, 1097 Question: For what reason are FREDDY VS. JASON, ORFEU, and ROBERT WALKER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FREDDY VS. JASON", "ORFEU", "ROBERT WALKER" ], "valid_edges": [ [ "16 YEARS OF ALCOHOL", "has_genre", "DRAMA" ], [ "16 YEARS OF ALCOHOL", "release_year", "2003" ], [ "21 GRAMS", "has_genre", "DRAMA" ], [ "21 GRAMS", "has_tags", "DRAMA" ], [ "21 GRAMS", "release_year", "2003" ], [ "ALILA", "has_genre", "DRAMA" ], [ "ALILA", "release_year", "2003" ], [ "ALL THE REAL GIRLS", "has_genre", "DRAMA" ], [ "ALL THE REAL GIRLS", "release_year", "2003" ], [ "AMERICAN SPLENDOR", "has_genre", "DRAMA" ], [ "AMERICAN SPLENDOR", "release_year", "2003" ], [ "ANA AND THE OTHERS", "has_genre", "DRAMA" ], [ "ANA AND THE OTHERS", "release_year", "2003" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "release_year", "2003" ], [ "BAGHBAN", "has_genre", "DRAMA" ], [ "BAGHBAN", "release_year", "2003" ], [ "BEYOND BORDERS", "has_genre", "DRAMA" ], [ "BEYOND BORDERS", "release_year", "2003" ], [ "BIG FISH", "has_genre", "DRAMA" ], [ "BIG FISH", "release_year", "2003" ], [ "BRIGHT FUTURE", "has_genre", "DRAMA" ], [ "BRIGHT FUTURE", "release_year", "2003" ], [ "BRIGHT YOUNG THINGS", "has_genre", "DRAMA" ], [ "BRIGHT YOUNG THINGS", "release_year", "2003" ], [ "CARANDIRU", "has_genre", "DRAMA" ], [ "CARANDIRU", "release_year", "2003" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "2003" ], [ "COLD MOUNTAIN", "has_genre", "DRAMA" ], [ "COLD MOUNTAIN", "has_tags", "DRAMA" ], [ "COLD MOUNTAIN", "release_year", "2003" ], [ "DEAD END", "has_genre", "DRAMA" ], [ "DEAD END", "release_year", "2003" ], [ "DOGVILLE", "has_genre", "DRAMA" ], [ "DOGVILLE", "has_tags", "DRAMA" ], [ "DOGVILLE", "release_year", "2003" ], [ "DOPAMINE", "has_genre", "DRAMA" ], [ "DOPAMINE", "release_year", "2003" ], [ "EILA", "has_genre", "DRAMA" ], [ "EILA", "release_year", "2003" ], [ "ELEPHANT", "has_genre", "DRAMA" ], [ "ELEPHANT", "release_year", "2003" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "release_year", "2003" ], [ "FLYWHEEL", "has_genre", "DRAMA" ], [ "FLYWHEEL", "release_year", "2003" ], [ "FREDDY VS. JASON", "release_year", "2003" ], [ "GACY", "has_genre", "DRAMA" ], [ "GACY", "release_year", "2003" ], [ "GAMES OF LOVE AND CHANCE", "has_genre", "DRAMA" ], [ "GAMES OF LOVE AND CHANCE", "release_year", "2003" ], [ "GIRL WITH A PEARL EARRING", "has_genre", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "has_tags", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "release_year", "2003" ], [ "HER HIGHNESS AND THE BELLBOY", "release_year", "1945" ], [ "HER HIGHNESS AND THE BELLBOY", "starred_actors", "ROBERT WALKER" ], [ "HITCHCOCK", "has_genre", "DRAMA" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HOLES", "release_year", "2003" ], [ "HOPE SPRINGS", "has_genre", "DRAMA" ], [ "HOPE SPRINGS", "release_year", "2003" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "release_year", "2003" ], [ "I ACCUSE", "has_genre", "DRAMA" ], [ "I ACCUSE", "release_year", "2003" ], [ "I'LL SLEEP WHEN I'M DEAD", "has_genre", "DRAMA" ], [ "I'LL SLEEP WHEN I'M DEAD", "release_year", "2003" ], [ "IN THE CITY", "has_genre", "DRAMA" ], [ "IN THE CITY", "release_year", "2003" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "release_year", "2003" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "IT RUNS IN THE FAMILY", "release_year", "2003" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "release_year", "2003" ], [ "JAPANESE STORY", "has_genre", "DRAMA" ], [ "JAPANESE STORY", "release_year", "2003" ], [ "JONNY VANG", "has_genre", "DRAMA" ], [ "JONNY VANG", "release_year", "2003" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KAL HO NAA HO", "release_year", "2003" ], [ "LATTER DAYS", "has_genre", "DRAMA" ], [ "LATTER DAYS", "release_year", "2003" ], [ "LEVITY", "has_genre", "DRAMA" ], [ "LEVITY", "release_year", "2003" ], [ "LOST IN TRANSLATION", "has_genre", "DRAMA" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "release_year", "2003" ], [ "MAIN PREM KI DIWANI HOON", "has_genre", "DRAMA" ], [ "MAIN PREM KI DIWANI HOON", "release_year", "2003" ], [ "MASKED AND ANONYMOUS", "has_genre", "DRAMA" ], [ "MASKED AND ANONYMOUS", "release_year", "2003" ], [ "MATCHSTICK MEN", "has_genre", "DRAMA" ], [ "MATCHSTICK MEN", "has_tags", "DRAMA" ], [ "MATCHSTICK MEN", "release_year", "2003" ], [ "MONA LISA SMILE", "has_genre", "DRAMA" ], [ "MONA LISA SMILE", "release_year", "2003" ], [ "MONSTER", "has_genre", "DRAMA" ], [ "MONSTER", "has_tags", "DRAMA" ], [ "MONSTER", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "MY SON JOHN", "has_genre", "DRAMA" ], [ "MY SON JOHN", "starred_actors", "ROBERT WALKER" ], [ "MYSTIC RIVER", "has_genre", "DRAMA" ], [ "MYSTIC RIVER", "has_tags", "DRAMA" ], [ "MYSTIC RIVER", "release_year", "2003" ], [ "NATHALIE...", "has_genre", "DRAMA" ], [ "NATHALIE...", "release_year", "2003" ], [ "NORMAL", "has_genre", "DRAMA" ], [ "NORMAL", "release_year", "2003" ], [ "OFF THE MAP", "has_genre", "DRAMA" ], [ "OFF THE MAP", "has_tags", "DRAMA" ], [ "OFF THE MAP", "release_year", "2003" ], [ "OPEN WATER", "has_genre", "DRAMA" ], [ "OPEN WATER", "release_year", "2003" ], [ "ORFEU", "has_genre", "DRAMA" ], [ "OSAMA", "has_genre", "DRAMA" ], [ "OSAMA", "release_year", "2003" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "release_year", "2003" ], [ "OUT OF THE ASHES", "has_genre", "DRAMA" ], [ "OUT OF THE ASHES", "release_year", "2003" ], [ "PARTY MONSTER", "has_genre", "DRAMA" ], [ "PARTY MONSTER", "release_year", "2003" ], [ "PIECES OF APRIL", "has_genre", "DRAMA" ], [ "PIECES OF APRIL", "release_year", "2003" ], [ "RECONSTRUCTION", "has_genre", "DRAMA" ], [ "RECONSTRUCTION", "release_year", "2003" ], [ "ROADS TO KOKTEBEL", "has_genre", "DRAMA" ], [ "ROADS TO KOKTEBEL", "release_year", "2003" ], [ "ROBOT STORIES", "has_genre", "DRAMA" ], [ "ROBOT STORIES", "release_year", "2003" ], [ "SAINTS AND SOLDIERS", "has_genre", "DRAMA" ], [ "SAINTS AND SOLDIERS", "release_year", "2003" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "release_year", "2003" ], [ "SECONDHAND LIONS", "has_genre", "DRAMA" ], [ "SECONDHAND LIONS", "release_year", "2003" ], [ "SHARA", "has_genre", "DRAMA" ], [ "SHARA", "release_year", "2003" ], [ "SHATTERED GLASS", "has_genre", "DRAMA" ], [ "SHATTERED GLASS", "release_year", "2003" ], [ "SOLDIER'S GIRL", "has_genre", "DRAMA" ], [ "SOLDIER'S GIRL", "release_year", "2003" ], [ "SPIN", "has_genre", "DRAMA" ], [ "SPIN", "release_year", "2003" ], [ "STRANGERS ON A TRAIN", "has_tags", "HITCHCOCK" ], [ "STRANGERS ON A TRAIN", "starred_actors", "ROBERT WALKER" ], [ "STRAYED", "has_genre", "DRAMA" ], [ "STRAYED", "release_year", "2003" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "release_year", "2003" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "release_year", "2003" ], [ "TAKE MY EYES", "has_genre", "DRAMA" ], [ "TAKE MY EYES", "release_year", "2003" ], [ "THE BARBARIAN INVASIONS", "has_genre", "DRAMA" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BATTLE OF SHAKER HEIGHTS", "has_genre", "DRAMA" ], [ "THE BATTLE OF SHAKER HEIGHTS", "release_year", "2003" ], [ "THE BIG EMPTY", "has_genre", "DRAMA" ], [ "THE BIG EMPTY", "release_year", "2003" ], [ "THE CLOCK", "has_genre", "DRAMA" ], [ "THE CLOCK", "release_year", "1945" ], [ "THE CLOCK", "starred_actors", "ROBERT WALKER" ], [ "THE COOLER", "has_genre", "DRAMA" ], [ "THE COOLER", "release_year", "2003" ], [ "THE DREAMERS", "has_genre", "DRAMA" ], [ "THE DREAMERS", "release_year", "2003" ], [ "THE EVENT", "has_genre", "DRAMA" ], [ "THE EVENT", "release_year", "2003" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "DRAMA" ], [ "THE FIGHTING TEMPTATIONS", "release_year", "2003" ], [ "THE HUMAN STAIN", "has_genre", "DRAMA" ], [ "THE HUMAN STAIN", "release_year", "2003" ], [ "THE LOST PRINCE", "has_genre", "DRAMA" ], [ "THE LOST PRINCE", "release_year", "2003" ], [ "THE MUDGE BOY", "has_genre", "DRAMA" ], [ "THE MUDGE BOY", "release_year", "2003" ], [ "THE RETURN", "has_genre", "DRAMA" ], [ "THE RETURN", "release_year", "2003" ], [ "THE ROOM", "has_genre", "DRAMA" ], [ "THE ROOM", "release_year", "2003" ], [ "THE SHAPE OF THINGS", "has_genre", "DRAMA" ], [ "THE SHAPE OF THINGS", "release_year", "2003" ], [ "THE SLEEPING DICTIONARY", "has_genre", "DRAMA" ], [ "THE SLEEPING DICTIONARY", "release_year", "2003" ], [ "THE STATEMENT", "has_genre", "DRAMA" ], [ "THE STATEMENT", "release_year", "2003" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE STORY OF MARIE AND JULIEN", "has_genre", "DRAMA" ], [ "THE STORY OF MARIE AND JULIEN", "release_year", "2003" ], [ "THE STORY OF THE WEEPING CAMEL", "has_genre", "DRAMA" ], [ "THE STORY OF THE WEEPING CAMEL", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_genre", "DRAMA" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THIRTEEN", "has_genre", "DRAMA" ], [ "THIRTEEN", "has_tags", "DRAMA" ], [ "THIRTEEN", "release_year", "2003" ], [ "TIME OF THE WOLF", "has_genre", "DRAMA" ], [ "TIME OF THE WOLF", "release_year", "2003" ], [ "TWO DAYS", "has_genre", "DRAMA" ], [ "TWO DAYS", "release_year", "2003" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "release_year", "2003" ], [ "VOICES OF A DISTANT STAR", "has_genre", "DRAMA" ], [ "VOICES OF A DISTANT STAR", "release_year", "2003" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "2003" ], [ "WUTHERING HEIGHTS", "has_genre", "DRAMA" ], [ "WUTHERING HEIGHTS", "release_year", "2003" ], [ "YOUNG ADAM", "has_genre", "DRAMA" ], [ "YOUNG ADAM", "release_year", "2003" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25535, 1950S 6721, 1972 15374, 2005 38707, ASYLUM 38578, BEAUTY SHOP 17939, BURT REYNOLDS 28094, DELIVERANCE 3677, FUZZ 19802, LOVE 20223, THE LONGEST YARD 24108, THE MAN 14967, THE NOTORIOUS BETTIE PAGE 2013, THE TREE OF LIFE src, edge_attr, dst 38707, release_year, 6721 38707, release_year, 15374 38578, release_year, 15374 28094, has_tags, 17939 28094, release_year, 6721 28094, starred_actors, 17939 3677, release_year, 6721 3677, starred_actors, 17939 19802, release_year, 15374 20223, has_tags, 17939 20223, release_year, 15374 20223, starred_actors, 17939 24108, release_year, 6721 24108, release_year, 15374 14967, has_tags, 25535 14967, release_year, 15374 2013, has_tags, 25535 2013, has_tags, 19802 Question: In what context are 1950S, BEAUTY SHOP, and FUZZ connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1950S", "BEAUTY SHOP", "FUZZ" ], "valid_edges": [ [ "ASYLUM", "release_year", "1972" ], [ "ASYLUM", "release_year", "2005" ], [ "BEAUTY SHOP", "release_year", "2005" ], [ "DELIVERANCE", "has_tags", "BURT REYNOLDS" ], [ "DELIVERANCE", "release_year", "1972" ], [ "DELIVERANCE", "starred_actors", "BURT REYNOLDS" ], [ "FUZZ", "release_year", "1972" ], [ "FUZZ", "starred_actors", "BURT REYNOLDS" ], [ "LOVE", "release_year", "2005" ], [ "THE LONGEST YARD", "has_tags", "BURT REYNOLDS" ], [ "THE LONGEST YARD", "release_year", "2005" ], [ "THE LONGEST YARD", "starred_actors", "BURT REYNOLDS" ], [ "THE MAN", "release_year", "1972" ], [ "THE MAN", "release_year", "2005" ], [ "THE NOTORIOUS BETTIE PAGE", "has_tags", "1950S" ], [ "THE NOTORIOUS BETTIE PAGE", "release_year", "2005" ], [ "THE TREE OF LIFE", "has_tags", "1950S" ], [ "THE TREE OF LIFE", "has_tags", "LOVE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37224, 1990 30985, ADVENTURELAND 8841, AIR AMERICA 23942, ALL FOR THE WINNER 39869, ALMOST AN ANGEL 35673, ANOTHER 48 HRS. 38136, ARACHNOPHOBIA 35141, BASKET CASE 2 7380, BETSY'S WEDDING 18793, BILL HADER 16277, BIRD ON A WIRE 21490, BOOK OF LOVE 37451, CADILLAC MAN 26811, CLEAR HISTORY 30463, COMEDY 23734, COUPE DE VILLE 22142, CRAZY PEOPLE 8346, CRY-BABY 16536, CYRANO DE BERGERAC 777, DEATH IN BRUNSWICK 11380, DOWNTOWN 36212, DRAMA 31615, ERNEST GOES TO JAIL 12404, FAR OUT MAN 36067, FLASHBACK 600, FRANKENHOOKER 27618, FUNNY ABOUT LOVE 157, GHOST DAD 26909, GREEN CARD 28236, GREG MOTTOLA 38964, HEART CONDITION 30886, HOME ALONE 17037, HOUSE PARTY 31236, I BOUGHT A VAMPIRE MOTORCYCLE 38459, I LOVE YOU TO DEATH 30468, I'M ALL RIGHT JACK 7361, JOE VERSUS THE VOLCANO 4046, KINDERGARTEN COP 19450, LOOK WHO'S TALKING TOO 35654, LOOSE CANNONS 26370, MADHOUSE 15746, MEN AT WORK 19498, MERMAIDS 5211, MR. DESTINY 18524, MY BLUE HEAVEN 25997, NUNS ON THE RUN 4387, OPPORTUNITY KNOCKS 30091, PAUL 1804, POSTCARDS FROM THE EDGE 17605, PRETTY WOMAN 25436, PROBLEM CHILD 27014, PUMP UP THE VOLUME 24486, QUICK CHANGE 11728, REPOSSESSED 7913, SETH ROGEN 30672, SHORT TIME 33684, SIBLING RIVALRY 15127, SKI PATROL 26957, SPACED INVADERS 35875, SUPERBAD 23378, TAKING CARE OF BUSINESS 39976, TEENAGE MUTANT NINJA TURTLES 13521, THE ADVENTURES OF FORD FAIRLANE 20873, THE BONFIRE OF THE VANITIES 15307, THE DAYTRIPPERS 31555, THE FRESHMAN 2782, THE LONG WALK HOME 17833, THE SHRIMP ON THE BARBIE 22406, THE SPIRIT OF '76 11987, TRUST 31732, URANUS 3620, WELCOME HOME, ROXY CARMICHAEL 33070, WHERE THE HEART IS 32503, WHY ME? src, edge_attr, dst 30985, directed_by, 28236 30985, has_genre, 30463 30985, has_genre, 36212 30985, has_tags, 18793 30985, has_tags, 28236 30985, written_by, 28236 8841, has_genre, 30463 8841, release_year, 37224 23942, has_genre, 30463 23942, release_year, 37224 39869, has_genre, 30463 39869, release_year, 37224 35673, has_genre, 30463 35673, has_tags, 30463 35673, release_year, 37224 38136, has_genre, 30463 38136, has_tags, 30463 38136, release_year, 37224 35141, has_genre, 30463 35141, release_year, 37224 7380, has_genre, 30463 7380, release_year, 37224 16277, has_genre, 30463 16277, has_tags, 30463 16277, release_year, 37224 21490, has_genre, 30463 21490, release_year, 37224 37451, has_genre, 30463 37451, release_year, 37224 26811, directed_by, 28236 26811, has_genre, 30463 26811, has_tags, 18793 26811, has_tags, 28236 26811, starred_actors, 18793 23734, has_genre, 30463 23734, release_year, 37224 22142, has_genre, 30463 22142, release_year, 37224 8346, has_genre, 30463 8346, release_year, 37224 16536, has_genre, 30463 16536, release_year, 37224 777, has_genre, 30463 777, release_year, 37224 11380, has_genre, 30463 11380, release_year, 37224 31615, has_genre, 30463 31615, release_year, 37224 12404, has_genre, 30463 12404, release_year, 37224 36067, has_genre, 30463 36067, release_year, 37224 600, has_genre, 30463 600, release_year, 37224 27618, has_genre, 30463 27618, release_year, 37224 157, has_genre, 30463 157, release_year, 37224 26909, has_genre, 30463 26909, release_year, 37224 38964, has_genre, 30463 38964, release_year, 37224 30886, has_genre, 30463 30886, has_tags, 30463 30886, release_year, 37224 17037, has_genre, 30463 17037, release_year, 