Datasets:
GEM
/

Tasks: unknown
Languages: Czech
Multilinguality: unknown
Size Categories: unknown
Language Creators: unknown
Annotations Creators: none
Source Datasets: original
Dataset Preview Go to dataset viewer
gem_id (string)gem_parent_id (string)dialog_act (string)dialog_act_delexicalized (string)target_delexicalized (string)target (string)references (list)
"cs_restaurants-train-0"
"cs_restaurants-train-0"
"inform(food=Indian,good_for_meal='lunch or dinner',name='Kočár z Vídně')"
"inform(food=X-food,good_for_meal=X-good_for_meal,name=X-name)"
"X-name podává X-food pokrmy a dá se zde dobře X-good_for_meal ."
"Kočár z Vídně podává indické pokrmy a dá se zde dobře naobědvat i navečeřet ."
[]
"cs_restaurants-train-1"
"cs_restaurants-train-1"
"inform(area=Karlín,food=French,name='Green Spirit')"
"inform(area=X-area,food=X-food,name=X-name)"
"X-name sídlí na X-area a vaří X-food jídla ."
"Green Spirit sídlí na Karlíně a vaří francouzská jídla ."
[]
"cs_restaurants-train-2"
"cs_restaurants-train-2"
"goodbye()"
"goodbye()"
"Tak na shledanou !"
"Tak na shledanou !"
[]
"cs_restaurants-train-3"
"cs_restaurants-train-3"
"inform(address='Národní 13',name='Baráčnická rychta')"
"inform(address=X-address,name=X-name)"
"Adresa X-name je X-address"
"Adresa Baráčnické rychty je Národní 13"
[]
"cs_restaurants-train-4"
"cs_restaurants-train-4"
"inform(address='Malostranské náměstí 1',area=Nusle,name=Ferdinanda)"
"inform(address=X-address,area=X-area,name=X-name)"
"Restaurace X-name se nachází v X-area na adrese X-address ."
"Restaurace Ferdinanda se nachází v Nuslích na adrese Malostranské náměstí 1 ."
[]
"cs_restaurants-train-5"
"cs_restaurants-train-5"
"?confirm(area=dont_care)"
"?confirm(area=dont_care)"
"Na oblasti nezáleží ?"
"Na oblasti nezáleží ?"
[]
"cs_restaurants-train-6"
"cs_restaurants-train-6"
"goodbye()"
"goodbye()"
"Děkuji , přeji hezký den ."
"Děkuji , přeji hezký den ."
[]
"cs_restaurants-train-7"
"cs_restaurants-train-7"
"inform(kids_allowed=yes,name='U Tučňáků')"
"inform(kids_allowed=yes,name=X-name)"
"Restaurace X-name je vhodná pro návštěvu s dětmi ."
"Restaurace U Tučňáků je vhodná pro návštěvu s dětmi ."
[]
"cs_restaurants-train-8"
"cs_restaurants-train-8"
"inform(address='Újezd 2',name='Café Kampus')"
"inform(address=X-address,name=X-name)"
"X-name najdete na X-address ."
"Café Kampus najdete na Újezdě 2 ."
[]
"cs_restaurants-train-9"
"cs_restaurants-train-9"
"?confirm(kids_allowed=no)"
"?confirm(kids_allowed=no)"
"Mohu se ujistit , že hledáte restauraci , kam nemají přístup děti ?"
"Mohu se ujistit , že hledáte restauraci , kam nemají přístup děti ?"
[]
"cs_restaurants-train-10"
"cs_restaurants-train-10"
"inform(food=Chinese,name=Ananta,near=Stromovka)"
"inform(food=X-food,name=X-name,near=X-near)"
"Mám tu restauraci X-name blízko X-near , která podává X-food kuchyni ."
"Mám tu restauraci Ananta blízko Stromovky , která podává čínskou kuchyni ."
[]
"cs_restaurants-train-11"
"cs_restaurants-train-11"
"?request(price_range)"
"?request(price_range)"
"Jakou cenovou kategorii si představujete ?"
"Jakou cenovou kategorii si představujete ?"
[]
"cs_restaurants-train-12"
"cs_restaurants-train-12"
"goodbye()"
"goodbye()"
"Děkuji za zavolání ."
"Děkuji za zavolání ."
[]
"cs_restaurants-train-13"
"cs_restaurants-train-13"
"inform(kids_allowed=yes,name=Místo)"
"inform(kids_allowed=yes,name=X-name)"
"Ano , do restaurace X-name mohou děti"
"Ano , do restaurace Místo mohou děti"
[]
"cs_restaurants-train-14"
"cs_restaurants-train-14"
"goodbye()"
"goodbye()"
"Děkuji , přeji krásný den ."
"Děkuji , přeji krásný den ."
[]
"cs_restaurants-train-15"
"cs_restaurants-train-15"
"inform(good_for_meal='lunch or dinner',kids_allowed=yes,name='Café Kampus')"
