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"PERSON",
"Doussou"
],
"tail": [
"16",
"17",
"GPE",
"France"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"21",
"22",
"GPE",
"Mali"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"27",
"28",
"GPE",
"Uzbekistan"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"42",
"43",
"GPE",
"Mali"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"44",
"45",
"DATE",
"2003"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"59",
"60",
"CARDINAL",
"two"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"62",
"63",
"WORK_OF_ART",
"Kouty"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"64",
"67",
"WORK_OF_ART",
"mémoire de sang"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"75",
"77",
"WORK_OF_ART",
"No Title"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"80",
"81",
"DATE",
"2002"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"88",
"89",
"PERSON",
"Karim"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"90",
"91",
"PERSON",
"Doussou"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
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],
"tail": [
"92",
"93",
"PERSON",
"Karim"
]
}
],
[
{
"head": [
"94",
"95",
"PERSON",
"Doussou"
],
"tail": [
"103",
"104",
"NORP",
"Malian"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"9",
"12",
"PERSON",
"Aïda Mady Diallo"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"16",
"17",
"GPE",
"France"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"21",
"22",
"GPE",
"Mali"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"27",
"28",
"GPE",
"Uzbekistan"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"42",
"43",
"GPE",
"Mali"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"88",
"89",
"PERSON",
"Karim"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"90",
"91",
"PERSON",
"Doussou"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"92",
"93",
"PERSON",
"Karim"
]
}
],
[
{
"head": [
"103",
"104",
"NORP",
"Malian"
],
"tail": [
"94",
"95",
"PERSON",
"Doussou"
]
}
]
] | [
" SPONSOR_OF",
" LOCATION.COUNTRY.PREVIOUS_RESIDENCE.CHILD",
" LOCATION.\n\n Explanation:\n The head entity 'FES",
" SCHOLARSHIP_GRANTOR",
" LOCATION. \n This text describes FESPACO 201",
" EVENT_STARTED_BY\n OR\n CAUSED\n OR\n T",
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" SUBJECT_OF. This is the relationship between the event (FESPACO ",
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" MARRIED_TO",
" MARRIED_TO",
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" SUBJECT_OF. This is the relation between the work of art (No Title) and",
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" MARRIED_TO",
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" PARTICIPANT_IN",
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" ORIGIN_FROM",
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" LIVED_IN",
" MARRIED_WITH\n\n Explanation:\n The text describes Kar",
" CREATED_BY",
" CREATED_BY",
" CREATED_BY",
" WRITTEN_WORK_BY_YEAR\n\n Entities: \n",
" MARRIED_TO",
" MARRIED_TO",
" MARRIED_TO",
" MARRIED_TO\n\n Explanation:\n The text describes Kar",
" HAPPENED_AT",
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" LIVES_IN",
" EDUCATION_AT.\n This relation indicates that Doussou studied at",
" LIVES_IN",
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" CREATED_BY",
" WRITTEN_DATE_OF_NOVEL",
" MARRIED_TO",
" MARRIED_TO",
" MARRIED_TO",
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" ORIGIN_FROM",
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" CREATED_BY",
" WRITTEN_BY",
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" WRITTEN_WORK_BY_YEAR\n OR\n NO_REL",
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" LIVED_IN",
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[
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[
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[
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[
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[
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[
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"91",
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],
[
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"93",
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],
[
"94",
"95",
"PERSON",
"Doussou"
],
[
"103",
"104",
"NORP",
"Malian"
]
] | 600 |
602 | [
"€ 79.99 incl. VAT\nOnly 2 left in stock\nStilinga kepuraitė su snapeliu dekoruota firminiu Agnės Kuzmickaitės drugeliu. Dydis universalus.\n98 proc medvilnė\n2 proc elastanas\nS, M, L\nBlack T-Shirt with white Butterfly print\nBlack Velvet Textile Belt with Lacquered Ribbon\nBlack velvet bow\nBlack jumper with white PUMPS print\nBlack jumper with white BUTTERFLY print\nBlack jumper with white ANKLE BOOTS print\nDue to increased demand your order fulfilment can take up to 10 business days. We are working hard to put in place additional resources as quickly as possible to restore our service standard. Thank you for your kind patience with us. Dismiss\nUsername or email address *\nLost your password?"
] | [
[
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]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['€ 79.99 incl. VAT\nOnly 2 left in stock\nStilinga kepuraitė su snapeliu dekoruota firminiu Agnės Kuzmickaitės drugeliu. Dydis universalus.\n98 proc medvilnė\n2 proc elastanas\nS, M, L\nBlack T-Shirt with white Butterfly print\nBlack Velvet Textile Belt with Lacquered Ribbon\nBlack velvet bow\nBlack jumper with white PUMPS print\nBlack jumper with white BUTTERFLY print\nBlack jumper with white ANKLE BOOTS print\nDue to increased demand your order fulfilment can take up to 10 business days. We are working hard to put in place additional resources as quickly as possible to restore our service standard. Thank you for your kind patience with us. Dismiss\nUsername or email address *\nLost your password?']