37224 31236, has_genre, 30463 31236, release_year, 37224 38459, has_genre, 30463 38459, release_year, 37224 30468, has_genre, 30463 7361, has_genre, 30463 7361, release_year, 37224 4046, has_genre, 30463 4046, has_tags, 30463 4046, release_year, 37224 19450, has_genre, 30463 19450, release_year, 37224 35654, has_genre, 30463 35654, release_year, 37224 26370, has_genre, 30463 26370, release_year, 37224 15746, has_genre, 30463 15746, release_year, 37224 19498, has_genre, 30463 19498, has_tags, 30463 19498, release_year, 37224 5211, has_genre, 30463 5211, release_year, 37224 18524, has_genre, 30463 18524, release_year, 37224 25997, has_genre, 30463 25997, release_year, 37224 4387, has_genre, 30463 4387, release_year, 37224 30091, directed_by, 28236 30091, has_tags, 28236 30091, has_tags, 7913 1804, has_genre, 30463 1804, release_year, 37224 17605, has_genre, 30463 17605, has_tags, 30463 17605, release_year, 37224 25436, has_genre, 30463 25436, release_year, 37224 27014, has_genre, 30463 27014, release_year, 37224 24486, has_genre, 30463 24486, release_year, 37224 11728, has_genre, 30463 11728, release_year, 37224 30672, has_genre, 30463 30672, release_year, 37224 33684, has_genre, 30463 33684, release_year, 37224 15127, has_genre, 30463 15127, release_year, 37224 26957, has_genre, 30463 26957, release_year, 37224 35875, directed_by, 28236 35875, has_genre, 30463 35875, has_tags, 30463 35875, has_tags, 28236 35875, has_tags, 7913 35875, written_by, 7913 23378, has_genre, 30463 23378, release_year, 37224 39976, has_genre, 30463 39976, release_year, 37224 13521, has_genre, 30463 13521, has_tags, 30463 13521, release_year, 37224 20873, has_genre, 30463 20873, release_year, 37224 15307, directed_by, 28236 15307, has_genre, 36212 15307, has_tags, 28236 15307, written_by, 28236 31555, has_genre, 30463 31555, release_year, 37224 2782, release_year, 37224 17833, has_genre, 30463 17833, release_year, 37224 22406, has_genre, 30463 22406, release_year, 37224 11987, has_genre, 30463 11987, release_year, 37224 31732, has_genre, 30463 31732, release_year, 37224 3620, has_genre, 30463 3620, release_year, 37224 33070, has_genre, 30463 33070, release_year, 37224 32503, has_genre, 30463 32503, release_year, 37224 Question: In what context are GREG MOTTOLA, I'M ALL RIGHT JACK, and THE LONG WALK HOME connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GREG MOTTOLA", "I'M ALL RIGHT JACK", "THE LONG WALK HOME" ], "valid_edges": [ [ "ADVENTURELAND", "directed_by", "GREG MOTTOLA" ], [ "ADVENTURELAND", "has_genre", "COMEDY" ], [ "ADVENTURELAND", "has_genre", "DRAMA" ], [ "ADVENTURELAND", "has_tags", "BILL HADER" ], [ "ADVENTURELAND", "has_tags", "GREG MOTTOLA" ], [ "ADVENTURELAND", "written_by", "GREG MOTTOLA" ], [ "AIR AMERICA", "has_genre", "COMEDY" ], [ "AIR AMERICA", "release_year", "1990" ], [ "ALL FOR THE WINNER", "has_genre", "COMEDY" ], [ "ALL FOR THE WINNER", "release_year", "1990" ], [ "ALMOST AN ANGEL", "has_genre", "COMEDY" ], [ "ALMOST AN ANGEL", "release_year", "1990" ], [ "ANOTHER 48 HRS.", "has_genre", "COMEDY" ], [ "ANOTHER 48 HRS.", "has_tags", "COMEDY" ], [ "ANOTHER 48 HRS.", "release_year", "1990" ], [ "ARACHNOPHOBIA", "has_genre", "COMEDY" ], [ "ARACHNOPHOBIA", "has_tags", "COMEDY" ], [ "ARACHNOPHOBIA", "release_year", "1990" ], [ "BASKET CASE 2", "has_genre", "COMEDY" ], [ "BASKET CASE 2", "release_year", "1990" ], [ "BETSY'S WEDDING", "has_genre", "COMEDY" ], [ "BETSY'S WEDDING", "release_year", "1990" ], [ "BIRD ON A WIRE", "has_genre", "COMEDY" ], [ "BIRD ON A WIRE", "has_tags", "COMEDY" ], [ "BIRD ON A WIRE", "release_year", "1990" ], [ "BOOK OF LOVE", "has_genre", "COMEDY" ], [ "BOOK OF LOVE", "release_year", "1990" ], [ "CADILLAC MAN", "has_genre", "COMEDY" ], [ "CADILLAC MAN", "release_year", "1990" ], [ "CLEAR HISTORY", "directed_by", "GREG MOTTOLA" ], [ "CLEAR HISTORY", "has_genre", "COMEDY" ], [ "CLEAR HISTORY", "has_tags", "BILL HADER" ], [ "CLEAR HISTORY", "has_tags", "GREG MOTTOLA" ], [ "CLEAR HISTORY", "starred_actors", "BILL HADER" ], [ "COUPE DE VILLE", "has_genre", "COMEDY" ], [ "COUPE DE VILLE", "release_year", "1990" ], [ "CRAZY PEOPLE", "has_genre", "COMEDY" ], [ "CRAZY PEOPLE", "release_year", "1990" ], [ "CRY-BABY", "has_genre", "COMEDY" ], [ "CRY-BABY", "release_year", "1990" ], [ "CYRANO DE BERGERAC", "has_genre", "COMEDY" ], [ "CYRANO DE BERGERAC", "release_year", "1990" ], [ "DEATH IN BRUNSWICK", "has_genre", "COMEDY" ], [ "DEATH IN BRUNSWICK", "release_year", "1990" ], [ "DOWNTOWN", "has_genre", "COMEDY" ], [ "DOWNTOWN", "release_year", "1990" ], [ "ERNEST GOES TO JAIL", "has_genre", "COMEDY" ], [ "ERNEST GOES TO JAIL", "release_year", "1990" ], [ "FAR OUT MAN", "has_genre", "COMEDY" ], [ "FAR OUT MAN", "release_year", "1990" ], [ "FLASHBACK", "has_genre", "COMEDY" ], [ "FLASHBACK", "release_year", "1990" ], [ "FRANKENHOOKER", "has_genre", "COMEDY" ], [ "FRANKENHOOKER", "release_year", "1990" ], [ "FUNNY ABOUT LOVE", "has_genre", "COMEDY" ], [ "FUNNY ABOUT LOVE", "release_year", "1990" ], [ "GHOST DAD", "has_genre", "COMEDY" ], [ "GHOST DAD", "release_year", "1990" ], [ "GREEN CARD", "has_genre", "COMEDY" ], [ "GREEN CARD", "release_year", "1990" ], [ "HEART CONDITION", "has_genre", "COMEDY" ], [ "HEART CONDITION", "release_year", "1990" ], [ "HOME ALONE", "has_genre", "COMEDY" ], [ "HOME ALONE", "has_tags", "COMEDY" ], [ "HOME ALONE", "release_year", "1990" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "release_year", "1990" ], [ "I BOUGHT A VAMPIRE MOTORCYCLE", "has_genre", "COMEDY" ], [ "I BOUGHT A VAMPIRE MOTORCYCLE", "release_year", "1990" ], [ "I LOVE YOU TO DEATH", "has_genre", "COMEDY" ], [ "I LOVE YOU TO DEATH", "release_year", "1990" ], [ "I'M ALL RIGHT JACK", "has_genre", "COMEDY" ], [ "JOE VERSUS THE VOLCANO", "has_genre", "COMEDY" ], [ "JOE VERSUS THE VOLCANO", "release_year", "1990" ], [ "KINDERGARTEN COP", "has_genre", "COMEDY" ], [ "KINDERGARTEN COP", "has_tags", "COMEDY" ], [ "KINDERGARTEN COP", "release_year", "1990" ], [ "LOOK WHO'S TALKING TOO", "has_genre", "COMEDY" ], [ "LOOK WHO'S TALKING TOO", "release_year", "1990" ], [ "LOOSE CANNONS", "has_genre", "COMEDY" ], [ "LOOSE CANNONS", "release_year", "1990" ], [ "MADHOUSE", "has_genre", "COMEDY" ], [ "MADHOUSE", "release_year", "1990" ], [ "MEN AT WORK", "has_genre", "COMEDY" ], [ "MEN AT WORK", "release_year", "1990" ], [ "MERMAIDS", "has_genre", "COMEDY" ], [ "MERMAIDS", "has_tags", "COMEDY" ], [ "MERMAIDS", "release_year", "1990" ], [ "MR. DESTINY", "has_genre", "COMEDY" ], [ "MR. DESTINY", "release_year", "1990" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "release_year", "1990" ], [ "NUNS ON THE RUN", "has_genre", "COMEDY" ], [ "NUNS ON THE RUN", "release_year", "1990" ], [ "OPPORTUNITY KNOCKS", "has_genre", "COMEDY" ], [ "OPPORTUNITY KNOCKS", "release_year", "1990" ], [ "PAUL", "directed_by", "GREG MOTTOLA" ], [ "PAUL", "has_tags", "GREG MOTTOLA" ], [ "PAUL", "has_tags", "SETH ROGEN" ], [ "POSTCARDS FROM THE EDGE", "has_genre", "COMEDY" ], [ "POSTCARDS FROM THE EDGE", "release_year", "1990" ], [ "PRETTY WOMAN", "has_genre", "COMEDY" ], [ "PRETTY WOMAN", "has_tags", "COMEDY" ], [ "PRETTY WOMAN", "release_year", "1990" ], [ "PROBLEM CHILD", "has_genre", "COMEDY" ], [ "PROBLEM CHILD", "release_year", "1990" ], [ "PUMP UP THE VOLUME", "has_genre", "COMEDY" ], [ "PUMP UP THE VOLUME", "release_year", "1990" ], [ "QUICK CHANGE", "has_genre", "COMEDY" ], [ "QUICK CHANGE", "release_year", "1990" ], [ "REPOSSESSED", "has_genre", "COMEDY" ], [ "REPOSSESSED", "release_year", "1990" ], [ "SHORT TIME", "has_genre", "COMEDY" ], [ "SHORT TIME", "release_year", "1990" ], [ "SIBLING RIVALRY", "has_genre", "COMEDY" ], [ "SIBLING RIVALRY", "release_year", "1990" ], [ "SKI PATROL", "has_genre", "COMEDY" ], [ "SKI PATROL", "release_year", "1990" ], [ "SPACED INVADERS", "has_genre", "COMEDY" ], [ "SPACED INVADERS", "release_year", "1990" ], [ "SUPERBAD", "directed_by", "GREG MOTTOLA" ], [ "SUPERBAD", "has_genre", "COMEDY" ], [ "SUPERBAD", "has_tags", "COMEDY" ], [ "SUPERBAD", "has_tags", "GREG MOTTOLA" ], [ "SUPERBAD", "has_tags", "SETH ROGEN" ], [ "SUPERBAD", "written_by", "SETH ROGEN" ], [ "TAKING CARE OF BUSINESS", "has_genre", "COMEDY" ], [ "TAKING CARE OF BUSINESS", "release_year", "1990" ], [ "TEENAGE MUTANT NINJA TURTLES", "has_genre", "COMEDY" ], [ "TEENAGE MUTANT NINJA TURTLES", "release_year", "1990" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "release_year", "1990" ], [ "THE BONFIRE OF THE VANITIES", "has_genre", "COMEDY" ], [ "THE BONFIRE OF THE VANITIES", "release_year", "1990" ], [ "THE DAYTRIPPERS", "directed_by", "GREG MOTTOLA" ], [ "THE DAYTRIPPERS", "has_genre", "DRAMA" ], [ "THE DAYTRIPPERS", "has_tags", "GREG MOTTOLA" ], [ "THE DAYTRIPPERS", "written_by", "GREG MOTTOLA" ], [ "THE FRESHMAN", "has_genre", "COMEDY" ], [ "THE FRESHMAN", "release_year", "1990" ], [ "THE LONG WALK HOME", "release_year", "1990" ], [ "THE SHRIMP ON THE BARBIE", "has_genre", "COMEDY" ], [ "THE SHRIMP ON THE BARBIE", "release_year", "1990" ], [ "THE SPIRIT OF '76", "has_genre", "COMEDY" ], [ "THE SPIRIT OF '76", "release_year", "1990" ], [ "TRUST", "has_genre", "COMEDY" ], [ "TRUST", "release_year", "1990" ], [ "URANUS", "has_genre", "COMEDY" ], [ "URANUS", "release_year", "1990" ], [ "WELCOME HOME, ROXY CARMICHAEL", "has_genre", "COMEDY" ], [ "WELCOME HOME, ROXY CARMICHAEL", "release_year", "1990" ], [ "WHERE THE HEART IS", "has_genre", "COMEDY" ], [ "WHERE THE HEART IS", "release_year", "1990" ], [ "WHY ME?", "has_genre", "COMEDY" ], [ "WHY ME?", "release_year", "1990" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 772, ALAN RUDOLPH 5905, BUENA VISTA SOCIAL CLUB 207, CHOOSE ME 17958, FLASHPOINT 29274, JON CRYER 10015, KRIS KRISTOFFERSON 39689, LATIN AMERICA 14351, MUSICIANS 18680, NO SMALL AFFAIR 36572, RIP TORN 11725, SONGWRITER 30297, THE WAR ON DEMOCRACY src, edge_attr, dst 5905, has_tags, 39689 5905, has_tags, 14351 207, directed_by, 772 207, release_year, 24525 207, written_by, 772 17958, release_year, 24525 17958, starred_actors, 10015 17958, starred_actors, 36572 18680, release_year, 24525 18680, starred_actors, 29274 11725, directed_by, 772 11725, has_tags, 14351 11725, release_year, 24525 11725, starred_actors, 10015 11725, starred_actors, 36572 30297, has_tags, 39689 Question: In what context are JON CRYER, SONGWRITER, and THE WAR ON DEMOCRACY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JON CRYER", "SONGWRITER", "THE WAR ON DEMOCRACY" ], "valid_edges": [ [ "BUENA VISTA SOCIAL CLUB", "has_tags", "LATIN AMERICA" ], [ "BUENA VISTA SOCIAL CLUB", "has_tags", "MUSICIANS" ], [ "CHOOSE ME", "directed_by", "ALAN RUDOLPH" ], [ "CHOOSE ME", "release_year", "1984" ], [ "CHOOSE ME", "written_by", "ALAN RUDOLPH" ], [ "FLASHPOINT", "release_year", "1984" ], [ "FLASHPOINT", "starred_actors", "KRIS KRISTOFFERSON" ], [ "FLASHPOINT", "starred_actors", "RIP TORN" ], [ "NO SMALL AFFAIR", "release_year", "1984" ], [ "NO SMALL AFFAIR", "starred_actors", "JON CRYER" ], [ "SONGWRITER", "directed_by", "ALAN RUDOLPH" ], [ "SONGWRITER", "has_tags", "MUSICIANS" ], [ "SONGWRITER", "release_year", "1984" ], [ "SONGWRITER", "starred_actors", "KRIS KRISTOFFERSON" ], [ "SONGWRITER", "starred_actors", "RIP TORN" ], [ "THE WAR ON DEMOCRACY", "has_tags", "LATIN AMERICA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7977, 1969 36212, DRAMA 16120, FRANK BUTLER 15642, GOLDEN EARRINGS 23263, RAY MILLAND 6572, THE EARTH IS A SINFUL SONG 1368, THE MILKY WAY 39538, THE THING WITH TWO HEADS 7476, WES BISHOP src, edge_attr, dst 7977, has_genre, 36212 15642, has_tags, 23263 15642, starred_actors, 23263 15642, written_by, 16120 6572, has_genre, 36212 1368, release_year, 7977 1368, written_by, 16120 39538, has_tags, 23263 39538, starred_actors, 23263 39538, written_by, 7476 Question: In what context are FRANK BUTLER, THE EARTH IS A SINFUL SONG, and WES BISHOP connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FRANK BUTLER", "THE EARTH IS A SINFUL SONG", "WES BISHOP" ], "valid_edges": [ [ "1969", "has_genre", "DRAMA" ], [ "GOLDEN EARRINGS", "has_tags", "RAY MILLAND" ], [ "GOLDEN EARRINGS", "starred_actors", "RAY MILLAND" ], [ "GOLDEN EARRINGS", "written_by", "FRANK BUTLER" ], [ "THE EARTH IS A SINFUL SONG", "has_genre", "DRAMA" ], [ "THE MILKY WAY", "release_year", "1969" ], [ "THE MILKY WAY", "written_by", "FRANK BUTLER" ], [ "THE THING WITH TWO HEADS", "has_tags", "RAY MILLAND" ], [ "THE THING WITH TWO HEADS", "starred_actors", "RAY MILLAND" ], [ "THE THING WITH TWO HEADS", "written_by", "WES BISHOP" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9855, AMSTERDAMNED 36212, DRAMA 31008, DUTCH 5870, HORROR 33981, PARANORMAL ACTIVITY 3 36186, PETER FAIMAN 5964, SHIRLEY DOUGLAS 13703, THE LAW OF ENCLOSURES src, edge_attr, dst 9855, has_genre, 5870 9855, in_language, 31008 31008, directed_by, 36186 31008, has_genre, 36212 33981, has_genre, 5870 33981, has_tags, 5870 13703, has_genre, 36212 13703, starred_actors, 5964 Question: For what reason are PARANORMAL ACTIVITY 3, PETER FAIMAN, and SHIRLEY DOUGLAS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "PARANORMAL ACTIVITY 3", "PETER FAIMAN", "SHIRLEY DOUGLAS" ], "valid_edges": [ [ "AMSTERDAMNED", "has_genre", "HORROR" ], [ "AMSTERDAMNED", "in_language", "DUTCH" ], [ "DUTCH", "directed_by", "PETER FAIMAN" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "PARANORMAL ACTIVITY 3", "has_genre", "HORROR" ], [ "PARANORMAL ACTIVITY 3", "has_tags", "HORROR" ], [ "THE LAW OF ENCLOSURES", "has_genre", "DRAMA" ], [ "THE LAW OF ENCLOSURES", "starred_actors", "SHIRLEY DOUGLAS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 17315, 2007 36876, ATTACK 11473, CAPTAIN NEWMAN, M.D. 3567, DAYS OF GLORY 34494, EDDIE ALBERT 11021, EYE IN THE SKY 14180, FORCE 10 FROM NAVARONE 8287, GREGORY PECK 19463, HEDD WYN 676, KATE TSUI 33297, OPERATION PETTICOAT 1916, ORDERS TO KILL 6064, PAUL TURNER 23515, PORK CHOP HILL 27043, PT 109 31405, THE CARDINAL 6424, THE GREAT ESCAPE 23037, THE MAN IN THE GRAY FLANNEL SUIT 3373, THE PURPLE PLAIN 2813, THE SEA WOLVES 16761, TONY CURTIS 38352, TWELVE O'CLOCK HIGH 22214, WAR src, edge_attr, dst 36876, has_genre, 22214 36876, starred_actors, 34494 11473, has_genre, 22214 11473, release_year, 13504 11473, starred_actors, 34494 11473, starred_actors, 8287 11473, starred_actors, 16761 3567, has_genre, 22214 3567, has_tags, 8287 3567, has_tags, 22214 3567, starred_actors, 8287 11021, release_year, 17315 11021, starred_actors, 676 14180, has_genre, 22214 14180, has_tags, 8287 19463, directed_by, 6064 19463, has_genre, 22214 33297, has_genre, 22214 33297, has_tags, 16761 33297, starred_actors, 16761 