"inform(good_for_meal=X-good_for_meal,kids_allowed=yes,name=X-name)"
"Restaurace X-name se hodí na X-good_for_meal a je vhodná pro děti ."
"Restaurace Café Kampus se hodí na oběd i večeři a je vhodná pro děti ."
[]
"cs_restaurants-train-16"
"cs_restaurants-train-16"
"goodbye()"
"goodbye()"
"Ráda jsem pomohla . Na shledanou ."
"Ráda jsem pomohla . Na shledanou ."
[]
"cs_restaurants-train-17"
"cs_restaurants-train-17"
"inform(name=BarBar,type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Pěkná restaurace je třeba X-name ."
"Pěkná restaurace je třeba BarBar ."
[]
"cs_restaurants-train-18"
"cs_restaurants-train-18"
"goodbye()"
"goodbye()"
"Není zač ."
"Není zač ."
[]
"cs_restaurants-train-19"
"cs_restaurants-train-19"
"inform(address='Štefánikova 8',area=Dejvice,name='Baráčnická rychta')"
"inform(address=X-address,area=X-area,name=X-name)"
"Restaurace X-name se nachází na adrese X-address v X-area ."
"Restaurace Baráčnická rychta se nachází na adrese Štefánikova 8 v Dejvicích ."
[]
"cs_restaurants-train-20"
"cs_restaurants-train-20"
"?request(price_range)"
"?request(price_range)"
"Chcete znát jejich cenovou skupinu ?"
"Chcete znát jejich cenovou skupinu ?"
[]
"cs_restaurants-train-21"
"cs_restaurants-train-21"
"inform(name=BarBar,postcode='127 00')"
"inform(name=X-name,postcode=X-postcode)"
"X-name má poštovní směrovací číslo X-postcode ."
"BarBar má poštovní směrovací číslo 127 00 ."
[]
"cs_restaurants-train-22"
"cs_restaurants-train-22"
"inform(address='Karmelitská 50',name=Místo)"
"inform(address=X-address,name=X-name)"
"X-name je v ulici X-address ."
"Místo je v ulici Karmelitské 50 ."
[]
"cs_restaurants-train-23"
"cs_restaurants-train-23"
"inform(name='Café Savoy',type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Jedna z místních restaurací je X-name ."
"Jedna z místních restaurací je Café Savoy ."
[]
"cs_restaurants-train-24"
"cs_restaurants-train-24"
"?request(good_for_meal)"
"?request(good_for_meal)"
"Snídaně , brunch , oběd nebo večeře ?"
"Snídaně , brunch , oběd nebo večeře ?"
[]
"cs_restaurants-train-25"
"cs_restaurants-train-25"
"inform(address='Újezd 21',area=Smíchov,name='Green Spirit')"
"inform(address=X-address,area=X-area,name=X-name)"
"X-name se nachází na X-area na adrese X-address ."
"Green Spirit se nachází na Smíchově na adrese Újezd 21 ."
[]
"cs_restaurants-train-26"
"cs_restaurants-train-26"
"goodbye()"
"goodbye()"
"Dobrý den"
"Dobrý den"
[]
"cs_restaurants-train-27"
"cs_restaurants-train-27"
"?request(price_range)"
"?request(price_range)"
"Jakou si přejete cenovou skupinu ?"
"Jakou si přejete cenovou skupinu ?"
[]
"cs_restaurants-train-28"
"cs_restaurants-train-28"
"?request(price_range)"
"?request(price_range)"
"Jaká cenová kategorie prosím ?"
"Jaká cenová kategorie prosím ?"
[]
"cs_restaurants-train-29"
"cs_restaurants-train-29"
"inform(name='Café Kampus',type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Ano , X-name je krásná restaurace ."
"Ano , Café Kampus je krásná restaurace ."
[]
"cs_restaurants-train-30"
"cs_restaurants-train-30"
"inform(name='Café Kampus',type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Mám zde příjemnou restauraci X-name ."
"Mám zde příjemnou restauraci Café Kampus ."
[]
"cs_restaurants-train-31"
"cs_restaurants-train-31"
"goodbye()"
"goodbye()"
"Na shledanou ."
"Na shledanou ."
[]
"cs_restaurants-train-32"
"cs_restaurants-train-32"
"goodbye()"
"goodbye()"
"Děkuji ."
"Děkuji ."
[]
"cs_restaurants-train-33"
"cs_restaurants-train-33"
"inform(good_for_meal=dinner,kids_allowed=yes,name='Kočár z Vídně')"
"inform(good_for_meal=X-good_for_meal,kids_allowed=yes,name=X-name)"
"Restaurace X-name nabízí X-good_for_meal a je vhodná pro děti ."
"Restaurace Kočár z Vídně nabízí večeře a je vhodná pro děti ."
[]
"cs_restaurants-train-34"
"cs_restaurants-train-34"
"goodbye()"
"goodbye()"
"Mějte se ."
"Mějte se ."
[]
"cs_restaurants-train-35"
"cs_restaurants-train-35"
"inform(address='Malostranské náměstí 49',name='U Tučňáků')"
"inform(address=X-address,name=X-name)"
"Adresa podniku X-name je X-address"
"Adresa podniku U Tučňáků je Malostranské náměstí 49"
[]
"cs_restaurants-train-36"
"cs_restaurants-train-36"
"?request(price_range)"
"?request(price_range)"
"Můžu se zeptat , jakou cenovou kategorii hledáte ?"
"Můžu se zeptat , jakou cenovou kategorii hledáte ?"
[]
"cs_restaurants-train-37"
"cs_restaurants-train-37"
"inform(area=Vinohrady,name=Ananta)"
"inform(area=X-area,name=X-name)"
"Restaurace X-name se nachází v lokalitě X-area ."
"Restaurace Ananta se nachází v lokalitě Vinohrad ."
[]
"cs_restaurants-train-38"
"cs_restaurants-train-38"
"goodbye()"
"goodbye()"
"Dobrý den"
"Dobrý den"
[]
"cs_restaurants-train-39"
"cs_restaurants-train-39"
"?request(near)"
"?request(near)"
"Poblíž jaké lokality hledáte ?"
"Poblíž jaké lokality hledáte ?"
[]
"cs_restaurants-train-40"
"cs_restaurants-train-40"
"goodbye()"
"goodbye()"
"Není zač ."
"Není zač ."
[]
"cs_restaurants-train-41"
"cs_restaurants-train-41"
"inform(food=Czech,kids_allowed=yes,name='Švejk Restaurant',near='TV Tower')"
"inform(food=X-food,kids_allowed=yes,name=X-name,near=X-near)"
"X-name je X-food restaurace poblíž X-near , možné jsou i návštěvy s dětmi ."
"Švejk Restaurant je česká restaurace poblíž televizní věže , možné jsou i návštěvy s dětmi ."
[]
"cs_restaurants-train-42"
"cs_restaurants-train-42"
"inform_no_match(area=Karlín,kids_allowed=yes)"
"inform_no_match(area=X-area,kids_allowed=yes)"
"Bohužel v X-area nejsou restaurace , které jsou vhodné pro návštěvu s dětmi ."
"Bohužel v Karlíně nejsou restaurace , které jsou vhodné pro návštěvu s dětmi ."
[]
"cs_restaurants-train-43"
"cs_restaurants-train-43"
"inform(area=Hradčany,name='Café Kampus')"
"inform(area=X-area,name=X-name)"
"X-name leží v okolí X-area ."
"Café Kampus leží v okolí Hradčan ."
[]
"cs_restaurants-train-44"
"cs_restaurants-train-44"
"?request(good_for_meal)"
"?request(good_for_meal)"
"Přejete si snídani , brunch , oběd nebo večeři ?"
"Přejete si snídani , brunch , oběd nebo večeři ?"
[]
"cs_restaurants-train-45"
"cs_restaurants-train-45"
"?reqmore()"
"?reqmore()"
"Mohu Vám pomoci s něčím dalším ?"
"Mohu Vám pomoci s něčím dalším ?"
[]
"cs_restaurants-train-46"
"cs_restaurants-train-46"
"goodbye()"
"goodbye()"
"Na shledanou"
"Na shledanou"
[]
"cs_restaurants-train-47"
"cs_restaurants-train-47"
"inform(name=Ferdinanda,type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Další restaurací je X-name ."
"Další restaurací je Ferdinanda ."
[]
"cs_restaurants-train-48"
"cs_restaurants-train-48"
"inform(count=89,good_for_meal=dinner,kids_allowed=yes,type=restaurant)"
"inform(count=X-count,good_for_meal=X-good_for_meal,kids_allowed=yes,type=restaurant)"
"Nabízí se X-count restaurací , kde mají dobré X-good_for_meal a povolený vstup s dětmi ."
"Nabízí se 89 restaurací , kde mají dobré večeře a povolený vstup s dětmi ."
[]
"cs_restaurants-train-49"
"cs_restaurants-train-49"
"goodbye()"
"goodbye()"
"Na shledanou , přeji Vám krásný den ."
"Na shledanou , přeji Vám krásný den ."
[]
"cs_restaurants-train-50"
"cs_restaurants-train-50"
"inform(food=Turkish,name='Baráčnická rychta')"
"inform(food=X-food,name=X-name)"
"X-name je X-food restaurace"
"Baráčnická rychta je turecká restaurace"
[]
"cs_restaurants-train-51"
"cs_restaurants-train-51"
"?request(price_range)"
"?request(price_range)"
"Kolik plánujete utratit peněz ?"
"Kolik plánujete utratit peněz ?"
[]
"cs_restaurants-train-52"
"cs_restaurants-train-52"