1916, has_genre, 22214 1916, starred_actors, 34494 23515, has_genre, 22214 23515, starred_actors, 8287 27043, has_genre, 22214 27043, release_year, 13504 31405, has_genre, 22214 31405, release_year, 13504 6424, has_tags, 22214 6424, release_year, 13504 23037, has_genre, 22214 23037, starred_actors, 8287 3373, has_genre, 22214 3373, starred_actors, 8287 2813, has_genre, 22214 2813, starred_actors, 8287 38352, has_genre, 22214 38352, has_tags, 8287 38352, starred_actors, 8287 22214, release_year, 17315 Question: How are CAPTAIN NEWMAN, M.D., KATE TSUI, and PAUL TURNER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CAPTAIN NEWMAN, M.D.", "KATE TSUI", "PAUL TURNER" ], "valid_edges": [ [ "ATTACK", "has_genre", "WAR" ], [ "ATTACK", "starred_actors", "EDDIE ALBERT" ], [ "CAPTAIN NEWMAN, M.D.", "has_genre", "WAR" ], [ "CAPTAIN NEWMAN, M.D.", "release_year", "1963" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "EDDIE ALBERT" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "GREGORY PECK" ], [ "CAPTAIN NEWMAN, M.D.", "starred_actors", "TONY CURTIS" ], [ "DAYS OF GLORY", "has_genre", "WAR" ], [ "DAYS OF GLORY", "has_tags", "GREGORY PECK" ], [ "DAYS OF GLORY", "has_tags", "WAR" ], [ "DAYS OF GLORY", "starred_actors", "GREGORY PECK" ], [ "EYE IN THE SKY", "release_year", "2007" ], [ "EYE IN THE SKY", "starred_actors", "KATE TSUI" ], [ "FORCE 10 FROM NAVARONE", "has_genre", "WAR" ], [ "FORCE 10 FROM NAVARONE", "has_tags", "GREGORY PECK" ], [ "HEDD WYN", "directed_by", "PAUL TURNER" ], [ "HEDD WYN", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_genre", "WAR" ], [ "OPERATION PETTICOAT", "has_tags", "TONY CURTIS" ], [ "OPERATION PETTICOAT", "starred_actors", "TONY CURTIS" ], [ "ORDERS TO KILL", "has_genre", "WAR" ], [ "ORDERS TO KILL", "starred_actors", "EDDIE ALBERT" ], [ "PORK CHOP HILL", "has_genre", "WAR" ], [ "PORK CHOP HILL", "starred_actors", "GREGORY PECK" ], [ "PT 109", "has_genre", "WAR" ], [ "PT 109", "release_year", "1963" ], [ "THE CARDINAL", "has_genre", "WAR" ], [ "THE CARDINAL", "release_year", "1963" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "release_year", "1963" ], [ "THE MAN IN THE GRAY FLANNEL SUIT", "has_genre", "WAR" ], [ "THE MAN IN THE GRAY FLANNEL SUIT", "starred_actors", "GREGORY PECK" ], [ "THE PURPLE PLAIN", "has_genre", "WAR" ], [ "THE PURPLE PLAIN", "starred_actors", "GREGORY PECK" ], [ "THE SEA WOLVES", "has_genre", "WAR" ], [ "THE SEA WOLVES", "starred_actors", "GREGORY PECK" ], [ "TWELVE O'CLOCK HIGH", "has_genre", "WAR" ], [ "TWELVE O'CLOCK HIGH", "has_tags", "GREGORY PECK" ], [ "TWELVE O'CLOCK HIGH", "starred_actors", "GREGORY PECK" ], [ "WAR", "release_year", "2007" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 34060, CREATION 13280, DENNIS THE MENACE 36212, DRAMA 30639, HANK KETCHAM 38634, JON AMIEL 5873, SOMMERSBY 30805, THE NEW GIRLFRIEND src, edge_attr, dst 34060, directed_by, 38634 34060, has_genre, 36212 34060, has_tags, 38634 34060, written_by, 38634 13280, release_year, 24438 13280, written_by, 30639 5873, directed_by, 38634 5873, has_genre, 36212 5873, release_year, 24438 30805, has_genre, 36212 Question: In what context are HANK KETCHAM, JON AMIEL, and THE NEW GIRLFRIEND connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HANK KETCHAM", "JON AMIEL", "THE NEW GIRLFRIEND" ], "valid_edges": [ [ "CREATION", "directed_by", "JON AMIEL" ], [ "CREATION", "has_genre", "DRAMA" ], [ "CREATION", "has_tags", "JON AMIEL" ], [ "CREATION", "written_by", "JON AMIEL" ], [ "DENNIS THE MENACE", "release_year", "1993" ], [ "DENNIS THE MENACE", "written_by", "HANK KETCHAM" ], [ "SOMMERSBY", "directed_by", "JON AMIEL" ], [ "SOMMERSBY", "has_genre", "DRAMA" ], [ "SOMMERSBY", "release_year", "1993" ], [ "THE NEW GIRLFRIEND", "has_genre", "DRAMA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15506, 1933 31362, CLARK GABLE 28538, DANCING LADY 15791, DINNER AT EIGHT 12841, DOCUMENTARY 20824, FLYING DOWN TO RIO 30016, H.W. HANEMANN 16644, JOHN BARRYMORE 23106, LAND WITHOUT BREAD 22149, LIONEL BARRYMORE 31195, LOOKING FORWARD 20443, NIGHT FLIGHT 29373, STEAM OF LIFE 29621, THE STRANGER'S RETURN src, edge_attr, dst 28538, release_year, 15506 28538, starred_actors, 31362 15791, release_year, 15506 15791, starred_actors, 16644 20824, release_year, 15506 20824, written_by, 30016 23106, has_genre, 12841 23106, release_year, 15506 31195, release_year, 15506 31195, starred_actors, 22149 20443, release_year, 15506 20443, starred_actors, 31362 20443, starred_actors, 16644 20443, starred_actors, 22149 29373, has_genre, 12841 29621, release_year, 15506 29621, starred_actors, 22149 Question: How are H.W. HANEMANN, NIGHT FLIGHT, and STEAM OF LIFE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "H.W. HANEMANN", "NIGHT FLIGHT", "STEAM OF LIFE" ], "valid_edges": [ [ "DANCING LADY", "release_year", "1933" ], [ "DANCING LADY", "starred_actors", "CLARK GABLE" ], [ "DINNER AT EIGHT", "release_year", "1933" ], [ "DINNER AT EIGHT", "starred_actors", "JOHN BARRYMORE" ], [ "FLYING DOWN TO RIO", "release_year", "1933" ], [ "FLYING DOWN TO RIO", "written_by", "H.W. HANEMANN" ], [ "LAND WITHOUT BREAD", "has_genre", "DOCUMENTARY" ], [ "LAND WITHOUT BREAD", "release_year", "1933" ], [ "LOOKING FORWARD", "release_year", "1933" ], [ "LOOKING FORWARD", "starred_actors", "LIONEL BARRYMORE" ], [ "NIGHT FLIGHT", "release_year", "1933" ], [ "NIGHT FLIGHT", "starred_actors", "CLARK GABLE" ], [ "NIGHT FLIGHT", "starred_actors", "JOHN BARRYMORE" ], [ "NIGHT FLIGHT", "starred_actors", "LIONEL BARRYMORE" ], [ "STEAM OF LIFE", "has_genre", "DOCUMENTARY" ], [ "THE STRANGER'S RETURN", "release_year", "1933" ], [ "THE STRANGER'S RETURN", "starred_actors", "LIONEL BARRYMORE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13504, 1963 19407, 8½ 24626, A CHILD IS WAITING 39646, ALL THE WAY HOME 34556, AMERICA AMERICA 13570, BILLY LIAR 19510, CLEOPATRA 36212, DRAMA 20659, HIGH AND LOW 39069, LARS AND THE REAL GIRL 5885, LOVE WITH THE PROPER STRANGER 1349, NANCY OLIVER 12572, SOLDIER IN THE RAIN 35252, STOP TRAIN 349 31405, THE CARDINAL 39534, THE CARETAKERS 2893, THE CRAWLING HAND 28928, THE FIRE WITHIN 12999, THE ORGANIZER 32147, THE SERVANT 23091, THE V.I.P.S 22999, TOYS IN THE ATTIC 27794, WATER FOR ELEPHANTS 35124, YOUNG APHRODITES src, edge_attr, dst 19407, has_genre, 36212 19407, release_year, 13504 24626, has_genre, 36212 24626, release_year, 13504 39646, has_genre, 36212 39646, release_year, 13504 34556, has_genre, 36212 34556, release_year, 13504 13570, has_genre, 36212 13570, release_year, 13504 19510, has_genre, 36212 19510, release_year, 13504 20659, has_genre, 36212 20659, release_year, 13504 39069, has_genre, 36212 39069, written_by, 1349 5885, has_genre, 36212 5885, release_year, 13504 12572, has_genre, 36212 12572, release_year, 13504 35252, has_genre, 36212 35252, release_year, 13504 31405, has_genre, 36212 31405, release_year, 13504 39534, has_genre, 36212 39534, release_year, 13504 2893, release_year, 13504 28928, has_genre, 36212 28928, release_year, 13504 12999, has_genre, 36212 12999, release_year, 13504 32147, has_genre, 36212 32147, release_year, 13504 23091, has_genre, 36212 23091, release_year, 13504 22999, has_genre, 36212 22999, release_year, 13504 27794, has_genre, 36212 35124, has_genre, 36212 35124, release_year, 13504 Question: For what reason are NANCY OLIVER, THE CRAWLING HAND, and WATER FOR ELEPHANTS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "NANCY OLIVER", "THE CRAWLING HAND", "WATER FOR ELEPHANTS" ], "valid_edges": [ [ "8½", "has_genre", "DRAMA" ], [ "8½", "release_year", "1963" ], [ "A CHILD IS WAITING", "has_genre", "DRAMA" ], [ "A CHILD IS WAITING", "release_year", "1963" ], [ "ALL THE WAY HOME", "has_genre", "DRAMA" ], [ "ALL THE WAY HOME", "release_year", "1963" ], [ "AMERICA AMERICA", "has_genre", "DRAMA" ], [ "AMERICA AMERICA", "release_year", "1963" ], [ "BILLY LIAR", "has_genre", "DRAMA" ], [ "BILLY LIAR", "release_year", "1963" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "1963" ], [ "HIGH AND LOW", "has_genre", "DRAMA" ], [ "HIGH AND LOW", "release_year", "1963" ], [ "LARS AND THE REAL GIRL", "has_genre", "DRAMA" ], [ "LARS AND THE REAL GIRL", "written_by", "NANCY OLIVER" ], [ "LOVE WITH THE PROPER STRANGER", "has_genre", "DRAMA" ], [ "LOVE WITH THE PROPER STRANGER", "release_year", "1963" ], [ "SOLDIER IN THE RAIN", "has_genre", "DRAMA" ], [ "SOLDIER IN THE RAIN", "release_year", "1963" ], [ "STOP TRAIN 349", "has_genre", "DRAMA" ], [ "STOP TRAIN 349", "release_year", "1963" ], [ "THE CARDINAL", "has_genre", "DRAMA" ], [ "THE CARDINAL", "release_year", "1963" ], [ "THE CARETAKERS", "has_genre", "DRAMA" ], [ "THE CARETAKERS", "release_year", "1963" ], [ "THE CRAWLING HAND", "release_year", "1963" ], [ "THE FIRE WITHIN", "has_genre", "DRAMA" ], [ "THE FIRE WITHIN", "release_year", "1963" ], [ "THE ORGANIZER", "has_genre", "DRAMA" ], [ "THE ORGANIZER", "release_year", "1963" ], [ "THE SERVANT", "has_genre", "DRAMA" ], [ "THE SERVANT", "release_year", "1963" ], [ "THE V.I.P.S", "has_genre", "DRAMA" ], [ "THE V.I.P.S", "release_year", "1963" ], [ "TOYS IN THE ATTIC", "has_genre", "DRAMA" ], [ "TOYS IN THE ATTIC", "release_year", "1963" ], [ "WATER FOR ELEPHANTS", "has_genre", "DRAMA" ], [ "YOUNG APHRODITES", "has_genre", "DRAMA" ], [ "YOUNG APHRODITES", "release_year", "1963" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15374, 2005 35798, 2010 28189, A LITTLE TRIP TO HEAVEN 29638, ALICE IN WONDERLAND 14880, AND SOON THE DARKNESS 28274, ASSASSINATION OF A HIGH SCHOOL PRESIDENT 37687, BALTASAR KORMÁKUR 30335, BE WITH ME 24260, CEREMONY 5840, CERTIFIED COPY 6521, DAYDREAM NATION 16522, DOMINO 31783, ENGLISH 35256, GAME OF DEATH 24815, GOING THE DISTANCE 37827, HIGH SCHOOL 15066, INHALE 37419, IT'S A WONDERFUL AFTERLIFE 5830, LEMMY 29987, LET ME IN 37130, LOOK BOTH WAYS 13531, MATCH POINT 36301, NEDS 24218, NEVERWAS 21568, ON A CLEAR DAY 32901, ON TOUR 26227, PETER MULLAN 13832, REECE THOMPSON 34806, ROOM IN ROME 25509, THE DEBT 8022, THE NEW WORLD 23343, THE WOLFMAN 24521, THESE GIRLS 6279, YOU WILL MEET A TALL DARK STRANGER src, edge_attr, dst 28189, directed_by, 37687 28189, release_year, 15374 28189, written_by, 37687 29638, in_language, 31783 29638, release_year, 35798 14880, in_language, 31783 14880, release_year, 35798 28274, has_tags, 37827 28274, starred_actors, 13832 30335, in_language, 31783 30335, release_year, 15374 24260, release_year, 35798 24260, starred_actors, 13832 5840, in_language, 31783 5840, release_year, 35798 6521, release_year, 35798 6521, starred_actors, 13832 16522, in_language, 31783 16522, release_year, 15374 35256, in_language, 31783 35256, release_year, 35798 24815, in_language, 31783 24815, release_year, 35798 37827, release_year, 35798 15066, directed_by, 37687 15066, release_year, 35798 37419, in_language, 31783 37419, release_year, 35798 5830, in_language, 31783 5830, release_year, 35798 29987, in_language, 31783 29987, release_year, 35798 37130, in_language, 31783 37130, release_year, 15374 13531, in_language, 31783 13531, release_year, 15374 36301, directed_by, 26227 36301, in_language, 31783 36301, release_year, 35798 36301, written_by, 26227 24218, in_language, 31783 24218, release_year, 15374 21568, in_language, 31783 21568, release_year, 15374 21568, starred_actors, 26227 32901, in_language, 31783 32901, release_year, 35798 34806, in_language, 31783 34806, release_year, 35798 25509, in_language, 31783 25509, release_year, 35798 8022, in_language, 31783 8022, release_year, 15374 23343, in_language, 31783 23343, release_year, 35798 24521, in_language, 31783 24521, release_year, 15374 6279, in_language, 31783 6279, release_year, 35798 Question: How are INHALE, ON A CLEAR DAY, and REECE THOMPSON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "INHALE", "ON A CLEAR DAY", "REECE THOMPSON" ], "valid_edges": [ [ "A LITTLE TRIP TO HEAVEN", "directed_by", "BALTASAR KORMÁKUR" ], [ "A LITTLE TRIP TO HEAVEN", "release_year", "2005" ], [ "A LITTLE TRIP TO HEAVEN", "written_by", "BALTASAR KORMÁKUR" ], [ "ALICE IN WONDERLAND", "in_language", "ENGLISH" ], [ "ALICE IN WONDERLAND", "release_year", "2010" ], [ "AND SOON THE DARKNESS", "in_language", "ENGLISH" ], [ "AND SOON THE DARKNESS", "release_year", "2010" ], [ "ASSASSINATION OF A HIGH SCHOOL PRESIDENT", "has_tags", "HIGH SCHOOL" ], [ "ASSASSINATION OF A HIGH SCHOOL PRESIDENT", "starred_actors", "REECE THOMPSON" ], [ "BE WITH ME", "in_language", "ENGLISH" ], [ "BE WITH ME", "release_year", "2005" ], [ "CEREMONY", "release_year", "2010" ], [ "CEREMONY", "starred_actors", "REECE THOMPSON" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "release_year", "2010" ], [ "DAYDREAM NATION", "release_year", "2010" ], [ "DAYDREAM NATION", "starred_actors", "REECE THOMPSON" ], [ "DOMINO", "in_language", "ENGLISH" ], [ "DOMINO", "release_year", "2005" ], [ "GAME OF DEATH", "in_language", "ENGLISH" ], [ "GAME OF DEATH", "release_year", "2010" ], [ "GOING THE DISTANCE", "in_language", "ENGLISH" ], [ "GOING THE DISTANCE", "release_year", "2010" ], [ "HIGH SCHOOL", "release_year", "2010" ], [ "INHALE", "directed_by", "BALTASAR KORMÁKUR" ], [ "INHALE", "release_year", "2010" ], [ "IT'S A WONDERFUL AFTERLIFE", "in_language", "ENGLISH" ], [ "IT'S A WONDERFUL AFTERLIFE", "release_year", "2010" ], [ "LEMMY", "in_language", "ENGLISH" ], [ "LEMMY", "release_year", "2010" ], [ "LET ME IN", "in_language", "ENGLISH" ], [ "LET ME IN", "release_year", "2010" ], [ "LOOK BOTH WAYS", "in_language", "ENGLISH" ], [ "LOOK BOTH WAYS", "release_year", "2005" ], [ "MATCH POINT", "in_language", "ENGLISH" ], [ "MATCH POINT", "release_year", "2005" ], [ "NEDS", "directed_by", "PETER MULLAN" ], [ "NEDS", "in_language", "ENGLISH" ], [ "NEDS", "release_year", "2010" ], [ "NEDS", "written_by", "PETER MULLAN" ], [ "NEVERWAS", "in_language", "ENGLISH" ], [ "NEVERWAS", "release_year", "2005" ], [ "ON A CLEAR DAY", "in_language", "ENGLISH" ], [ "ON A CLEAR DAY", "release_year", "2005" ], [ "ON A CLEAR DAY", "starred_actors", "PETER MULLAN" ], [ "ON TOUR", "in_language", "ENGLISH" ], [ "ON TOUR", "release_year", "2010" ], [ "ROOM IN ROME", "in_language", "ENGLISH" ], [ "ROOM IN ROME", "release_year", "2010" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2010" ], [ "THE NEW WORLD", "in_language", "ENGLISH" ], [ "THE NEW WORLD", "release_year", "2005" ], [ "THE WOLFMAN", "in_language", "ENGLISH" ], [ "THE WOLFMAN", "release_year", "2010" ], [ "THESE GIRLS", "in_language", "ENGLISH" ], [ "THESE GIRLS", "release_year", "2005" ], [ "YOU WILL MEET A TALL DARK STRANGER", "in_language", "ENGLISH" ], [ "YOU WILL MEET A TALL DARK STRANGER", "release_year", "2010" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 27261, 2009 29424, 2011 36438, COMMAND PERFORMANCE 38780, DETENTION 36402, DIRECT CONTACT 31470, DOLPH LUNDGREN 24563, FULL BODY MASSAGE 21083, NOTHING PERSONAL 5538, QUEEN TO PLAY 7240, THE GIRL WITH THE DRAGON TATTOO 15562, THE ROAD src, edge_attr, dst 36438, directed_by, 31470 36438, release_year, 27261 36438, starred_actors, 31470 36438, written_by, 31470 38780, release_year, 29424 38780, starred_actors, 31470 36402, release_year, 27261 36402, starred_actors, 31470 24563, release_year, 3702 21083, release_year, 3702 21083, release_year, 27261 5538, release_year, 27261 7240, release_year, 27261 7240, release_year, 29424 15562, release_year, 27261 15562, release_year, 29424 Question: In what context are DETENTION, FULL BODY MASSAGE, and QUEEN TO PLAY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DETENTION", "FULL BODY MASSAGE", "QUEEN TO PLAY" ], "valid_edges": [ [ "COMMAND PERFORMANCE", "directed_by", "DOLPH LUNDGREN" ], [ "COMMAND PERFORMANCE", "release_year", "2009" ], [ "COMMAND PERFORMANCE", "starred_actors", "DOLPH LUNDGREN" ], [ "COMMAND PERFORMANCE", "written_by", "DOLPH LUNDGREN" ], [ "DETENTION", "release_year", "2011" ], [ "DETENTION", "starred_actors", "DOLPH LUNDGREN" ], [ "DIRECT CONTACT", "release_year", "2009" ], [ "DIRECT CONTACT", "starred_actors", "DOLPH LUNDGREN" ], [ "FULL BODY MASSAGE", "release_year", "1995" ], [ "NOTHING PERSONAL", "release_year", "1995" ], [ "NOTHING PERSONAL", "release_year", "2009" ], [ "QUEEN TO PLAY", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2011" ], [ "THE ROAD", "release_year", "2009" ], [ "THE ROAD", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 3702, 1995 18899, A BUCKET OF BLOOD 30407, ALIEN 9493, ALLEN PAYNE 10045, BD-R 19826, BLACK DEATH 26014, BLOOD OF THE VAMPIRE 32620, BUBBA HO-TEP 13138, CANNIBALISM 37126, CASTLE FREAK 37912, CAT PEOPLE 38158, DAVID HILLENBRAND 4381, DEAD OF NIGHT 27143, DEMENTIA 13 8381, DETOUR 23807, DOCTOR X 3154, DONOVAN'S BRAIN 34827, DR. JEKYLL AND MR. HYDE 36920, DRACULA HAS RISEN FROM THE GRAVE 37707, DRACULA'S DAUGHTER 24825, EVOLVER 29503, EYE OF THE DEVIL 24540, EYES WITHOUT A FACE 4653, FAY WRAY 32144, FRANKENSTEIN MUST BE DESTROYED 5291, FREAKS 38609, GALAXY OF TERROR 12378, HANDS OF THE RIPPER 13990, HIDEAWAY 39972, HOLLOW MAN 5870, HORROR 22421, HORROR EXPRESS 10955, HOUSE OF USHER 9686, HOUSE OF WAX 33663, ICE CREAM MAN 33269, ISLAND OF LOST SOULS 35018, KING COBRA 30645, LIONEL ATWILL 33627, LORD OF ILLUSIONS 40127, MACABRE 17728, MAD LOVE 26370, MADHOUSE 25643, MARK OF THE VAMPIRE 3129, MAXIMUM OVERDRIVE 13889, MICHAEL CURTIZ 18744, MURDERS IN THE RUE MORGUE 16462, MYSTERY OF THE WAX MUSEUM 17189, NIGHT OF THE DEMONS 9330, NIGHT OF THE LEPUS 32988, NIGHT OF THE LIVING DEAD 32891, NOSFERATU 19017, PEEPING TOM 16004, PLANET TERROR 13060, RAVENOUS 5897, REPULSION 7531, SPECIES 8436, SPIRITS OF THE DEAD 32367, STAGE FRIGHT 39265, STORAGE 24 34349, SVENGALI 4938, TALES FROM THE HOOD 14072, THE ABOMINABLE DR. PHIBES 12781, THE ALLIGATOR PEOPLE 13151, THE BAD SEED 17361, THE BRAIN THAT WOULDN'T DIE 25829, THE CABINET OF DR. CALIGARI 31239, THE CAT AND THE CANARY 38676, THE CREEPING FLESH 24990, THE CURSE OF FRANKENSTEIN 38265, THE DEVIL-DOLL 32732, THE DOCTOR AND THE DEVILS 23327, THE FEARLESS VAMPIRE KILLERS 28048, THE GHOST BREAKERS 10613, THE GHOST OF FRANKENSTEIN 14113, THE GHOUL 14382, THE GORGON 25175, THE HAUNTED PALACE 11787, THE HAUNTING 31283, THE HOUND OF THE BASKERVILLES 22212, THE HOUSE THAT DRIPPED BLOOD 32595, THE HOWLING 15198, THE HUNCHBACK OF NOTRE DAME 29358, THE HUNGER 27780, THE INNOCENTS 34005, THE INVISIBLE MAN 8623, THE LEGEND OF HELL HOUSE 33794, THE LITTLE SHOP OF HORRORS 29109, THE LODGER 26566, THE MANGLER 11243, THE MASQUE OF THE RED DEATH 12785, THE MONSTER WALKS 26820, THE MUMMY 27182, THE NATURE OF THE BEAST 9420, THE OLD DARK HOUSE 8727, THE PICTURE OF DORIAN GRAY 1565, THE PLAGUE OF THE ZOMBIES 22294, THE PROPHECY 18162, THE RAVEN 10186, THE REVENGE OF FRANKENSTEIN 1143, THE SEVENTH VICTIM 23847, THE STEPFORD WIVES 23260, THE SWARM 33991, THE TERROR 19823, THE UNKNOWN 39200, THE VAMPIRE BAT 13780, THE WALKING DEAD 22751, THE WICKER MAN 6833, THE WITCHES 3594, THEATRE OF BLOOD 14444, THEM! 1596, TORTURE GARDEN 29370, TROG 31252, V/H/S 11907, VAMPIRE IN BROOKLYN 38370, VAMPYR 36374, VILLAGE OF THE DAMNED 28352, WHITE ZOMBIE 6037, WITCHFINDER GENERAL src, edge_attr, dst 18899, has_genre, 5870 18899, has_tags, 10045 18899, release_year, 3702 30407, has_genre, 5870 30407, has_tags, 5870 19826, has_genre, 5870 19826, has_tags, 10045 26014, has_genre, 5870 26014, has_tags, 10045 32620, has_tags, 10045 32620, has_tags, 5870 37126, has_genre, 5870 37126, release_year, 3702 37912, has_genre, 5870 37912, has_tags, 10045 4381, has_genre, 5870 4381, has_tags, 10045 27143, has_genre, 5870 27143, has_tags, 10045 8381, has_genre, 5870 8381, has_tags, 10045 23807, directed_by, 13889 23807, has_genre, 5870 23807, has_tags, 10045 23807, has_tags, 13138 23807, has_tags, 4653 23807, release_year, 1892 23807, starred_actors, 4653 23807, starred_actors, 30645 3154, has_genre, 5870 3154, has_tags, 10045 34827, has_genre, 5870 34827, has_tags, 10045 36920, has_genre, 5870 36920, has_tags, 10045 37707, has_genre, 5870 37707, has_tags, 10045 24825, has_genre, 5870 24825, release_year, 3702 29503, has_genre, 5870 29503, has_tags, 10045 24540, has_genre, 5870 24540, has_tags, 10045 32144, has_genre, 5870 32144, has_tags, 10045 5291, has_genre, 5870 5291, release_year, 1892 38609, has_genre, 5870 38609, has_tags, 10045 12378, has_genre, 5870 12378, has_tags, 10045 13990, has_genre, 5870 13990, release_year, 3702 39972, has_tags, 10045 39972, has_tags, 5870 22421, has_genre, 5870 22421, has_tags, 10045 10955, has_genre, 5870 10955, has_tags, 10045 10955, has_tags, 5870 9686, has_genre, 5870 9686, has_tags, 10045 33663, has_genre, 5870 33663, release_year, 3702 33269, has_genre, 5870 33269, release_year, 1892 35018, directed_by, 38158 35018, has_genre, 5870 35018, written_by, 38158 33627, has_genre, 5870 33627, release_year, 3702 40127, has_genre, 5870 40127, has_tags, 10045 17728, has_genre, 5870 17728, has_tags, 10045 17728, release_year, 3702 26370, has_genre, 5870 26370, has_tags, 10045 25643, has_genre, 5870 25643, has_tags, 10045 25643, starred_actors, 30645 3129, has_genre, 5870 3129, has_tags, 10045 18744, has_genre, 5870 18744, release_year, 1892 16462, directed_by, 13889 16462, has_genre, 5870 16462, has_tags, 10045 16462, has_tags, 4653 16462, has_tags, 13889 16462, starred_actors, 4653 16462, starred_actors, 30645 17189, has_genre, 5870 17189, has_tags, 10045 9330, has_genre, 5870 9330, has_tags, 10045 32988, has_genre, 5870 32988, has_tags, 10045 32988, has_tags, 5870 32891, has_genre, 5870 32891, has_tags, 10045 19017, has_genre, 5870 19017, has_tags, 10045 16004, has_genre, 5870 16004, has_tags, 10045 16004, has_tags, 5870 13060, has_genre, 5870 13060, has_tags, 13138 5897, has_genre, 5870 5897, has_tags, 10045 7531, has_genre, 5870 7531, has_tags, 30407 7531, release_year, 3702 8436, has_genre, 5870 8436, has_tags, 10045 32367, has_genre, 5870 32367, has_tags, 10045 39265, has_genre, 5870 39265, has_tags, 10045 34349, has_genre, 5870 34349, has_tags, 10045 4938, has_genre, 5870 4938, release_year, 3702 14072, has_genre, 5870 14072, has_tags, 10045 14072, has_tags, 5870 12781, has_genre, 5870 12781, has_tags, 10045 13151, has_genre, 5870 13151, has_tags, 10045 17361, has_genre, 5870 17361, has_tags, 10045 25829, has_genre, 5870 25829, has_tags, 10045 31239, has_genre, 5870 31239, has_tags, 10045 38676, has_genre, 5870 38676, has_tags, 10045 24990, has_genre, 5870 24990, has_tags, 10045 24990, has_tags, 5870 38265, has_genre, 5870 38265, has_tags, 10045 32732, has_genre, 5870 32732, has_tags, 10045 23327, has_genre, 5870 23327, has_tags, 10045 28048, has_genre, 5870 28048, has_tags, 10045 10613, has_genre, 5870 10613, starred_actors, 30645 14113, has_genre, 5870 14113, has_tags, 10045 14382, has_genre, 5870 14382, has_tags, 10045 25175, has_genre, 5870 25175, has_tags, 10045 11787, has_genre, 5870 11787, has_tags, 10045 11787, has_tags, 5870 31283, has_genre, 5870 31283, has_tags, 10045 22212, has_genre, 5870 22212, has_tags, 10045 32595, has_genre, 5870 32595, has_tags, 10045 15198, has_genre, 5870 15198, has_tags, 10045 29358, has_genre, 5870 29358, has_tags, 10045 27780, has_genre, 5870 27780, has_tags, 10045 34005, has_genre, 5870 34005, has_tags, 10045 8623, has_genre, 5870 8623, has_tags, 10045 33794, has_genre, 5870 33794, has_tags, 10045 29109, has_genre, 5870 29109, has_tags, 10045 26566, has_genre, 5870 26566, has_tags, 5870 26566, release_year, 3702 11243, has_genre, 5870 11243, has_tags, 10045 12785, has_genre, 5870 12785, release_year, 1892 26820, has_genre, 5870 26820, has_tags, 10045 26820, has_tags, 5870 26820, release_year, 1892 27182, has_genre, 5870 27182, release_year, 3702 9420, has_genre, 5870 9420, release_year, 1892 8727, has_genre, 5870 8727, has_tags, 10045 1565, has_genre, 5870 1565, has_tags, 10045 22294, has_genre, 5870 22294, release_year, 3702 18162, has_genre, 5870 18162, has_tags, 10045 18162, has_tags, 5870 10186, has_genre, 5870 10186, has_tags, 10045 1143, has_genre, 5870 1143, has_tags, 10045 23847, has_genre, 5870 23847, has_tags, 10045 23260, has_genre, 5870 23260, has_tags, 10045 33991, has_genre, 5870 33991, has_tags, 10045 19823, has_genre, 5870 19823, has_tags, 10045 39200, has_genre, 5870 39200, has_tags, 4653 39200, starred_actors, 4653 39200, starred_actors, 30645 13780, directed_by, 13889 13780, has_genre, 5870 13780, release_year, 3702 13780, starred_actors, 9493 22751, has_genre, 5870 22751, has_tags, 10045 6833, has_genre, 5870 6833, has_tags, 10045 3594, has_genre, 5870 3594, has_tags, 10045 14444, has_genre, 5870 14444, has_tags, 10045 14444, has_tags, 5870 1596, has_genre, 5870 1596, has_tags, 10045 29370, has_genre, 5870 29370, has_tags, 10045 31252, has_genre, 5870 31252, has_tags, 10045 31252, has_tags, 5870 11907, has_genre, 5870 11907, release_year, 3702 11907, starred_actors, 9493 38370, has_genre, 5870 38370, release_year, 1892 36374, has_genre, 5870 36374, has_tags, 10045 36374, release_year, 3702 28352, has_genre, 5870 28352, has_tags, 10045 28352, release_year, 1892 6037, has_genre, 5870 6037, has_tags, 10045 Question: For what reason are 1995, DAVID HILLENBRAND, and DOCTOR X associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1995", "DAVID HILLENBRAND", "DOCTOR X" ], "valid_edges": [ [ "A BUCKET OF BLOOD", "has_genre", "HORROR" ], [ "A BUCKET OF BLOOD", "has_tags", "BD-R" ], [ "A BUCKET OF BLOOD", "release_year", "1995" ], [ "ALIEN", "has_genre", "HORROR" ], [ "ALIEN", "has_tags", "HORROR" ], [ "BLACK DEATH", "has_genre", "HORROR" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BLOOD OF THE VAMPIRE", "has_genre", "HORROR" ], [ "BLOOD OF THE VAMPIRE", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "BD-R" ], [ "BUBBA HO-TEP", "has_tags", "HORROR" ], [ "CASTLE FREAK", "has_genre", "HORROR" ], [ "CASTLE FREAK", "release_year", "1995" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "has_tags", "BD-R" ], [ "DEAD OF NIGHT", "has_genre", "HORROR" ], [ "DEAD OF NIGHT", "has_tags", "BD-R" ], [ "DEMENTIA 13", "has_genre", "HORROR" ], [ "DEMENTIA 13", "has_tags", "BD-R" ], [ "DETOUR", "has_genre", "HORROR" ], [ "DETOUR", "has_tags", "BD-R" ], [ "DOCTOR X", "directed_by", "MICHAEL CURTIZ" ], [ "DOCTOR X", "has_genre", "HORROR" ], [ "DOCTOR X", "has_tags", "BD-R" ], [ "DOCTOR X", "has_tags", "CANNIBALISM" ], [ "DOCTOR X", "has_tags", "FAY WRAY" ], [ "DOCTOR X", "release_year", "1932" ], [ "DOCTOR X", "starred_actors", "FAY WRAY" ], [ "DOCTOR X", "starred_actors", "LIONEL ATWILL" ], [ "DONOVAN'S BRAIN", "has_genre", "HORROR" ], [ "DONOVAN'S BRAIN", "has_tags", "BD-R" ], [ "DR. JEKYLL AND MR. HYDE", "has_genre", "HORROR" ], [ "DR. JEKYLL AND MR. HYDE", "has_tags", "BD-R" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_genre", "HORROR" ], [ "DRACULA HAS RISEN FROM THE GRAVE", "has_tags", "BD-R" ], [ "DRACULA'S DAUGHTER", "has_genre", "HORROR" ], [ "DRACULA'S DAUGHTER", "has_tags", "BD-R" ], [ "EVOLVER", "has_genre", "HORROR" ], [ "EVOLVER", "release_year", "1995" ], [ "EYE OF THE DEVIL", "has_genre", "HORROR" ], [ "EYE OF THE DEVIL", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_genre", "HORROR" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_genre", "HORROR" ], [ "FRANKENSTEIN MUST BE DESTROYED", "has_tags", "BD-R" ], [ "FREAKS", "has_genre", "HORROR" ], [ "FREAKS", "release_year", "1932" ], [ "GALAXY OF TERROR", "has_genre", "HORROR" ], [ "GALAXY OF TERROR", "has_tags", "BD-R" ], [ "HANDS OF THE RIPPER", "has_genre", "HORROR" ], [ "HANDS OF THE RIPPER", "has_tags", "BD-R" ], [ "HIDEAWAY", "has_genre", "HORROR" ], [ "HIDEAWAY", "release_year", "1995" ], [ "HOLLOW MAN", "has_tags", "BD-R" ], [ "HOLLOW MAN", "has_tags", "HORROR" ], [ "HORROR EXPRESS", "has_genre", "HORROR" ], [ "HORROR EXPRESS", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_genre", "HORROR" ], [ "HOUSE OF USHER", "has_tags", "BD-R" ], [ "HOUSE OF USHER", "has_tags", "HORROR" ], [ "HOUSE OF WAX", "has_genre", "HORROR" ], [ "HOUSE OF WAX", "has_tags", "BD-R" ], [ "ICE CREAM MAN", "has_genre", "HORROR" ], [ "ICE CREAM MAN", "release_year", "1995" ], [ "ISLAND OF LOST SOULS", "has_genre", "HORROR" ], [ "ISLAND OF LOST SOULS", "release_year", "1932" ], [ "KING COBRA", "directed_by", "DAVID HILLENBRAND" ], [ "KING COBRA", "has_genre", "HORROR" ], [ "KING COBRA", "written_by", "DAVID HILLENBRAND" ], [ "LORD OF ILLUSIONS", "has_genre", "HORROR" ], [ "LORD OF ILLUSIONS", "release_year", "1995" ], [ "MACABRE", "has_genre", "HORROR" ], [ "MACABRE", "has_tags", "BD-R" ], [ "MAD LOVE", "has_genre", "HORROR" ], [ "MAD LOVE", "has_tags", "BD-R" ], [ "MAD LOVE", "release_year", "1995" ], [ "MADHOUSE", "has_genre", "HORROR" ], [ "MADHOUSE", "has_tags", "BD-R" ], [ "MARK OF THE VAMPIRE", "has_genre", "HORROR" ], [ "MARK OF THE VAMPIRE", "has_tags", "BD-R" ], [ "MARK OF THE VAMPIRE", "starred_actors", "LIONEL ATWILL" ], [ "MAXIMUM OVERDRIVE", "has_genre", "HORROR" ], [ "MAXIMUM OVERDRIVE", "has_tags", "BD-R" ], [ "MURDERS IN THE RUE MORGUE", "has_genre", "HORROR" ], [ "MURDERS IN THE RUE MORGUE", "release_year", "1932" ], [ "MYSTERY OF THE WAX MUSEUM", "directed_by", "MICHAEL CURTIZ" ], [ "MYSTERY OF THE WAX MUSEUM", "has_genre", "HORROR" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "BD-R" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "FAY WRAY" ], [ "MYSTERY OF THE WAX MUSEUM", "has_tags", "MICHAEL CURTIZ" ], [ "MYSTERY OF THE