"?select(kids_allowed='yes or no')"
"?select(kids_allowed='yes or no')"
"Chtěli byste , aby byla restaurace vhodná i pro děti ?"
"Chtěli byste , aby byla restaurace vhodná i pro děti ?"
[]
"cs_restaurants-train-53"
"cs_restaurants-train-53"
"goodbye()"
"goodbye()"
"Děkuji za zavolání . Na shledanou ."
"Děkuji za zavolání . Na shledanou ."
[]
"cs_restaurants-train-54"
"cs_restaurants-train-54"
"goodbye()"
"goodbye()"
"Na shledanou ."
"Na shledanou ."
[]
"cs_restaurants-train-55"
"cs_restaurants-train-55"
"inform(good_for_meal=dinner,kids_allowed=yes,name='Baráčnická rychta')"
"inform(good_for_meal=X-good_for_meal,kids_allowed=yes,name=X-name)"
"X-name je dobré místo na X-good_for_meal a hodí se pro děti ."
"Baráčnická rychta je dobré místo na večeři a hodí se pro děti ."
[]
"cs_restaurants-train-56"
"cs_restaurants-train-56"
"goodbye()"
"goodbye()"
"Na shledanou , mějte se ."
"Na shledanou , mějte se ."
[]
"cs_restaurants-train-57"
"cs_restaurants-train-57"
"?request(near)"
"?request(near)"
"Poblíž čeho to má být ?"
"Poblíž čeho to má být ?"
[]
"cs_restaurants-train-58"
"cs_restaurants-train-58"
"goodbye()"
"goodbye()"
"Na shledanou a hezký den ."
"Na shledanou a hezký den ."
[]
"cs_restaurants-train-59"
"cs_restaurants-train-59"
"inform(area=Vinohrady,kids_allowed=yes,name='Green Spirit',price_range=moderate)"
"inform(area=X-area,kids_allowed=yes,name=X-name,price_range=X-price_range)"
"X-name vaří za X-price_range ceny , povoluje děti a nachází se na X-area ."
"Green Spirit vaří za průměrné ceny , povoluje děti a nachází se na Vinohradech ."
[]
"cs_restaurants-train-60"
"cs_restaurants-train-60"
"?confirm(food=German)"
"?confirm(food=X-food)"
"Mohu se ujistit , že jste si vybral X-food kuchyni ?"
"Mohu se ujistit , že jste si vybral německou kuchyni ?"
[]
"cs_restaurants-train-61"
"cs_restaurants-train-61"
"goodbye()"
"goodbye()"
"Děkuji vám . Na shledanou ."
"Děkuji vám . Na shledanou ."
[]
"cs_restaurants-train-62"
"cs_restaurants-train-62"
"inform(name='U Konšelů',type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Našla jsem restauraci X-name , která splňuje , co hledáte ."
"Našla jsem restauraci U Konšelů , která splňuje , co hledáte ."
[]
"cs_restaurants-train-63"
"cs_restaurants-train-63"
"inform(address='Štefánikova 8',name='U Tučňáků')"
"inform(address=X-address,name=X-name)"
"Adresa restaurace X-name je ulice X-address ."
"Adresa restaurace U Tučňáků je ulice Štefánikova 8 ."
[]
"cs_restaurants-train-64"
"cs_restaurants-train-64"
"?request(price_range)"
"?request(price_range)"
"Jakou máte cenovou představu ?"
"Jakou máte cenovou představu ?"
[]
"cs_restaurants-train-65"
"cs_restaurants-train-65"
"inform(kids_allowed=yes,name='Švejk Restaurant')"
"inform(kids_allowed=yes,name=X-name)"
"X-name je dobrá restaurace , kde je povolen vstup s dětmi ."
"Restaurace Švejk je dobrá restaurace , kde je povolen vstup s dětmi ."
[]
"cs_restaurants-train-66"
"cs_restaurants-train-66"
"goodbye()"
"goodbye()"
"Děkuji vám . Na shledanou ."
"Děkuji vám . Na shledanou ."
[]
"cs_restaurants-train-67"
"cs_restaurants-train-67"
"inform(food=vegetarian,name='U Tučňáků')"
"inform(food=X-food,name=X-name)"
"V restauraci X-name připravují X-food jídla ."
"V restauraci U Tučňáků připravují vegetariánská jídla ."
[]
"cs_restaurants-train-68"
"cs_restaurants-train-68"
"inform(food=American,name='Kočár z Vídně',near='Wenceslas Square')"
"inform(food=X-food,name=X-name,near=X-near)"
"V restauraci X-name poblíž X-near podávají X-food jídla ."
"V restauraci Kočár z Vídně poblíž Václavského náměstí podávají americká jídla ."
[]
"cs_restaurants-train-69"
"cs_restaurants-train-69"
"inform(good_for_meal=lunch,name='Café Savoy',near='Wenceslas Square')"