WAX MUSEUM", "starred_actors", "FAY WRAY" ], [ "MYSTERY OF THE WAX MUSEUM", "starred_actors", "LIONEL ATWILL" ], [ "NIGHT OF THE DEMONS", "has_genre", "HORROR" ], [ "NIGHT OF THE DEMONS", "has_tags", "BD-R" ], [ "NIGHT OF THE LEPUS", "has_genre", "HORROR" ], [ "NIGHT OF THE LEPUS", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "BD-R" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "NOSFERATU", "has_genre", "HORROR" ], [ "NOSFERATU", "has_tags", "BD-R" ], [ "PEEPING TOM", "has_genre", "HORROR" ], [ "PEEPING TOM", "has_tags", "BD-R" ], [ "PLANET TERROR", "has_genre", "HORROR" ], [ "PLANET TERROR", "has_tags", "BD-R" ], [ "PLANET TERROR", "has_tags", "HORROR" ], [ "RAVENOUS", "has_genre", "HORROR" ], [ "RAVENOUS", "has_tags", "CANNIBALISM" ], [ "REPULSION", "has_genre", "HORROR" ], [ "REPULSION", "has_tags", "BD-R" ], [ "SPECIES", "has_genre", "HORROR" ], [ "SPECIES", "has_tags", "ALIEN" ], [ "SPECIES", "release_year", "1995" ], [ "SPIRITS OF THE DEAD", "has_genre", "HORROR" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "STAGE FRIGHT", "has_genre", "HORROR" ], [ "STAGE FRIGHT", "has_tags", "BD-R" ], [ "STORAGE 24", "has_genre", "HORROR" ], [ "STORAGE 24", "has_tags", "BD-R" ], [ "SVENGALI", "has_genre", "HORROR" ], [ "SVENGALI", "has_tags", "BD-R" ], [ "TALES FROM THE HOOD", "has_genre", "HORROR" ], [ "TALES FROM THE HOOD", "release_year", "1995" ], [ "THE ABOMINABLE DR. PHIBES", "has_genre", "HORROR" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "BD-R" ], [ "THE ABOMINABLE DR. PHIBES", "has_tags", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_genre", "HORROR" ], [ "THE ALLIGATOR PEOPLE", "has_tags", "BD-R" ], [ "THE BAD SEED", "has_genre", "HORROR" ], [ "THE BAD SEED", "has_tags", "BD-R" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_tags", "BD-R" ], [ "THE CABINET OF DR. CALIGARI", "has_genre", "HORROR" ], [ "THE CABINET OF DR. CALIGARI", "has_tags", "BD-R" ], [ "THE CAT AND THE CANARY", "has_genre", "HORROR" ], [ "THE CAT AND THE CANARY", "has_tags", "BD-R" ], [ "THE CREEPING FLESH", "has_genre", "HORROR" ], [ "THE CREEPING FLESH", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "HORROR" ], [ "THE DEVIL-DOLL", "has_genre", "HORROR" ], [ "THE DEVIL-DOLL", "has_tags", "BD-R" ], [ "THE DOCTOR AND THE DEVILS", "has_genre", "HORROR" ], [ "THE DOCTOR AND THE DEVILS", "has_tags", "BD-R" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_genre", "HORROR" ], [ "THE FEARLESS VAMPIRE KILLERS", "has_tags", "BD-R" ], [ "THE GHOST BREAKERS", "has_genre", "HORROR" ], [ "THE GHOST BREAKERS", "has_tags", "BD-R" ], [ "THE GHOST OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE GHOST OF FRANKENSTEIN", "starred_actors", "LIONEL ATWILL" ], [ "THE GHOUL", "has_genre", "HORROR" ], [ "THE GHOUL", "has_tags", "BD-R" ], [ "THE GORGON", "has_genre", "HORROR" ], [ "THE GORGON", "has_tags", "BD-R" ], [ "THE HAUNTED PALACE", "has_genre", "HORROR" ], [ "THE HAUNTED PALACE", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_genre", "HORROR" ], [ "THE HAUNTING", "has_tags", "BD-R" ], [ "THE HAUNTING", "has_tags", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "HORROR" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "BD-R" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_genre", "HORROR" ], [ "THE HOUSE THAT DRIPPED BLOOD", "has_tags", "BD-R" ], [ "THE HOWLING", "has_genre", "HORROR" ], [ "THE HOWLING", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "HORROR" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNGER", "has_genre", "HORROR" ], [ "THE HUNGER", "has_tags", "BD-R" ], [ "THE INNOCENTS", "has_genre", "HORROR" ], [ "THE INNOCENTS", "has_tags", "BD-R" ], [ "THE INVISIBLE MAN", "has_genre", "HORROR" ], [ "THE INVISIBLE MAN", "has_tags", "BD-R" ], [ "THE LEGEND OF HELL HOUSE", "has_genre", "HORROR" ], [ "THE LEGEND OF HELL HOUSE", "has_tags", "BD-R" ], [ "THE LITTLE SHOP OF HORRORS", "has_genre", "HORROR" ], [ "THE LITTLE SHOP OF HORRORS", "has_tags", "BD-R" ], [ "THE LODGER", "has_genre", "HORROR" ], [ "THE LODGER", "has_tags", "BD-R" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "release_year", "1995" ], [ "THE MASQUE OF THE RED DEATH", "has_genre", "HORROR" ], [ "THE MASQUE OF THE RED DEATH", "has_tags", "BD-R" ], [ "THE MONSTER WALKS", "has_genre", "HORROR" ], [ "THE MONSTER WALKS", "release_year", "1932" ], [ "THE MUMMY", "has_genre", "HORROR" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE MUMMY", "has_tags", "HORROR" ], [ "THE MUMMY", "release_year", "1932" ], [ "THE NATURE OF THE BEAST", "has_genre", "HORROR" ], [ "THE NATURE OF THE BEAST", "release_year", "1995" ], [ "THE OLD DARK HOUSE", "has_genre", "HORROR" ], [ "THE OLD DARK HOUSE", "release_year", "1932" ], [ "THE PICTURE OF DORIAN GRAY", "has_genre", "HORROR" ], [ "THE PICTURE OF DORIAN GRAY", "has_tags", "BD-R" ], [ "THE PLAGUE OF THE ZOMBIES", "has_genre", "HORROR" ], [ "THE PLAGUE OF THE ZOMBIES", "has_tags", "BD-R" ], [ "THE PROPHECY", "has_genre", "HORROR" ], [ "THE PROPHECY", "release_year", "1995" ], [ "THE RAVEN", "has_genre", "HORROR" ], [ "THE RAVEN", "has_tags", "BD-R" ], [ "THE RAVEN", "has_tags", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_genre", "HORROR" ], [ "THE REVENGE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE SEVENTH VICTIM", "has_genre", "HORROR" ], [ "THE SEVENTH VICTIM", "has_tags", "BD-R" ], [ "THE STEPFORD WIVES", "has_genre", "HORROR" ], [ "THE STEPFORD WIVES", "has_tags", "BD-R" ], [ "THE SWARM", "has_genre", "HORROR" ], [ "THE SWARM", "has_tags", "BD-R" ], [ "THE TERROR", "has_genre", "HORROR" ], [ "THE TERROR", "has_tags", "BD-R" ], [ "THE UNKNOWN", "has_genre", "HORROR" ], [ "THE UNKNOWN", "has_tags", "BD-R" ], [ "THE VAMPIRE BAT", "has_genre", "HORROR" ], [ "THE VAMPIRE BAT", "has_tags", "FAY WRAY" ], [ "THE VAMPIRE BAT", "starred_actors", "FAY WRAY" ], [ "THE VAMPIRE BAT", "starred_actors", "LIONEL ATWILL" ], [ "THE WALKING DEAD", "directed_by", "MICHAEL CURTIZ" ], [ "THE WALKING DEAD", "has_genre", "HORROR" ], [ "THE WALKING DEAD", "release_year", "1995" ], [ "THE WALKING DEAD", "starred_actors", "ALLEN PAYNE" ], [ "THE WICKER MAN", "has_genre", "HORROR" ], [ "THE WICKER MAN", "has_tags", "BD-R" ], [ "THE WITCHES", "has_genre", "HORROR" ], [ "THE WITCHES", "has_tags", "BD-R" ], [ "THEATRE OF BLOOD", "has_genre", "HORROR" ], [ "THEATRE OF BLOOD", "has_tags", "BD-R" ], [ "THEM!", "has_genre", "HORROR" ], [ "THEM!", "has_tags", "BD-R" ], [ "THEM!", "has_tags", "HORROR" ], [ "TORTURE GARDEN", "has_genre", "HORROR" ], [ "TORTURE GARDEN", "has_tags", "BD-R" ], [ "TROG", "has_genre", "HORROR" ], [ "TROG", "has_tags", "BD-R" ], [ "V/H/S", "has_genre", "HORROR" ], [ "V/H/S", "has_tags", "BD-R" ], [ "V/H/S", "has_tags", "HORROR" ], [ "VAMPIRE IN BROOKLYN", "has_genre", "HORROR" ], [ "VAMPIRE IN BROOKLYN", "release_year", "1995" ], [ "VAMPIRE IN BROOKLYN", "starred_actors", "ALLEN PAYNE" ], [ "VAMPYR", "has_genre", "HORROR" ], [ "VAMPYR", "release_year", "1932" ], [ "VILLAGE OF THE DAMNED", "has_genre", "HORROR" ], [ "VILLAGE OF THE DAMNED", "has_tags", "BD-R" ], [ "VILLAGE OF THE DAMNED", "release_year", "1995" ], [ "WHITE ZOMBIE", "has_genre", "HORROR" ], [ "WHITE ZOMBIE", "has_tags", "BD-R" ], [ "WHITE ZOMBIE", "release_year", "1932" ], [ "WITCHFINDER GENERAL", "has_genre", "HORROR" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36646, HE GOT GAME 6315, RAY ALLEN 32404, SPORT 3049, SPORTS 32526, THE BLIND SIDE 35135, THE LAST AMERICAN HERO 32080, TIM MCGRAW 2955, TOM WOLFE src, edge_attr, dst 36646, has_genre, 32404 36646, has_tags, 3049 36646, starred_actors, 6315 32526, has_genre, 32404 32526, has_tags, 3049 32526, has_tags, 32080 32526, starred_actors, 32080 35135, has_genre, 32404 35135, written_by, 2955 Question: In what context are RAY ALLEN, TIM MCGRAW, and TOM WOLFE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "RAY ALLEN", "TIM MCGRAW", "TOM WOLFE" ], "valid_edges": [ [ "HE GOT GAME", "has_genre", "SPORT" ], [ "HE GOT GAME", "has_tags", "SPORTS" ], [ "HE GOT GAME", "starred_actors", "RAY ALLEN" ], [ "THE BLIND SIDE", "has_genre", "SPORT" ], [ "THE BLIND SIDE", "has_tags", "SPORTS" ], [ "THE BLIND SIDE", "has_tags", "TIM MCGRAW" ], [ "THE BLIND SIDE", "starred_actors", "TIM MCGRAW" ], [ "THE LAST AMERICAN HERO", "has_genre", "SPORT" ], [ "THE LAST AMERICAN HERO", "written_by", "TOM WOLFE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 23696, ETERNAL SUNSHINE OF THE SPOTLESS MIND 9621, HAWAII, OSLO 12112, LINDSAY LOHAN 19791, MEAN GIRLS 38298, NONLINEAR 31625, TROND ESPEN SEIM src, edge_attr, dst 10272, has_tags, 12112 10272, release_year, 37484 10272, starred_actors, 12112 23696, has_tags, 38298 23696, release_year, 37484 9621, release_year, 37484 9621, starred_actors, 31625 19791, has_tags, 12112 19791, release_year, 37484 19791, starred_actors, 12112 Question: For what reason are LINDSAY LOHAN, NONLINEAR, and TROND ESPEN SEIM associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LINDSAY LOHAN", "NONLINEAR", "TROND ESPEN SEIM" ], "valid_edges": [ [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "LINDSAY LOHAN" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "release_year", "2004" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "starred_actors", "LINDSAY LOHAN" ], [ "ETERNAL SUNSHINE OF THE SPOTLESS MIND", "has_tags", "NONLINEAR" ], [ "ETERNAL SUNSHINE OF THE SPOTLESS MIND", "release_year", "2004" ], [ "HAWAII, OSLO", "release_year", "2004" ], [ "HAWAII, OSLO", "starred_actors", "TROND ESPEN SEIM" ], [ "MEAN GIRLS", "has_tags", "LINDSAY LOHAN" ], [ "MEAN GIRLS", "release_year", "2004" ], [ "MEAN GIRLS", "starred_actors", "LINDSAY LOHAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 40094, 1930S 6776, 2000 20719, A TIME FOR DRUNKEN HORSES 21413, AMARCORD 32815, BLACKBOARDS 9778, GLADIATOR 16200, ITALIAN 17279, KIPPUR 13725, KURDISH 37499, PARAGRAPH 175 8504, PRIMO LEVI 6759, RULES OF ENGAGEMENT 12691, THE PATRIOT 37529, THE TRUCE 3934, TIGERLAND 23247, TRIAGE 29947, TURTLES CAN FLY 37253, U-571 22214, WAR src, edge_attr, dst 20719, has_genre, 22214 20719, in_language, 13725 20719, release_year, 6776 21413, has_tags, 40094 21413, in_language, 16200 32815, has_genre, 22214 32815, in_language, 13725 32815, release_year, 6776 9778, has_tags, 22214 9778, release_year, 6776 17279, has_genre, 22214 17279, release_year, 6776 37499, has_genre, 22214 37499, release_year, 6776 6759, has_genre, 22214 6759, release_year, 6776 12691, has_tags, 22214 12691, release_year, 6776 37529, has_genre, 22214 37529, in_language, 16200 37529, written_by, 8504 3934, has_genre, 22214 3934, release_year, 6776 23247, has_genre, 22214 23247, in_language, 13725 29947, has_genre, 22214 29947, in_language, 13725 37253, has_genre, 22214 37253, has_tags, 22214 37253, release_year, 6776 Question: For what reason are 1930S, BLACKBOARDS, and PRIMO LEVI associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1930S", "BLACKBOARDS", "PRIMO LEVI" ], "valid_edges": [ [ "A TIME FOR DRUNKEN HORSES", "has_genre", "WAR" ], [ "A TIME FOR DRUNKEN HORSES", "in_language", "KURDISH" ], [ "A TIME FOR DRUNKEN HORSES", "release_year", "2000" ], [ "AMARCORD", "has_tags", "1930S" ], [ "AMARCORD", "in_language", "ITALIAN" ], [ "BLACKBOARDS", "has_genre", "WAR" ], [ "BLACKBOARDS", "in_language", "KURDISH" ], [ "BLACKBOARDS", "release_year", "2000" ], [ "GLADIATOR", "has_tags", "WAR" ], [ "GLADIATOR", "release_year", "2000" ], [ "KIPPUR", "has_genre", "WAR" ], [ "KIPPUR", "release_year", "2000" ], [ "PARAGRAPH 175", "has_genre", "WAR" ], [ "PARAGRAPH 175", "release_year", "2000" ], [ "RULES OF ENGAGEMENT", "has_genre", "WAR" ], [ "RULES OF ENGAGEMENT", "release_year", "2000" ], [ "THE PATRIOT", "has_tags", "WAR" ], [ "THE PATRIOT", "release_year", "2000" ], [ "THE TRUCE", "has_genre", "WAR" ], [ "THE TRUCE", "in_language", "ITALIAN" ], [ "THE TRUCE", "written_by", "PRIMO LEVI" ], [ "TIGERLAND", "has_genre", "WAR" ], [ "TIGERLAND", "release_year", "2000" ], [ "TRIAGE", "has_genre", "WAR" ], [ "TRIAGE", "in_language", "KURDISH" ], [ "TURTLES CAN FLY", "has_genre", "WAR" ], [ "TURTLES CAN FLY", "in_language", "KURDISH" ], [ "U-571", "has_genre", "WAR" ], [ "U-571", "has_tags", "WAR" ], [ "U-571", "release_year", "2000" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10757, EDDIE 33902, FOOL FOR LOVE 18907, IMAGES 33184, RANDY QUAID 29049, ROBERT ALTMAN 35362, THE MAGICAL LEGEND OF THE LEPRECHAUNS 37332, WHOOPI GOLDBERG src, edge_attr, dst 10757, starred_actors, 37332 33902, directed_by, 29049 33902, starred_actors, 33184 18907, directed_by, 29049 18907, has_tags, 29049 18907, written_by, 29049 35362, starred_actors, 33184 35362, starred_actors, 37332 Question: In what context are EDDIE, FOOL FOR LOVE, and IMAGES connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EDDIE", "FOOL FOR LOVE", "IMAGES" ], "valid_edges": [ [ "EDDIE", "starred_actors", "WHOOPI GOLDBERG" ], [ "FOOL FOR LOVE", "directed_by", "ROBERT ALTMAN" ], [ "FOOL FOR LOVE", "starred_actors", "RANDY QUAID" ], [ "IMAGES", "directed_by", "ROBERT ALTMAN" ], [ "IMAGES", "has_tags", "ROBERT ALTMAN" ], [ "IMAGES", "written_by", "ROBERT ALTMAN" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "RANDY QUAID" ], [ "THE MAGICAL LEGEND OF THE LEPRECHAUNS", "starred_actors", "WHOOPI GOLDBERG" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 3417, COPPOLA 14724, CRIME 36645, JON COHEN 3487, MINORITY REPORT 10956, REAL WOMEN HAVE CURVES 35551, THE GODFATHER src, edge_attr, dst 3487, has_tags, 14724 3487, release_year, 35935 3487, written_by, 36645 10956, release_year, 35935 35551, has_genre, 14724 35551, has_tags, 3417 35551, has_tags, 14724 Question: How are COPPOLA, JON COHEN, and REAL WOMEN HAVE CURVES related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "COPPOLA", "JON COHEN", "REAL WOMEN HAVE CURVES" ], "valid_edges": [ [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "release_year", "2002" ], [ "MINORITY REPORT", "written_by", "JON COHEN" ], [ "REAL WOMEN HAVE CURVES", "release_year", "2002" ], [ "THE GODFATHER", "has_genre", "CRIME" ], [ "THE GODFATHER", "has_tags", "COPPOLA" ], [ "THE GODFATHER", "has_tags", "CRIME" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 6718, A FAREWELL TO ARMS 34734, BATTLE OF THE BULGE 34812, BECKY SHARP 40074, BLACK BOOK 867, BREAKING AND ENTERING 11929, CASABLANCA 25285, COME AND SEE 30463, COMEDY 10293, CONSPIRACY 30624, DANCES WITH WOLVES 24410, DEMONLOVER 30123, DORIAN GRAY 36212, DRAMA 31008, DUTCH 31783, ENGLISH 8294, FIVE FINGERS 1273, FLYBOYS 13834, FLYING TIGERS 39145, FURY 15765, HAMSUN 24370, HOWARD TEICHMANN 15343, IN DARKNESS 30910, LONELYHEARTS 22260, MEMORY 28910, MICHAEL CRICHTON 38294, MRS. MINIVER 26892, NAZIS 25264, NOTES ON A SCANDAL 39852, PAN'S LABYRINTH 24369, QUINCEAÑERA 35586, SAHARA 11124, STALINGRAD 27210, THE BEST YEARS OF OUR LIVES 36692, THE CAINE MUTINY 19883, THE CHATTERLEY AFFAIR 25509, THE DEBT 36390, THE ENGLISH PATIENT 6424, THE GREAT ESCAPE 28107, THE LAST KISS 12614, THE PIANIST 28919, THE RETURN 21548, THE SUN 2783, THE WIND THAT SHAKES THE BARLEY 36313, THERE BE DRAGONS 24811, THRILLER 30585, TWISTER 22214, WAR 24155, WORLD WAR II 15904, YANKS 16849, ZERO DARK THIRTY src, edge_attr, dst 6718, has_genre, 22214 6718, in_language, 31783 34734, has_genre, 22214 34734, has_tags, 24155 34812, has_genre, 22214 34812, in_language, 31783 40074, has_genre, 24811 40074, has_genre, 22214 40074, has_tags, 26892 40074, has_tags, 24155 40074, in_language, 31008 40074, in_language, 31783 40074, release_year, 35845 867, in_language, 31783 867, release_year, 35845 11929, has_genre, 22214 11929, has_tags, 26892 11929, has_tags, 22214 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 30624, has_tags, 22214 30624, in_language, 31783 24410, has_genre, 24811 24410, in_language, 31783 30123, has_genre, 24811 30123, in_language, 31783 31008, has_genre, 30463 31008, has_genre, 36212 8294, has_genre, 24811 8294, release_year, 35845 1273, has_tags, 22214 1273, release_year, 35845 13834, has_genre, 22214 13834, has_tags, 24155 39145, has_genre, 22214 39145, has_tags, 22214 39145, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 15765, in_language, 31783 15343, has_genre, 22214 15343, has_tags, 22214 15343, has_tags, 24155 30910, has_genre, 36212 30910, written_by, 24370 22260, has_genre, 24811 22260, release_year, 35845 38294, has_genre, 22214 38294, has_tags, 24155 25264, has_genre, 24811 25264, release_year, 35845 39852, has_genre, 22214 39852, has_tags, 22214 39852, release_year, 35845 24369, in_language, 31783 24369, release_year, 35845 35586, has_genre, 22214 35586, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 27210, has_genre, 22214 27210, has_tags, 24155 36692, has_genre, 22214 36692, has_tags, 24155 19883, in_language, 31783 19883, release_year, 35845 25509, has_genre, 24811 25509, in_language, 31783 36390, has_genre, 22214 36390, has_tags, 22214 36390, in_language, 31783 6424, has_tags, 22214 6424, has_tags, 24155 28107, in_language, 31783 28107, release_year, 35845 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 28919, has_genre, 24811 28919, release_year, 35845 21548, has_tags, 22214 21548, has_tags, 24155 2783, has_genre, 22214 2783, in_language, 31783 2783, release_year, 35845 36313, has_genre, 22214 36313, in_language, 31783 30585, has_genre, 30463 30585, has_genre, 36212 30585, has_tags, 28910 30585, written_by, 28910 15904, has_genre, 22214 15904, has_tags, 24155 16849, has_genre, 24811 16849, has_tags, 22214 Question: In what context are BLACK BOOK, HOWARD TEICHMANN, and MICHAEL CRICHTON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BLACK BOOK", "HOWARD TEICHMANN", "MICHAEL CRICHTON" ], "valid_edges": [ [ "A FAREWELL TO ARMS", "has_genre", "WAR" ], [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "BATTLE OF THE BULGE", "has_genre", "WAR" ], [ "BATTLE OF THE BULGE", "has_tags", "WORLD WAR II" ], [ "BECKY SHARP", "has_genre", "WAR" ], [ "BECKY SHARP", "in_language", "ENGLISH" ], [ "BLACK BOOK", "has_genre", "THRILLER" ], [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "has_tags", "NAZIS" ], [ "BLACK BOOK", "has_tags", "WORLD WAR II" ], [ "BLACK BOOK", "in_language", "DUTCH" ], [ "BLACK BOOK", "in_language", "ENGLISH" ], [ "BLACK BOOK", "release_year", "2006" ], [ "BREAKING AND ENTERING", "in_language", "ENGLISH" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "CASABLANCA", "has_genre", "WAR" ], [ "CASABLANCA", "has_tags", "NAZIS" ], [ "CASABLANCA", "has_tags", "WAR" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "DANCES WITH WOLVES", "has_tags", "WAR" ], [ "DANCES WITH WOLVES", "in_language", "ENGLISH" ], [ "DEMONLOVER", "has_genre", "THRILLER" ], [ "DEMONLOVER", "in_language", "ENGLISH" ], [ "DORIAN GRAY", "has_genre", "THRILLER" ], [ "DORIAN GRAY", "in_language", "ENGLISH" ], [ "DUTCH", "has_genre", "COMEDY" ], [ "DUTCH", "has_genre", "DRAMA" ], [ "FIVE FINGERS", "has_genre", "THRILLER" ], [ "FIVE FINGERS", "release_year", "2006" ], [ "FLYBOYS", "has_tags", "WAR" ], [ "FLYBOYS", "release_year", "2006" ], [ "FLYING TIGERS", "has_genre", "WAR" ], [ "FLYING TIGERS", "has_tags", "WORLD WAR II" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "in_language", "ENGLISH" ], [ "IN DARKNESS", "has_genre", "WAR" ], [ "IN DARKNESS", "has_tags", "WAR" ], [ "IN DARKNESS", "has_tags", "WORLD WAR II" ], [ "LONELYHEARTS", "has_genre", "DRAMA" ], [ "LONELYHEARTS", "written_by", "HOWARD TEICHMANN" ], [ "MEMORY", "has_genre", "THRILLER" ], [ "MEMORY", "release_year", "2006" ], [ "MRS. MINIVER", "has_genre", "WAR" ], [ "MRS. MINIVER", "has_tags", "WORLD WAR II" ], [ "NOTES ON A SCANDAL", "has_genre", "THRILLER" ], [ "NOTES ON A SCANDAL", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_genre", "WAR" ], [ "PAN'S LABYRINTH", "has_tags", "WAR" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "QUINCEAÑERA", "in_language", "ENGLISH" ], [ "QUINCEAÑERA", "release_year", "2006" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "THE BEST YEARS OF OUR LIVES", "has_genre", "WAR" ], [ "THE BEST YEARS OF OUR LIVES", "has_tags", "WORLD WAR II" ], [ "THE CAINE MUTINY", "has_genre", "WAR" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE CHATTERLEY AFFAIR", "in_language", "ENGLISH" ], [ "THE CHATTERLEY AFFAIR", "release_year", "2006" ], [ "THE DEBT", "has_genre", "THRILLER" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE ENGLISH PATIENT", "has_genre", "WAR" ], [ "THE ENGLISH PATIENT", "has_tags", "WAR" ], [ "THE ENGLISH PATIENT", "in_language", "ENGLISH" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "has_tags", "WORLD WAR II" ], [ "THE LAST KISS", "in_language", "ENGLISH" ], [ "THE LAST KISS", "release_year", "2006" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "THE RETURN", "has_genre", "THRILLER" ], [ "THE RETURN", "release_year", "2006" ], [ "THE SUN", "has_tags", "WAR" ], [ "THE SUN", "has_tags", "WORLD WAR II" ], [ "THE WIND THAT SHAKES THE BARLEY", "has_genre", "WAR" ], [ "THE WIND THAT SHAKES THE BARLEY", "in_language", "ENGLISH" ], [ "THE WIND THAT SHAKES THE BARLEY", "release_year", "2006" ], [ "THERE BE DRAGONS", "has_genre", "WAR" ], [ "THERE BE DRAGONS", "in_language", "ENGLISH" ], [ "TWISTER", "has_genre", "COMEDY" ], [ "TWISTER", "has_genre", "DRAMA" ], [ "TWISTER", "has_tags", "MICHAEL CRICHTON" ], [ "TWISTER", "written_by", "MICHAEL CRICHTON" ], [ "YANKS", "has_genre", "WAR" ], [ "YANKS", "has_tags", "WORLD WAR II" ], [ "ZERO DARK THIRTY", "has_genre", "THRILLER" ], [ "ZERO DARK THIRTY", "has_tags", "WAR" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 9256, ANDREW CALDWELL 23702, BLOOMINGTON 16496, BLUE CHIPS 39848, BLUE LIKE JAZZ 24116, COLLEGE 38134, DANTE 01 36212, DRAMA 14023, GLORY ROAD 37982, GUMMO 14931, LIBERAL ARTS 4569, MARC CARO 9433, STOMP THE YARD 10213, THE GREAT DEBATERS 31401, THE RULES OF ATTRACTION src, edge_attr, dst 23702, has_genre, 36212 23702, has_tags, 24116 16496, has_genre, 36212 16496, has_tags, 24116 39848, has_genre, 36212 39848, has_tags, 24116 24116, has_genre, 36212 24116, release_year, 26762 24116, starred_actors, 9256 38134, directed_by, 4569 38134, release_year, 26762 38134, written_by, 4569 14023, has_genre, 36212 14023, has_tags, 24116 37982, has_genre, 36212 14931, has_genre, 36212 14931, has_tags, 24116 9433, has_genre, 36212 9433, has_tags, 24116 10213, has_genre, 36212 10213, has_tags, 24116 31401, has_genre, 36212 31401, has_tags, 24116 Question: How are ANDREW CALDWELL, GUMMO, and MARC CARO related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANDREW CALDWELL", "GUMMO", "MARC CARO" ], "valid_edges": [ [ "BLOOMINGTON", "has_genre", "DRAMA" ], [ "BLOOMINGTON", "has_tags", "COLLEGE" ], [ "BLUE CHIPS", "has_genre", "DRAMA" ], [ "BLUE CHIPS", "has_tags", "COLLEGE" ], [ "BLUE LIKE JAZZ", "has_genre", "DRAMA" ], [ "BLUE LIKE JAZZ", "has_tags", "COLLEGE" ], [ "COLLEGE", "has_genre", "DRAMA" ], [ "COLLEGE", "release_year", "2008" ], [ "COLLEGE", "starred_actors", "ANDREW CALDWELL" ], [ "DANTE 01", "directed_by", "MARC CARO" ], [ "DANTE 01", "release_year", "2008" ], [ "DANTE 01", "written_by", "MARC CARO" ], [ "GLORY ROAD", "has_genre", "DRAMA" ], [ "GLORY ROAD", "has_tags", "COLLEGE" ], [ "GUMMO", "has_genre", "DRAMA" ], [ "LIBERAL ARTS", "has_genre", "DRAMA" ], [ "LIBERAL ARTS", "has_tags", "COLLEGE" ], [ "STOMP THE YARD", "has_genre", "DRAMA" ], [ "STOMP THE YARD", "has_tags", "COLLEGE" ], [ "THE GREAT DEBATERS", "has_genre", "DRAMA" ], [ "THE GREAT DEBATERS", "has_tags", "COLLEGE" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "has_tags", "COLLEGE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 658, 2012 35724, ALTER EGOS 14883, DANNY MASTERSON 34031, RAGING PHOENIX 15926, SILENT NIGHT 36058, STEVEN C. MILLER src, edge_attr, dst 658, release_year, 27261 35724, release_year, 658 35724, starred_actors, 14883 34031, release_year, 27261 15926, directed_by, 36058 15926, release_year, 658 Question: For what reason are DANNY MASTERSON, RAGING PHOENIX, and STEVEN C. MILLER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DANNY MASTERSON", "RAGING PHOENIX", "STEVEN C. MILLER" ], "valid_edges": [ [ "2012", "release_year", "2009" ], [ "ALTER EGOS", "release_year", "2012" ], [ "ALTER EGOS", "starred_actors", "DANNY MASTERSON" ], [ "RAGING PHOENIX", "release_year", "2009" ], [ "SILENT NIGHT", "directed_by", "STEVEN C. MILLER" ], [ "SILENT NIGHT", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 1006, 1996 35845, 2006 18243, A SCANNER DARKLY 23754, AFTER THE WEDDING 6938, ALPHA DOG 8229, APOCALYPTO 24301, ART SCHOOL CONFIDENTIAL 18820, ASK THE DUST 24366, BABEL 17883, BARRY LEVINSON 38865, BIG NIGHT 36593, BLACK CHRISTMAS 16664, BLOOD DIAMOND 10531, BOBBY 867, BREAKING AND ENTERING 16749, BROKEN ARROW 17899, BUG 33360, CANDY 22435, CHILDREN OF MEN 21625, CLERKS II 37750, CRANK 32049, CRASH 15115, CURSE OF THE GOLDEN FLOWER 932, DAVID HARE 3567, DAYS OF GLORY 21123, FARGO 13766, FAST FOOD NATION 13893, FIDO 18217, FIND ME GUILTY 10315, FLAGS OF OUR FATHERS 39988, FRIENDS WITH MONEY 7879, HALF NELSON 26170, HOLLYWOODLAND 17120, INFAMOUS 19637, INLAND EMPIRE 7264, INSIDE MAN 18934, LETTERS FROM IWO JIMA 11277, LITTLE CHILDREN 24376, LITTLE MISS SUNSHINE 19123, LONE STAR 33950, LUCKY NUMBER SLEVIN 38677, MIAMI VICE 39852, PAN'S LABYRINTH 3451, PAPRIKA 13081, R 37623, RAIN MAN 2169, RANSOM 18480, RENAISSANCE 5766, RUNNING WITH SCISSORS 17383, SHERRYBABY 26768, SLEEPERS 29018, SLING BLADE 26930, SLITHER 12333, SMOKIN' ACES 21171, STEPHEN DALDRY 37807, TELL NO ONE 37498, TENACIOUS D IN THE PICK OF DESTINY 11948, THE BLACK DAHLIA 31353, THE CONTRACT 1059, THE DA VINCI CODE 18997, THE DEPARTED 1723, THE FALL 4662, THE GOOD GERMAN 15862, THE GOOD SHEPHERD 31309, THE HOAX 11713, THE HOURS 2467, THE LAST KING OF SCOTLAND 14315, THE LIVES OF OTHERS 17393, THE NIGHT LISTENER 9058, THE READER 36327, THE ROCK 11383, THE SCIENCE OF SLEEP 27559, TRAINSPOTTING 25806, UNITED 93 36753, VENUS 35728, VOLVER 27612, WHAT JUST HAPPENED src, edge_attr, dst 29145, has_tags, 13081 29145, release_year, 35845 18243, has_tags, 13081 18243, release_year, 35845 23754, has_tags, 13081 23754, release_year, 35845 6938, has_tags, 13081 6938, release_year, 35845 8229, has_tags, 13081 8229, release_year, 35845 24301, has_tags, 13081 24301, release_year, 35845 18820, has_tags, 13081 18820, release_year, 35845 24366, has_tags, 13081 24366, release_year, 35845 38865, has_tags, 13081 38865, release_year, 1006 36593, has_tags, 13081 36593, release_year, 35845 16664, has_tags, 13081 16664, release_year, 35845 10531, has_tags, 13081 10531, release_year, 35845 867, has_tags, 13081 867, release_year, 35845 16749, has_tags, 13081 16749, release_year, 1006 17899, has_tags, 13081 17899, release_year, 35845 33360, has_tags, 13081 33360, release_year, 35845 22435, has_tags, 13081 22435, release_year, 35845 21625, has_tags, 13081 21625, release_year, 35845 37750, has_tags, 13081 37750, release_year, 35845 32049, has_tags, 13081 32049, release_year, 1006 15115, has_tags, 13081 15115, release_year, 35845 3567, has_tags, 13081 3567, release_year, 35845 21123, has_tags, 13081 21123, release_year, 1006 13766, has_tags, 13081 13766, release_year, 35845 13893, has_tags, 13081 13893, release_year, 35845 18217, has_tags, 13081 18217, release_year, 35845 10315, has_tags, 13081 10315, release_year, 35845 39988, has_tags, 13081 39988, release_year, 35845 7879, has_tags, 13081 7879, release_year, 35845 26170, has_tags, 13081 26170, release_year, 35845 17120, has_tags, 13081 17120, release_year, 35845 19637, has_tags, 13081 19637, release_year, 35845 7264, has_tags, 13081 7264, release_year, 35845 18934, has_tags, 13081 18934, release_year, 35845 11277, has_tags, 13081 11277, release_year, 35845 24376, has_tags, 13081 24376, release_year, 35845 19123, has_tags, 13081 19123, release_year, 1006 33950, has_tags, 13081 33950, release_year, 35845 38677, has_tags, 13081 38677, release_year, 35845 39852, has_tags, 13081 39852, release_year, 35845 3451, has_tags, 13081 3451, release_year, 35845 37623, directed_by, 17883 37623, has_tags, 17883 37623, has_tags, 13081 2169, has_tags, 13081 2169, release_year, 1006 18480, has_tags, 13081 18480, release_year, 35845 5766, has_tags, 13081 5766, release_year, 35845 17383, has_tags, 13081 17383, release_year, 35845 26768, directed_by, 17883 26768, has_tags, 17883 26768, has_tags, 13081 26768, release_year, 1006 26768, written_by, 17883 29018, has_tags, 13081 29018, release_year, 1006 26930, has_tags, 13081 26930, release_year, 35845 12333, has_tags, 13081 12333, release_year, 35845 37807, release_year, 35845 37498, has_tags, 13081 37498, release_year, 35845 11948, has_tags, 13081 11948, release_year, 35845 31353, has_tags, 13081 31353, release_year, 35845 1059, has_tags, 13081 1059, release_year, 35845 18997, has_tags, 13081 18997, release_year, 35845 1723, has_tags, 13081 1723, release_year, 35845 4662, has_tags, 13081 4662, release_year, 35845 15862, has_tags, 13081 15862, release_year, 35845 31309, has_tags, 13081 31309, release_year, 35845 11713, directed_by, 21171 11713, has_tags, 21171 11713, written_by, 932 2467, has_tags, 13081 2467, release_year, 35845 14315, has_tags, 13081 14315, release_year, 35845 17393, has_tags, 13081 17393, release_year, 35845 9058, directed_by, 21171 9058, has_tags, 13081 9058, has_tags, 21171 9058, written_by, 