"inform(good_for_meal=X-good_for_meal,name=X-name,near=X-near)"
"X-name se nachází blízko X-near a můžete se zde dobře X-good_for_meal ."
"Café Savoy se nachází blízko Václavskému náměstí a můžete se zde dobře naobědvat ."
[]
"cs_restaurants-train-70"
"cs_restaurants-train-70"
"inform(kids_allowed=yes,name=Místo,price_range=cheap)"
"inform(kids_allowed=yes,name=X-name,price_range=X-price_range)"
"X-name nabízí X-price_range jídla a povoluje vstup dětem ."
"Místo nabízí levná jídla a povoluje vstup dětem ."
[]
"cs_restaurants-train-71"
"cs_restaurants-train-71"
"inform(address='Kaprova 36',name='Pivo & Basilico')"
"inform(address=X-address,name=X-name)"
"Restaurace X-name sídlí na adrese X-address ."
"Restaurace Pivo & Basilico sídlí na adrese Kaprova 36 ."
[]
"cs_restaurants-train-72"
"cs_restaurants-train-72"
"inform(name='Green Spirit',near='Charles Bridge',price_range=cheap)"
"inform(name=X-name,near=X-near,price_range=X-price_range)"
"X-name se nachází poblíž X-near a patří mezi X-price_range restaurace ."
"Green Spirit se nachází poblíž Karlova mostu a patří mezi levné restaurace ."
[]
"cs_restaurants-train-73"
"cs_restaurants-train-73"
"?confirm(food=dont_care)"
"?confirm(food=dont_care)"
"Záleží vám na tom , jaké jídlo servírují ?"
"Záleží vám na tom , jaké jídlo servírují ?"
[]
"cs_restaurants-train-74"
"cs_restaurants-train-74"
"inform(name=Místo,type=restaurant)"
"inform(name=X-name,type=restaurant)"
"X-name je název restaurace"
"Místo je název restaurace"
[]
"cs_restaurants-train-75"
"cs_restaurants-train-75"
"inform(good_for_meal=dinner,kids_allowed=no,name='Baráčnická rychta',near='Old Town Square')"
"inform(good_for_meal=X-good_for_meal,kids_allowed=no,name=X-name,near=X-near)"
"X-name leží nedaleko X-near . Dobře se zde X-good_for_meal a není přístupná pro děti ."
"Baráčnická rychta leží nedaleko Staroměstského náměstí . Dobře se zde navečeříte a není přístupná pro děti ."
[]
"cs_restaurants-train-76"
"cs_restaurants-train-76"
"goodbye()"
"goodbye()"
"Jste určitě vítáni !"
"Jste určitě vítáni !"
[]
"cs_restaurants-train-77"
"cs_restaurants-train-77"
"inform(count=54,good_for_meal=dont_care,type=restaurant)"
"inform(count=X-count,good_for_meal=dont_care,type=restaurant)"
"V nabídce je X-count restaurací , které nabízí všechny druhy jídel ."
"V nabídce je 54 restaurací , které nabízí všechny druhy jídel ."
[]
"cs_restaurants-train-78"
"cs_restaurants-train-78"
"inform(count=12,good_for_meal=lunch,price_range=moderate,type=restaurant)"
"inform(count=X-count,good_for_meal=X-good_for_meal,price_range=X-price_range,type=restaurant)"
"Našla jsme X-count restaurací , které jsou dobré na X-good_for_meal a X-price_range ."
"Našla jsme 12 restaurací , které jsou dobré na oběd a středně drahé ."
[]
"cs_restaurants-train-79"
"cs_restaurants-train-79"
"?reqmore()"
"?reqmore()"
"Potřebujete ještě něco ?"
"Potřebujete ještě něco ?"
[]
"cs_restaurants-train-80"
"cs_restaurants-train-80"
"goodbye()"
"goodbye()"
"Není za co , na shledanou ."
"Není za co , na shledanou ."
[]
"cs_restaurants-train-81"
"cs_restaurants-train-81"
"inform(kids_allowed=no,name=Místo,price_range=expensive)"
"inform(kids_allowed=no,name=X-name,price_range=X-price_range)"
"Je tu pěkná , X-price_range restaurace X-name , která není přístupná dětem ."
"Je tu pěkná , drahá restaurace Místo , která není přístupná dětem ."
[]
"cs_restaurants-train-82"
"cs_restaurants-train-82"
"inform(address='Tržiště 30',name='Kočár z Vídně')"
"inform(address=X-address,name=X-name)"
"Adresa X-name zní X-address ."
"Adresa Kočáru z Vídně zní Tržiště 30 ."
[]
"cs_restaurants-train-83"
"cs_restaurants-train-83"
"goodbye()"
"goodbye()"
"Není za co ! Na shledanou ."
"Není za co ! Na shledanou ."
[]
"cs_restaurants-train-84"
"cs_restaurants-train-84"
"?request(price_range)"
"?request(price_range)"
"Jakou cenovou kategorii byste si přáli ?"
"Jakou cenovou kategorii byste si přáli ?"
[]
"cs_restaurants-train-85"
"cs_restaurants-train-85"
"goodbye()"
"goodbye()"
"Dobrý den"
"Dobrý den"
[]
"cs_restaurants-train-86"
"cs_restaurants-train-86"
"goodbye()"
"goodbye()"
"Rádo se stalo . Na shledanou ."
"Rádo se stalo . Na shledanou ."
[]
"cs_restaurants-train-87"
"cs_restaurants-train-87"
"inform(food=Asian,good_for_meal=lunch,name=Ananta)"
"inform(food=X-food,good_for_meal=X-good_for_meal,name=X-name)"
"Nabízí se restaurace X-name , dobré místo na X-good_for_meal , kde podávají X-food jídla ."
"Nabízí se restaurace Ananta , dobré místo na oběd , kde podávají asijská jídla ."
[]
"cs_restaurants-train-88"
"cs_restaurants-train-88"
"?request(near)"
"?request(near)"
"Poblíž čeho to je ?"
"Poblíž čeho to je ?"
[]
"cs_restaurants-train-89"
"cs_restaurants-train-89"
"inform(name=BarBar,type=restaurant)"
"inform(name=X-name,type=restaurant)"
"Mám tu restauraci X-name ."
"Mám tu restauraci BarBar ."
[]
"cs_restaurants-train-90"
"cs_restaurants-train-90"
"inform(kids_allowed=yes,name='Švejk Restaurant')"
"inform(kids_allowed=yes,name=X-name)"
"X-name je vegetariánská a vaří i pro děti ."
"Restaurace Švejk je vegetariánská a vaří i pro děti ."
[]
"cs_restaurants-train-91"
"cs_restaurants-train-91"
"inform(name='Baráčnická rychta',postcode='159 00')"
"inform(name=X-name,postcode=X-postcode)"
"X-name má poštovní směrovací číslo X-postcode ."
"Baráčnická rychta má poštovní směrovací číslo 159 00 ."
[]
"cs_restaurants-train-92"
"cs_restaurants-train-92"
"inform(name='Švejk Restaurant',postcode='143 00')"
"inform(name=X-name,postcode=X-postcode)"
"X-name má poštovní směrovací číslo X-postcode ."
"Restaurace Švejk má poštovní směrovací číslo 143 00 ."
[]
"cs_restaurants-train-93"
"cs_restaurants-train-93"
"inform(address='Karmelitská 42',name='Švejk Restaurant',phone=265745239,postcode='167 00')"
"inform(address=X-address,name=X-name,phone=X-phone,postcode=X-postcode)"
"Adresa X-name je X-address , telefonní číslo je X-phone a poštovní směrovací číslo je X-postcode ."
"Adresa restaurace Švejk je Karmelitská 42 , telefonní číslo je 265745239 a poštovní směrovací číslo je 167 00 ."
[]
"cs_restaurants-train-94"
"cs_restaurants-train-94"
"inform(count=2,good_for_meal=brunch,type=restaurant)"
"inform(count=X-count,good_for_meal=X-good_for_meal,type=restaurant)"
"V nabídce jsou X-count restaurace dobré pro X-good_for_meal ."
"V nabídce jsou 2 restaurace dobré pro pozdní snídaně ."
[]
"cs_restaurants-train-95"
"cs_restaurants-train-95"
"inform(address='Újezd 14',name='Švejk Restaurant')"
"inform(address=X-address,name=X-name)"
"X-name najdete na adrese X-address"
"Restauraci Švejk najdete na adrese Újezd 14"
[]
"cs_restaurants-train-96"
"cs_restaurants-train-96"
"inform(name='Kočár z Vídně',type=restaurant)"
"inform(name=X-name,type=restaurant)"
"X-name je restaurace"
"Kočár z Vídně je restaurace"
[]
"cs_restaurants-train-97"
"cs_restaurants-train-97"
"goodbye()"
"goodbye()"
"Na shledanou , přeji krásný den ."
"Na shledanou , přeji krásný den ."
[]
"cs_restaurants-train-98"
"cs_restaurants-train-98"
"inform(name='Pivo & Basilico',near='TV Tower',price_range=cheap)"
"inform(name=X-name,near=X-near,price_range=X-price_range)"
"X-name v blízkosti X-near je za X-price_range ceny ."
"Pivo & Basilico v blízkosti televizního vysílače je za nízké ceny ."
[]
"cs_restaurants-train-99"
"cs_restaurants-train-99"
"inform(area=Žižkov,name=Ferdinanda)"
"inform(area=X-area,name=X-name)"
"X-name leží na X-area ."
"Ferdinanda leží na Žižkově ."
[]
End of preview (truncated to 100 rows)