932 36327, has_tags, 13081 36327, release_year, 1006 11383, has_tags, 13081 11383, release_year, 35845 27559, has_tags, 13081 27559, release_year, 1006 25806, has_tags, 13081 25806, release_year, 35845 36753, has_tags, 13081 36753, release_year, 35845 35728, has_tags, 13081 35728, release_year, 35845 27612, directed_by, 17883 27612, has_tags, 17883 27612, has_tags, 13081 Question: How are DAVID HARE, SLEEPERS, and TELL NO ONE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAVID HARE", "SLEEPERS", "TELL NO ONE" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_tags", "R" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "A SCANNER DARKLY", "has_tags", "R" ], [ "A SCANNER DARKLY", "release_year", "2006" ], [ "AFTER THE WEDDING", "has_tags", "R" ], [ "AFTER THE WEDDING", "release_year", "2006" ], [ "ALPHA DOG", "has_tags", "R" ], [ "ALPHA DOG", "release_year", "2006" ], [ "APOCALYPTO", "has_tags", "R" ], [ "APOCALYPTO", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_tags", "R" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "ASK THE DUST", "has_tags", "R" ], [ "ASK THE DUST", "release_year", "2006" ], [ "BABEL", "has_tags", "R" ], [ "BABEL", "release_year", "2006" ], [ "BIG NIGHT", "has_tags", "R" ], [ "BIG NIGHT", "release_year", "1996" ], [ "BLACK CHRISTMAS", "has_tags", "R" ], [ "BLACK CHRISTMAS", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "R" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "BOBBY", "has_tags", "R" ], [ "BOBBY", "release_year", "2006" ], [ "BREAKING AND ENTERING", "has_tags", "R" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "BROKEN ARROW", "has_tags", "R" ], [ "BROKEN ARROW", "release_year", "1996" ], [ "BUG", "has_tags", "R" ], [ "BUG", "release_year", "2006" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "R" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "CLERKS II", "has_tags", "R" ], [ "CLERKS II", "release_year", "2006" ], [ "CRANK", "has_tags", "R" ], [ "CRANK", "release_year", "2006" ], [ "CRASH", "has_tags", "R" ], [ "CRASH", "release_year", "1996" ], [ "CURSE OF THE GOLDEN FLOWER", "has_tags", "R" ], [ "CURSE OF THE GOLDEN FLOWER", "release_year", "2006" ], [ "DAYS OF GLORY", "has_tags", "R" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "FARGO", "has_tags", "R" ], [ "FARGO", "release_year", "1996" ], [ "FAST FOOD NATION", "has_tags", "R" ], [ "FAST FOOD NATION", "release_year", "2006" ], [ "FIDO", "has_tags", "R" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_tags", "R" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FRIENDS WITH MONEY", "has_tags", "R" ], [ "FRIENDS WITH MONEY", "release_year", "2006" ], [ "HALF NELSON", "has_tags", "R" ], [ "HALF NELSON", "release_year", "2006" ], [ "HOLLYWOODLAND", "has_tags", "R" ], [ "HOLLYWOODLAND", "release_year", "2006" ], [ "INFAMOUS", "has_tags", "R" ], [ "INFAMOUS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "R" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "INSIDE MAN", "has_tags", "R" ], [ "INSIDE MAN", "release_year", "2006" ], [ "LETTERS FROM IWO JIMA", "has_tags", "R" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "LITTLE CHILDREN", "has_tags", "R" ], [ "LITTLE CHILDREN", "release_year", "2006" ], [ "LITTLE MISS SUNSHINE", "has_tags", "R" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LONE STAR", "has_tags", "R" ], [ "LONE STAR", "release_year", "1996" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "release_year", "2006" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MIAMI VICE", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_tags", "R" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PAPRIKA", "has_tags", "R" ], [ "PAPRIKA", "release_year", "2006" ], [ "RAIN MAN", "directed_by", "BARRY LEVINSON" ], [ "RAIN MAN", "has_tags", "BARRY LEVINSON" ], [ "RAIN MAN", "has_tags", "R" ], [ "RANSOM", "has_tags", "R" ], [ "RANSOM", "release_year", "1996" ], [ "RENAISSANCE", "has_tags", "R" ], [ "RENAISSANCE", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_tags", "R" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "SHERRYBABY", "has_tags", "R" ], [ "SHERRYBABY", "release_year", "2006" ], [ "SLEEPERS", "directed_by", "BARRY LEVINSON" ], [ "SLEEPERS", "has_tags", "BARRY LEVINSON" ], [ "SLEEPERS", "has_tags", "R" ], [ "SLEEPERS", "release_year", "1996" ], [ "SLEEPERS", "written_by", "BARRY LEVINSON" ], [ "SLING BLADE", "has_tags", "R" ], [ "SLING BLADE", "release_year", "1996" ], [ "SLITHER", "has_tags", "R" ], [ "SLITHER", "release_year", "2006" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "TELL NO ONE", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "R" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE BLACK DAHLIA", "release_year", "2006" ], [ "THE CONTRACT", "has_tags", "R" ], [ "THE CONTRACT", "release_year", "2006" ], [ "THE DA VINCI CODE", "has_tags", "R" ], [ "THE DA VINCI CODE", "release_year", "2006" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "release_year", "2006" ], [ "THE FALL", "has_tags", "R" ], [ "THE FALL", "release_year", "2006" ], [ "THE GOOD GERMAN", "has_tags", "R" ], [ "THE GOOD GERMAN", "release_year", "2006" ], [ "THE GOOD SHEPHERD", "has_tags", "R" ], [ "THE GOOD SHEPHERD", "release_year", "2006" ], [ "THE HOAX", "has_tags", "R" ], [ "THE HOAX", "release_year", "2006" ], [ "THE HOURS", "directed_by", "STEPHEN DALDRY" ], [ "THE HOURS", "has_tags", "STEPHEN DALDRY" ], [ "THE HOURS", "written_by", "DAVID HARE" ], [ "THE LAST KING OF SCOTLAND", "has_tags", "R" ], [ "THE LAST KING OF SCOTLAND", "release_year", "2006" ], [ "THE LIVES OF OTHERS", "has_tags", "R" ], [ "THE LIVES OF OTHERS", "release_year", "2006" ], [ "THE NIGHT LISTENER", "has_tags", "R" ], [ "THE NIGHT LISTENER", "release_year", "2006" ], [ "THE READER", "directed_by", "STEPHEN DALDRY" ], [ "THE READER", "has_tags", "R" ], [ "THE READER", "has_tags", "STEPHEN DALDRY" ], [ "THE READER", "written_by", "DAVID HARE" ], [ "THE ROCK", "has_tags", "R" ], [ "THE ROCK", "release_year", "1996" ], [ "THE SCIENCE OF SLEEP", "has_tags", "R" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "TRAINSPOTTING", "has_tags", "R" ], [ "TRAINSPOTTING", "release_year", "1996" ], [ "UNITED 93", "has_tags", "R" ], [ "UNITED 93", "release_year", "2006" ], [ "VENUS", "has_tags", "R" ], [ "VENUS", "release_year", "2006" ], [ "VOLVER", "has_tags", "R" ], [ "VOLVER", "release_year", "2006" ], [ "WHAT JUST HAPPENED", "directed_by", "BARRY LEVINSON" ], [ "WHAT JUST HAPPENED", "has_tags", "BARRY LEVINSON" ], [ "WHAT JUST HAPPENED", "has_tags", "R" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26633, 1989 37484, 2004 812, BATMAN 27815, CLOWNHOUSE 18348, DHOOM 22693, HELLS ANGELS ON WHEELS 21488, JACK NICHOLSON 32051, THE PUNISHER src, edge_attr, dst 812, has_tags, 21488 812, release_year, 26633 812, starred_actors, 21488 27815, release_year, 26633 18348, release_year, 37484 22693, has_tags, 21488 22693, starred_actors, 21488 32051, release_year, 26633 32051, release_year, 37484 Question: In what context are CLOWNHOUSE, DHOOM, and HELLS ANGELS ON WHEELS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CLOWNHOUSE", "DHOOM", "HELLS ANGELS ON WHEELS" ], "valid_edges": [ [ "BATMAN", "has_tags", "JACK NICHOLSON" ], [ "BATMAN", "release_year", "1989" ], [ "BATMAN", "starred_actors", "JACK NICHOLSON" ], [ "CLOWNHOUSE", "release_year", "1989" ], [ "DHOOM", "release_year", "2004" ], [ "HELLS ANGELS ON WHEELS", "has_tags", "JACK NICHOLSON" ], [ "HELLS ANGELS ON WHEELS", "starred_actors", "JACK NICHOLSON" ], [ "THE PUNISHER", "release_year", "1989" ], [ "THE PUNISHER", "release_year", "2004" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35187, 1948 26423, 1950 32617, GLORIA DEHAVEN 31193, PAT GARRISON 6498, RUSSEL CROUSE 5765, STATE OF THE UNION 29067, SUMMER HOLIDAY 37757, SUMMER STOCK 34691, THE FLYING SAUCER 37555, THE YELLOW CAB MAN src, edge_attr, dst 5765, release_year, 35187 5765, written_by, 6498 29067, release_year, 35187 29067, starred_actors, 32617 37757, release_year, 26423 37757, starred_actors, 32617 34691, release_year, 26423 34691, starred_actors, 31193 37555, release_year, 26423 37555, starred_actors, 32617 Question: How are GLORIA DEHAVEN, PAT GARRISON, and RUSSEL CROUSE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GLORIA DEHAVEN", "PAT GARRISON", "RUSSEL CROUSE" ], "valid_edges": [ [ "STATE OF THE UNION", "release_year", "1948" ], [ "STATE OF THE UNION", "written_by", "RUSSEL CROUSE" ], [ "SUMMER HOLIDAY", "release_year", "1948" ], [ "SUMMER HOLIDAY", "starred_actors", "GLORIA DEHAVEN" ], [ "SUMMER STOCK", "release_year", "1950" ], [ "SUMMER STOCK", "starred_actors", "GLORIA DEHAVEN" ], [ "THE FLYING SAUCER", "release_year", "1950" ], [ "THE FLYING SAUCER", "starred_actors", "PAT GARRISON" ], [ "THE YELLOW CAB MAN", "release_year", "1950" ], [ "THE YELLOW CAB MAN", "starred_actors", "GLORIA DEHAVEN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16055, 1983 21497, A NIGHT IN HEAVEN 37540, DON JUAN DEMARCO 32719, EDWIGE FEUILLÈRE 6012, FRENCH 24485, HIGH ROAD TO CHINA 2625, JOYSTICKS 11142, LUCREZIA BORGIA 8379, ROMANCE src, edge_attr, dst 21497, has_genre, 8379 21497, release_year, 16055 37540, has_genre, 8379 37540, has_tags, 8379 24485, has_genre, 8379 24485, release_year, 16055 2625, release_year, 16055 11142, in_language, 6012 11142, starred_actors, 32719 8379, in_language, 6012 Question: In what context are DON JUAN DEMARCO, EDWIGE FEUILLÈRE, and JOYSTICKS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DON JUAN DEMARCO", "EDWIGE FEUILLÈRE", "JOYSTICKS" ], "valid_edges": [ [ "A NIGHT IN HEAVEN", "has_genre", "ROMANCE" ], [ "A NIGHT IN HEAVEN", "release_year", "1983" ], [ "DON JUAN DEMARCO", "has_genre", "ROMANCE" ], [ "DON JUAN DEMARCO", "has_tags", "ROMANCE" ], [ "HIGH ROAD TO CHINA", "has_genre", "ROMANCE" ], [ "HIGH ROAD TO CHINA", "release_year", "1983" ], [ "JOYSTICKS", "release_year", "1983" ], [ "LUCREZIA BORGIA", "in_language", "FRENCH" ], [ "LUCREZIA BORGIA", "starred_actors", "EDWIGE FEUILLÈRE" ], [ "ROMANCE", "in_language", "FRENCH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 14259, 1997 2216, ALONG THE GREAT DIVIDE 33132, ARNOLD SCHWARZENEGGER 9589, BLUE 37414, FRANZ KAFKA 21574, KIRK DOUGLAS 39841, LAST ACTION HERO 22519, LAST TRAIN FROM GUN HILL 3937, POSSE 21732, SUTURE 18456, THE BALLAD OF LITTLE JO 29540, THE BIG SKY 13392, THE CASTLE 7009, THE LAST SUNSET 27535, THE VILLAIN 6789, THE WAR WAGON 19240, TOMBSTONE 36026, WESTERN src, edge_attr, dst 2216, has_genre, 36026 2216, starred_actors, 21574 9589, has_genre, 36026 9589, release_year, 24438 39841, has_tags, 33132 39841, release_year, 24438 39841, starred_actors, 33132 22519, has_genre, 36026 22519, starred_actors, 21574 3937, directed_by, 21574 3937, has_genre, 36026 3937, release_year, 24438 3937, starred_actors, 21574 21732, release_year, 24438 18456, has_genre, 36026 18456, release_year, 24438 29540, has_genre, 36026 29540, starred_actors, 21574 13392, has_tags, 37414 13392, release_year, 14259 13392, written_by, 37414 7009, has_genre, 36026 7009, starred_actors, 21574 27535, has_genre, 36026 27535, starred_actors, 33132 27535, starred_actors, 21574 6789, has_genre, 36026 6789, has_tags, 21574 6789, starred_actors, 21574 19240, has_tags, 36026 19240, release_year, 24438 36026, release_year, 14259 Question: How are FRANZ KAFKA, SUTURE, and THE VILLAIN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FRANZ KAFKA", "SUTURE", "THE VILLAIN" ], "valid_edges": [ [ "ALONG THE GREAT DIVIDE", "has_genre", "WESTERN" ], [ "ALONG THE GREAT DIVIDE", "starred_actors", "KIRK DOUGLAS" ], [ "BLUE", "has_genre", "WESTERN" ], [ "BLUE", "release_year", "1993" ], [ "LAST ACTION HERO", "has_tags", "ARNOLD SCHWARZENEGGER" ], [ "LAST ACTION HERO", "release_year", "1993" ], [ "LAST ACTION HERO", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "LAST TRAIN FROM GUN HILL", "has_genre", "WESTERN" ], [ "LAST TRAIN FROM GUN HILL", "starred_actors", "KIRK DOUGLAS" ], [ "POSSE", "directed_by", "KIRK DOUGLAS" ], [ "POSSE", "has_genre", "WESTERN" ], [ "POSSE", "release_year", "1993" ], [ "POSSE", "starred_actors", "KIRK DOUGLAS" ], [ "SUTURE", "release_year", "1993" ], [ "THE BALLAD OF LITTLE JO", "has_genre", "WESTERN" ], [ "THE BALLAD OF LITTLE JO", "release_year", "1993" ], [ "THE BIG SKY", "has_genre", "WESTERN" ], [ "THE BIG SKY", "starred_actors", "KIRK DOUGLAS" ], [ "THE CASTLE", "has_tags", "FRANZ KAFKA" ], [ "THE CASTLE", "release_year", "1997" ], [ "THE CASTLE", "written_by", "FRANZ KAFKA" ], [ "THE LAST SUNSET", "has_genre", "WESTERN" ], [ "THE LAST SUNSET", "starred_actors", "KIRK DOUGLAS" ], [ "THE VILLAIN", "has_genre", "WESTERN" ], [ "THE VILLAIN", "starred_actors", "ARNOLD SCHWARZENEGGER" ], [ "THE VILLAIN", "starred_actors", "KIRK DOUGLAS" ], [ "THE WAR WAGON", "has_genre", "WESTERN" ], [ "THE WAR WAGON", "has_tags", "KIRK DOUGLAS" ], [ "THE WAR WAGON", "starred_actors", "KIRK DOUGLAS" ], [ "TOMBSTONE", "has_tags", "WESTERN" ], [ "TOMBSTONE", "release_year", "1993" ], [ "WESTERN", "release_year", "1997" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 26762, 2008 18239, A RAISIN IN THE SUN 35253, ACE OF HEARTS 25639, BEDTIME STORIES 21862, COLLEGE ROAD TRIP 10509, FAMILY 25086, FRENCH FILM 15629, HOME ALONE 4 21518, HONEY, I SHRUNK THE KIDS 6713, KAMCHATKA 33783, KRISTINE SUTHERLAND 31974, MANITO 20844, MEET DAVE 14026, PINOCCHIO 1507, ROAD TO PERDITION 24467, SPEED RACER 32587, SUMMER HOURS 7013, THE COUNTRY BEARS 4872, THE SPIDERWICK CHRONICLES 15632, THUNDERPANTS 900, TUCK EVERLASTING src, edge_attr, dst 18239, has_tags, 10509 18239, release_year, 26762 35253, has_genre, 10509 35253, release_year, 26762 25639, has_genre, 10509 25639, release_year, 26762 21862, has_tags, 10509 21862, release_year, 26762 25086, release_year, 26762 15629, has_genre, 10509 15629, release_year, 35935 21518, has_genre, 10509 21518, has_tags, 10509 21518, starred_actors, 33783 6713, has_tags, 10509 6713, release_year, 35935 31974, has_genre, 10509 31974, release_year, 35935 20844, has_genre, 10509 20844, release_year, 26762 14026, has_genre, 10509 14026, release_year, 35935 1507, has_tags, 10509 1507, release_year, 35935 24467, has_genre, 10509 24467, release_year, 26762 32587, has_genre, 10509 32587, release_year, 26762 7013, has_genre, 10509 7013, release_year, 35935 4872, has_genre, 10509 4872, release_year, 26762 15632, has_genre, 10509 15632, release_year, 35935 900, has_genre, 10509 900, release_year, 35935 Question: How are FRENCH FILM, KRISTINE SUTHERLAND, and MANITO related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FRENCH FILM", "KRISTINE SUTHERLAND", "MANITO" ], "valid_edges": [ [ "A RAISIN IN THE SUN", "has_tags", "FAMILY" ], [ "A RAISIN IN THE SUN", "release_year", "2008" ], [ "ACE OF HEARTS", "has_genre", "FAMILY" ], [ "ACE OF HEARTS", "release_year", "2008" ], [ "BEDTIME STORIES", "has_genre", "FAMILY" ], [ "BEDTIME STORIES", "release_year", "2008" ], [ "COLLEGE ROAD TRIP", "has_tags", "FAMILY" ], [ "COLLEGE ROAD TRIP", "release_year", "2008" ], [ "FRENCH FILM", "release_year", "2008" ], [ "HOME ALONE 4", "has_genre", "FAMILY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "HONEY, I SHRUNK THE KIDS", "has_genre", "FAMILY" ], [ "HONEY, I SHRUNK THE KIDS", "has_tags", "FAMILY" ], [ "HONEY, I SHRUNK THE KIDS", "starred_actors", "KRISTINE SUTHERLAND" ], [ "KAMCHATKA", "has_tags", "FAMILY" ], [ "KAMCHATKA", "release_year", "2002" ], [ "MANITO", "has_genre", "FAMILY" ], [ "MANITO", "release_year", "2002" ], [ "MEET DAVE", "has_genre", "FAMILY" ], [ "MEET DAVE", "release_year", "2008" ], [ "PINOCCHIO", "has_genre", "FAMILY" ], [ "PINOCCHIO", "release_year", "2002" ], [ "ROAD TO PERDITION", "has_tags", "FAMILY" ], [ "ROAD TO PERDITION", "release_year", "2002" ], [ "SPEED RACER", "has_genre", "FAMILY" ], [ "SPEED RACER", "release_year", "2008" ], [ "SUMMER HOURS", "has_genre", "FAMILY" ], [ "SUMMER HOURS", "release_year", "2008" ], [ "THE COUNTRY BEARS", "has_genre", "FAMILY" ], [ "THE COUNTRY BEARS", "release_year", "2002" ], [ "THE SPIDERWICK CHRONICLES", "has_genre", "FAMILY" ], [ "THE SPIDERWICK CHRONICLES", "release_year", "2008" ], [ "THUNDERPANTS", "has_genre", "FAMILY" ], [ "THUNDERPANTS", "release_year", "2002" ], [ "TUCK EVERLASTING", "has_genre", "FAMILY" ], [ "TUCK EVERLASTING", "release_year", "2002" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 14004, 1955 29424, 2011 23373, ARTISTS AND MODELS 12155, DADDY LONG LEGS 4057, FOOTLIGHT PARADE 28905, GOLD DIGGERS OF 1933 12244, GUYS AND DOLLS 6813, IT'S ALWAYS FAIR WEATHER 5208, JAMES CAGNEY 103, LOVE ME OR LEAVE ME 7765, LOVELY TO LOOK AT 34605, MERVYN LEROY 6961, MILLION DOLLAR MERMAID 31701, MISTER ROBERTS 9327, MONTE CARLO 24593, MUSICAL 8397, MY SISTER EILEEN 18184, OKLAHOMA! 33981, PARANORMAL ACTIVITY 3 20243, RUN FOR COVER 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 30311, THE COURT JESTER 12773, THE GLASS SLIPPER 11189, THE MUPPETS 31313, THE WEST POINT STORY 3043, YANKEE DOODLE DANDY src, edge_attr, dst 23373, has_genre, 24593 23373, release_year, 14004 12155, has_genre, 24593 12155, has_tags, 24593 12155, release_year, 14004 4057, has_genre, 24593 4057, has_tags, 5208 4057, has_tags, 24593 4057, starred_actors, 5208 28905, directed_by, 34605 28905, has_genre, 24593 28905, has_tags, 34605 12244, has_genre, 24593 12244, release_year, 14004 6813, has_genre, 24593 6813, release_year, 14004 103, release_year, 14004 103, starred_actors, 5208 7765, directed_by, 34605 7765, has_genre, 24593 6961, directed_by, 34605 6961, has_genre, 24593 31701, directed_by, 34605 31701, has_tags, 5208 31701, has_tags, 34605 31701, release_year, 14004 31701, starred_actors, 5208 9327, has_genre, 24593 9327, release_year, 29424 8397, has_genre, 24593 8397, release_year, 14004 18184, has_genre, 24593 18184, has_tags, 24593 18184, release_year, 14004 33981, release_year, 29424 20243, release_year, 14004 20243, starred_actors, 5208 10409, has_genre, 24593 30311, has_tags, 24593 30311, release_year, 14004 12773, has_genre, 24593 12773, release_year, 14004 11189, has_genre, 24593 11189, has_tags, 24593 11189, release_year, 29424 31313, has_tags, 5208 31313, has_tags, 24593 31313, starred_actors, 5208 3043, has_genre, 24593 3043, has_tags, 5208 3043, has_tags, 24593 3043, starred_actors, 5208 Question: For what reason are MISTER ROBERTS, PARANORMAL ACTIVITY 3, and THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MISTER ROBERTS", "PARANORMAL ACTIVITY 3", "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER" ], "valid_edges": [ [ "ARTISTS AND MODELS", "has_genre", "MUSICAL" ], [ "ARTISTS AND MODELS", "release_year", "1955" ], [ "DADDY LONG LEGS", "has_genre", "MUSICAL" ], [ "DADDY LONG LEGS", "has_tags", "MUSICAL" ], [ "DADDY LONG LEGS", "release_year", "1955" ], [ "FOOTLIGHT PARADE", "has_genre", "MUSICAL" ], [ "FOOTLIGHT PARADE", "has_tags", "JAMES CAGNEY" ], [ "FOOTLIGHT PARADE", "has_tags", "MUSICAL" ], [ "FOOTLIGHT PARADE", "starred_actors", "JAMES CAGNEY" ], [ "GOLD DIGGERS OF 1933", "directed_by", "MERVYN LEROY" ], [ "GOLD DIGGERS OF 1933", "has_genre", "MUSICAL" ], [ "GOLD DIGGERS OF 1933", "has_tags", "MERVYN LEROY" ], [ "GUYS AND DOLLS", "has_genre", "MUSICAL" ], [ "GUYS AND DOLLS", "release_year", "1955" ], [ "IT'S ALWAYS FAIR WEATHER", "has_genre", "MUSICAL" ], [ "IT'S ALWAYS FAIR WEATHER", "release_year", "1955" ], [ "LOVE ME OR LEAVE ME", "release_year", "1955" ], [ "LOVE ME OR LEAVE ME", "starred_actors", "JAMES CAGNEY" ], [ "LOVELY TO LOOK AT", "directed_by", "MERVYN LEROY" ], [ "LOVELY TO LOOK AT", "has_genre", "MUSICAL" ], [ "MILLION DOLLAR MERMAID", "directed_by", "MERVYN LEROY" ], [ "MILLION DOLLAR MERMAID", "has_genre", "MUSICAL" ], [ "MISTER ROBERTS", "directed_by", "MERVYN LEROY" ], [ "MISTER ROBERTS", "has_tags", "JAMES CAGNEY" ], [ "MISTER ROBERTS", "has_tags", "MERVYN LEROY" ], [ "MISTER ROBERTS", "release_year", "1955" ], [ "MISTER ROBERTS", "starred_actors", "JAMES CAGNEY" ], [ "MONTE CARLO", "has_genre", "MUSICAL" ], [ "MONTE CARLO", "release_year", "2011" ], [ "MY SISTER EILEEN", "has_genre", "MUSICAL" ], [ "MY SISTER EILEEN", "release_year", "1955" ], [ "OKLAHOMA!", "has_genre", "MUSICAL" ], [ "OKLAHOMA!", "has_tags", "MUSICAL" ], [ "OKLAHOMA!", "release_year", "1955" ], [ "PARANORMAL ACTIVITY 3", "release_year", "2011" ], [ "RUN FOR COVER", "release_year", "1955" ], [ "RUN FOR COVER", "starred_actors", "JAMES CAGNEY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "MUSICAL" ], [ "THE COURT JESTER", "has_tags", "MUSICAL" ], [ "THE COURT JESTER", "release_year", "1955" ], [ "THE GLASS SLIPPER", "has_genre", "MUSICAL" ], [ "THE GLASS SLIPPER", "release_year", "1955" ], [ "THE MUPPETS", "has_genre", "MUSICAL" ], [ "THE MUPPETS", "has_tags", "MUSICAL" ], [ "THE MUPPETS", "release_year", "2011" ], [ "THE WEST POINT STORY", "has_tags", "JAMES CAGNEY" ], [ "THE WEST POINT STORY", "has_tags", "MUSICAL" ], [ "THE WEST POINT STORY", "starred_actors", "JAMES CAGNEY" ], [ "YANKEE DOODLE DANDY", "has_genre", "MUSICAL" ], [ "YANKEE DOODLE DANDY", "has_tags", "JAMES CAGNEY" ], [ "YANKEE DOODLE DANDY", "has_tags", "MUSICAL" ], [ "YANKEE DOODLE DANDY", "starred_actors", "JAMES CAGNEY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 30146, A CHRISTMAS CAROL 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 16486, AGENT CODY BANKS 39750, ALIENS 10507, ALIENS IN THE ATTIC 22412, ALLAN QUATERMAIN AND THE LOST CITY OF GOLD 18310, AROUND THE WORLD IN 80 DAYS 38657, BEAT THE DEVIL 16795, CASANOVA'S BIG NIGHT 524, CHARLIE'S ANGELS 30463, COMEDY 30802, CUTTHROAT ISLAND 1329, ENVY 2449, EUROTRIP 549, GENTARO NAKAJIMA 39494, HOLES 358, HOWARD THE DUCK 1628, HUMPDAY 24061, INFESTATION 28405, JENNIFER'S BODY 6222, JOHN LARROQUETTE 34939, LO 26370, MADHOUSE 32058, MUPPET TREASURE ISLAND 14797, O BROTHER, WHERE ART THOU? 2391, PIRATES 31703, PUSS IN BOOTS 28221, ROMANCING THE STONE 35586, SAHARA 5629, SCOOBY-DOO! THE MYSTERY BEGINS 38231, SHANGHAI NOON 34989, STAR TREK 26790, SWEPT AWAY 13521, THE ADVENTURES OF FORD FAIRLANE 21330, THE CRIMSON PIRATE 18263, THE DUKES OF HAZZARD 4068, THE GENERAL 18150, THE JEWEL OF THE NILE 31851, THE PRISONER OF ZENDA 35221, THE REVENANT 30746, THE SECRET LIFE OF WALTER MITTY 15608, THE SPONGEBOB SQUAREPANTS MOVIE 7816, THE THREE MUSKETEERS 25443, TOM JONES 26828, TORMENTED 14499, TOY STORY 2 14057, TRANSYLMANIA 11659, VIVA MARIA! 36315, WARNING FROM SPACE src, edge_attr, dst 30146, has_genre, 30463 30146, release_year, 27261 16054, has_genre, 4763 16054, has_genre, 30463 16054, has_tags, 4763 16486, has_genre, 4763 16486, has_genre, 30463 39750, has_genre, 4763 10507, has_genre, 30463 10507, release_year, 27261 22412, has_genre, 4763 22412, has_genre, 30463 22412, has_tags, 4763 18310, has_genre, 4763 18310, has_genre, 30463 38657, has_genre, 4763 38657, has_genre, 30463 16795, has_genre, 4763 16795, has_genre, 30463 524, has_genre, 4763 524, has_genre, 30463 30802, has_genre, 4763 30802, has_genre, 30463 30802, has_tags, 4763 1329, has_genre, 30463 1329, release_year, 27261 2449, has_genre, 4763 2449, has_genre, 30463 2449, has_tags, 30463 39494, has_genre, 4763 39494, has_genre, 30463 358, has_genre, 4763 358, has_genre, 30463 1628, has_genre, 30463 1628, has_tags, 30463 1628, release_year, 27261 24061, has_genre, 30463 24061, release_year, 27261 28405, has_genre, 30463 28405, has_tags, 30463 28405, release_year, 27261 34939, has_genre, 30463 34939, release_year, 27261 26370, has_genre, 30463 26370, starred_actors, 6222 32058, has_genre, 4763 32058, has_genre, 30463 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 2391, has_genre, 4763 2391, has_genre, 30463 31703, has_genre, 4763 31703, has_genre, 30463 28221, has_genre, 4763 28221, has_genre, 30463 28221, has_tags, 4763 35586, has_genre, 4763 35586, has_genre, 30463 5629, has_genre, 4763 5629, has_genre, 30463 5629, release_year, 27261 38231, has_genre, 4763 38231, has_genre, 30463 34989, has_genre, 4763 34989, has_tags, 4763 34989, release_year, 27261 26790, has_genre, 4763 26790, has_genre, 30463 13521, has_genre, 4763 13521, has_genre, 30463 13521, has_tags, 30463 21330, has_genre, 4763 21330, has_genre, 30463 18263, has_genre, 4763 18263, has_genre, 30463 4068, has_genre, 4763 4068, has_genre, 30463 4068, has_tags, 30463 18150, has_genre, 4763 18150, has_genre, 30463 18150, has_tags, 4763 18150, has_tags, 30463 31851, has_genre, 4763 31851, has_genre, 30463 35221, has_genre, 30463 35221, release_year, 27261 30746, has_genre, 4763 30746, has_genre, 30463 15608, has_genre, 4763 15608, has_genre, 30463 7816, has_genre, 4763 7816, has_genre, 30463 25443, has_genre, 4763 25443, has_genre, 30463 26828, has_tags, 30463 26828, release_year, 27261 14499, has_genre, 4763 14499, has_genre, 30463 14057, has_genre, 30463 14057, release_year, 27261 11659, has_genre, 4763 11659, has_genre, 30463 36315, has_tags, 39750 36315, written_by, 549 Question: In what context are GENTARO NAKAJIMA, JOHN LARROQUETTE, and SCOOBY-DOO! THE MYSTERY BEGINS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GENTARO NAKAJIMA", "JOHN LARROQUETTE", "SCOOBY-DOO! THE MYSTERY BEGINS" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "release_year", "2009" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "COMEDY" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "ADVENTURE" ], [ "AGENT CODY BANKS", "has_genre", "COMEDY" ], [ "ALIENS", "has_genre", "ADVENTURE" ], [ "ALIENS IN THE ATTIC", "has_genre", "COMEDY" ], [ "ALIENS IN THE ATTIC", "release_year", "2009" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "ADVENTURE" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_genre", "COMEDY" ], [ "ALLAN QUATERMAIN AND THE LOST CITY OF GOLD", "has_tags", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "ADVENTURE" ], [ "AROUND THE WORLD IN 80 DAYS", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "ADVENTURE" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_genre", "ADVENTURE" ], [ "CUTTHROAT ISLAND", "has_genre", "COMEDY" ], [ "CUTTHROAT ISLAND", "has_tags", "ADVENTURE" ], [ "ENVY", "has_genre", "COMEDY" ], [ "ENVY", "release_year", "2009" ], [ "EUROTRIP", "has_genre", "ADVENTURE" ], [ "EUROTRIP", "has_genre", "COMEDY" ], [ "EUROTRIP", "has_tags", "COMEDY" ], [ "HOLES", "has_genre", "ADVENTURE" ], [ "HOLES", "has_genre", "COMEDY" ], [ "HOWARD THE DUCK", "has_genre", "ADVENTURE" ], [ "HOWARD THE DUCK", "has_genre", "COMEDY" ], [ "HUMPDAY", "has_genre", "COMEDY" ], [ "HUMPDAY", "has_tags", "COMEDY" ], [ "HUMPDAY", "release_year", "2009" ], [ "INFESTATION", "has_genre", "COMEDY" ], [ "INFESTATION", "release_year", "2009" ], [ "JENNIFER'S BODY", "has_genre", "COMEDY" ], [ "JENNIFER'S BODY", "has_tags", "COMEDY" ], [ "JENNIFER'S BODY", "release_year", "2009" ], [ "LO", "has_genre", "COMEDY" ], [ "LO", "release_year", "2009" ], [ "MADHOUSE", "has_genre", "COMEDY" ], [ "MADHOUSE", "starred_actors", "JOHN LARROQUETTE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "ADVENTURE" ], [ "MUPPET TREASURE ISLAND", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "PIRATES", "has_genre", "ADVENTURE" ], [ "PIRATES", "has_genre", "COMEDY" ], [ "PUSS IN BOOTS", "has_genre", "ADVENTURE" ], [ "PUSS IN BOOTS", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_genre", "ADVENTURE" ], [ "ROMANCING THE STONE", "has_genre", "COMEDY" ], [ "ROMANCING THE STONE", "has_tags", "ADVENTURE" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_genre", "COMEDY" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "ADVENTURE" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "has_genre", "COMEDY" ], [ "SCOOBY-DOO! THE MYSTERY BEGINS", "release_year", "2009" ], [ "SHANGHAI NOON", "has_genre", "ADVENTURE" ], [ "SHANGHAI NOON", "has_genre", "COMEDY" ], [ "STAR TREK", "has_genre", "ADVENTURE" ], [ "STAR TREK", "has_tags", "ADVENTURE" ], [ "STAR TREK", "release_year", "2009" ], [ "SWEPT AWAY", "has_genre", "ADVENTURE" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF FORD FAIRLANE", "has_tags", "COMEDY" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_genre", "COMEDY" ], [ "THE DUKES OF HAZZARD", "has_genre", "ADVENTURE" ], [ "THE DUKES OF HAZZARD", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_genre", "ADVENTURE" ], [ "THE GENERAL", "has_genre", "COMEDY" ], [ "THE GENERAL", "has_tags", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_genre", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_genre", "COMEDY" ], [ "THE JEWEL OF THE NILE", "has_tags", "ADVENTURE" ], [ "THE JEWEL OF THE NILE", "has_tags", "COMEDY" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE REVENANT", "has_genre", "COMEDY" ], [ "THE REVENANT", "release_year", "2009" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "ADVENTURE" ], [ "THE SPONGEBOB SQUAREPANTS MOVIE", "has_genre", "COMEDY" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_genre", "COMEDY" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_genre", "COMEDY" ], [ "TORMENTED", "has_tags", "COMEDY" ], [ "TORMENTED", "release_year", "2009" ], [ "TOY STORY 2", "has_genre", "ADVENTURE" ], [ "TOY STORY 2", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "release_year", "2009" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_genre", "COMEDY" ], [ "WARNING FROM SPACE", "has_tags", "ALIENS" ], [ "WARNING FROM SPACE", "written_by", "GENTARO NAKAJIMA" ] ] }