Dataset Card for GEM/cs_restaurants

Link to Main Data Card

You can find the main data card on the GEM Website.

Dataset Summary

The Czech Restaurants dataset is a task oriented dialog dataset in which a model needs to verbalize a response that a service agent could provide which is specified through a series of dialog acts. The dataset originated as a translation of an English dataset to test the generation capabilities of an NLG system on a highly morphologically rich language like Czech.

You can load the dataset via:

import datasets
data = datasets.load_dataset('GEM/cs_restaurants')

The data loader can be found here.

website

n/a

paper

Github

authors

Ondrej Dusek and Filip Jurcicek

Dataset Overview

Where to find the Data and its Documentation

Download

Github

Paper

Github

BibTex

@inproceedings{cs_restaurants,
    address = {Tokyo, Japan},
    title = {Neural {Generation} for {Czech}: {Data} and {Baselines}},
    shorttitle = {Neural {Generation} for {Czech}},
    url = {https://www.aclweb.org/anthology/W19-8670/},
    urldate = {2019-10-18},
    booktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},
    author = {Dušek, Ondřej and Jurčíček, Filip},
    month = oct,
    year = {2019},
    pages = {563--574},
}

Contact Name

Ondrej Dusek

Contact Email

odusek@ufal.mff.cuni.cz

Has a Leaderboard?

no

Languages and Intended Use

Multilingual?

no

Covered Dialects

No breakdown of dialects is provided.

Covered Languages

Czech

Whose Language?

Six professional translators produced the outputs

License

cc-by-sa-4.0: Creative Commons Attribution Share Alike 4.0 International

Intended Use

The dataset was created to test neural NLG systems in Czech and their ability to deal with rich morphology.

Primary Task

Dialog Response Generation

Communicative Goal

Producing a text expressing the given intent/dialogue act and all and only the attributes specified in the input meaning representation.

Credit

Curation Organization Type(s)

academic

Curation Organization(s)

Charles University, Prague

Dataset Creators

Ondrej Dusek and Filip Jurcicek

Funding

This research was supported by the Charles University project PRIMUS/19/SCI/10 and by the Ministry of Education, Youth and Sports of the Czech Republic under the grant agreement LK11221. This work used using language resources distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).

Who added the Dataset to GEM?

Simon Mille wrote the initial data card and Yacine Jernite the data loader. Sebastian Gehrmann migrated the data card and loader to the v2 format.

Dataset Structure

Data Fields

The data is stored in a JSON or CSV format, with identical contents. The data has 4 fields:

  • da: the input meaning representation/dialogue act (MR)
  • delex_da: the input MR, delexicalized -- all slot values are replaced with placeholders, such as X-name
  • text: the corresponding target natural language text (reference)
  • delex_text: the target text, delexicalized (delexicalization is applied regardless of inflection)

In addition, the data contains a JSON file with all possible inflected forms for all slot values in the dataset (surface_forms.json). Each slot -> value entry contains a list of inflected forms for the given value, with the base form (lemma), the inflected form, and a morphological tag.

The same MR is often repeated multiple times with different synonymous reference texts.

Reason for Structure

The data originated as a translation and localization of Wen et al.'s SF restaurant NLG dataset.

How were labels chosen?

The input MRs were collected from Wen et al.'s SF restaurant NLG data and localized by randomly replacing slot values (using a list of Prague restaurant names, neighborhoods etc.).

The generated slot values were then automatically replaced in reference texts in the data.

Example Instance

{
  "input": "inform_only_match(food=Turkish,name='Švejk Restaurant',near='Charles Bridge',price_range=cheap)",
  "target": "Našla jsem pouze jednu levnou restauraci poblíž Karlova mostu , kde podávají tureckou kuchyni , Švejk Restaurant ."
}

Data Splits

Property Value
Total instances 5,192
Unique MRs 2,417
Unique delexicalized instances 2,752
Unique delexicalized MRs 248

The data is split in a roughly 3:1:1 proportion into training, development and test sections, making sure no delexicalized MR appears in two different parts. On the other hand, most DA types/intents are represented in all data parts.

Splitting Criteria

The creators ensured that after delexicalization of the meaning representation there was no overlap between training and test.

The data is split at a 3:1:1 rate between training, validation, and test.

Dataset in GEM

Rationale for Inclusion in GEM

Why is the Dataset in GEM?

This is one of a few non-English data-to-text datasets, in a well-known domain, but covering a morphologically rich language that is harder to generate since named entities need to be inflected. This makes it harder to apply common techniques such as delexicalization or copy mechanisms.

Similar Datasets

yes

Unique Language Coverage

yes

Difference from other GEM datasets

The dialog acts in this dataset are much more varied than the e2e dataset which is the closest in style.

Ability that the Dataset measures

surface realization

GEM-Specific Curation

Modificatied for GEM?

yes

Additional Splits?

yes

Split Information

5 challenge sets for the Czech Restaurants dataset were added to the GEM evaluation suite.

  1. Data shift: We created subsets of the training and development sets of 500 randomly selected inputs each.
  2. Scrambling: We applied input scrambling on a subset of 500 randomly selected test instances; the order of the input dialogue acts was randomly reassigned.
  3. We identified different subsets of the test set that we could compare to each other so that we would have a better understanding of the results. There are currently two selections that we have made:

The first comparison is based on input size: the number of predicates differs between different inputs, ranging from 1 to 5. The table below provides an indication of the distribution of inputs with a particular length. It is clear from the table that this distribution is not balanced, and comparisions between items should be done with caution. Particularly for input size 4 and 5, there may not be enough data to draw reliable conclusions.

Input length Number of inputs
1 183
2 267
3 297
4 86
5 9

The second comparison is based on the type of act. Again we caution against comparing the different groups that have relatively few items. It is probably OK to compare inform and ?request, but the other acts are all low-frequent.

Act Frequency
?request 149
inform 609
?confirm 22
inform_only_match 16
inform_no_match 34
?select 12

Split Motivation

Generalization and robustness.

Getting Started with the Task

Technical Terms

  • utterance: something a system or user may say in a turn
  • meaning representation: a representation of meaning that the system should be in accordance with. The specific type of MR in this dataset are dialog acts which describe what a dialog system should do, e.g., inform a user about a value.

Previous Results

Previous Results

Measured Model Abilities

Surface realization

Metrics

BLEU, ROUGE, METEOR

Proposed Evaluation

This dataset uses the suite of word-overlap-based automatic metrics from the E2E NLG Challenge (BLEU, NIST, ROUGE-L, METEOR, and CIDEr). In addition, the slot error rate is measured.

Previous results available?

no

Dataset Curation

Original Curation

Original Curation Rationale

The dataset was created to test neural NLG systems in Czech and their ability to deal with rich morphology.

Communicative Goal

Producing a text expressing the given intent/dialogue act and all and only the attributes specified in the input MR.

Sourced from Different Sources

no

Language Data

How was Language Data Obtained?

Created for the dataset

Creation Process

Six professional translators translated the underlying dataset with the following instructions:

  • Each utterance should be translated by itself
  • fluent spoken-style Czech should be produced
  • Facts should be preserved
  • If possible, synonyms should be varied to create diverse utterances
  • Entity names should be inflected as necessary
  • the reader of the generated text should be addressed using formal form and self-references should use the female form.

The translators did not have access to the meaning representation.

Data Validation

validated by data curator

Was Data Filtered?

not filtered

Structured Annotations

Additional Annotations?

none

Annotation Service?

no

Consent

Any Consent Policy?

no

Justification for Using the Data

It was not explicitly stated but we can safely assume that the translators agreed to this use of their data.

Private Identifying Information (PII)

Contains PII?

no PII

Justification for no PII

This dataset does not include any information about individuals.

Maintenance

Any Maintenance Plan?

no

Broader Social Context

Previous Work on the Social Impact of the Dataset

Usage of Models based on the Data

no

Impact on Under-Served Communities

Addresses needs of underserved Communities?

yes

Details on how Dataset Addresses the Needs

The dataset may help improve NLG methods for morphologically rich languages beyond Czech.

Discussion of Biases

Any Documented Social Biases?

yes

Links and Summaries of Analysis Work

To ensure consistency of translation, the data always uses formal/polite address for the user, and uses the female form for first-person self-references (as if the dialogue agent producing the sentences was female). This prevents data sparsity and ensures consistent results for systems trained on the dataset, but does not represent all potential situations arising in Czech.

Considerations for Using the Data

PII Risks and Liability

Licenses

Copyright Restrictions on the Dataset

open license - commercial use allowed

Copyright Restrictions on the Language Data

open license - commercial use allowed

Known Technical Limitations

Technical Limitations

The test set may lead users to over-estimate the performance of their NLG systems with respect to their generalisability, because there are no unseen restaurants or addresses in the test set. This is something we will look into for future editions of the GEM shared task.

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