Entities:
[{'head': ['1', '2', 'MONEY', '79.99'], 'tail': ['22', '25', 'PERSON', 'Dydis universalus.']}]
Relation:
| [
[
{
"head": [
"1",
"2",
"MONEY",
"79.99"
],
"tail": [
"22",
"25",
"PERSON",
"Dydis universalus."
]
}
],
[
{
"head": [
"7",
"8",
"CARDINAL",
"2"
],
"tail": [
"22",
"25",
"PERSON",
"Dydis universalus."
]
}
],
[
{
"head": [
"22",
"25",
"PERSON",
"Dydis universalus."
],
"tail": [
"1",
"2",
"MONEY",
"79.99"
]
}
],
[
{
"head": [
"22",
"25",
"PERSON",
"Dydis universalus."
],
"tail": [
"7",
"8",
"CARDINAL",
"2"
]
}
],
[
{
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"22",
"25",
"PERSON",
"Dydis universalus."
],
"tail": [
"30",
"31",
"CARDINAL",
"2"
]
}
],
[
{
"head": [
"22",
"25",
"PERSON",
"Dydis universalus."
],
"tail": [
"94",
"97",
"DATE",
"10 business days"
]
}
],
[
{
"head": [
"30",
"31",
"CARDINAL",
"2"
],
"tail": [
"22",
"25",
"PERSON",
"Dydis universalus."
]
}
],
[
{
"head": [
"94",
"97",
"DATE",
"10 business days"
],
"tail": [
"22",
"25",
"PERSON",
"Dydis universalus."
]
}
]
] | [
" PRICE_OF\n\n Explanation:\n The text mentions the price",
" SELLER_OF\n\n Explanation:\n The text mentions that",
" PRICE",
" IN_STOCK_FOR_ENTITY \n (The given entities represent the number",
" IN Stock_Quantity_Of\n or\n Qty_Of_Stocked",
" DELIVERY_TIME",
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] | [
[
"1",
"2",
"MONEY",
"79.99"
],
[
"7",
"8",
"CARDINAL",
"2"
],
[
"22",
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"Dydis universalus."
],
[
"30",
"31",
"CARDINAL",
"2"
],
[
"94",
"97",
"DATE",
"10 business days"
]
] | 601 |
603 | [
"Forty years ago, Ahmed El-Helw fell in love with natural slate. At a Spanish trade show, he watched as skilled craftsmen demonstrated how thinly quality slate can be split and cleaved.\nHe found it fascinating – so fascinating, in fact, that he’d go on to dedicate the next four decades of his life to the same material.\nAhmed founded Spanish Slate Quarries UK Ltd (SSQ for short), and became the first person to bring the finest quality Spanish slate to homeowners and architects around the UK.\nDomiz First Datasheet Download"
] | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Forty years ago, Ahmed El-Helw fell in love with natural slate. At a Spanish trade show, he watched as skilled craftsmen demonstrated how thinly quality slate can be split and cleaved.\nHe found it fascinating – so fascinating, in fact, that he’d go on to dedicate the next four decades of his life to the same material.\nAhmed founded Spanish Slate Quarries UK Ltd (SSQ for short), and became the first person to bring the finest quality Spanish slate to homeowners and architects around the UK.\nDomiz First Datasheet Download']
Entities:
[{'head': ['0', '3', 'DATE', 'Forty years ago'], 'tail': ['4', '8', 'PERSON', 'Ahmed El-Helw']}]
Relation:
| [
[
{
"head": [
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}
],
[
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604 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['[Remark: on Friday 05/06/1964 and Saturday 06/06/1964, the Royal Canadian Air Force flew a Supermarine Spitfire and a Sopwith Snipe (World War 1) plane. The NFB photographed the event.] GROUND TO AIR SHOTs of Spitfire, piloted by flight lieutenant Gerry Billing of RCAF, Trenton, Ontario making passes over Rockcliffe Airport, Ottawa, in full camouflage colours. Shots of Spitfire swooping, barrel rolling. LS of Spitfire landing and taxiing up to camera. Shot of Sopwith Snipe, piloted by wing commander Hartmann of RCAF Uplands, Ontario swooping over camera and over field. Several shots of Snipe sweeping over camera at low level.']
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],
"tail": [
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"113",
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]
}
],
[
{
"head": [
"112",
"113",
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],
"tail": [
"10",
"15",
"ORG",
"the Royal Canadian Air Force"
]
}
],
[
{
"head": [
"112",
"113",
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"Snipe"
],
"tail": [
"31",
"32",
"ORG",
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]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"48",
"50",
"PERSON",
"Gerry Billing"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"51",
"52",
"ORG",
"RCAF"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"53",
"54",
"GPE",
"Trenton"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"55",
"56",
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}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
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],
"tail": [
"62",
"63",
"GPE",
"Ottawa"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"96",
"97",
"PERSON",
"Hartmann"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"98",
"100",
"ORG",
"RCAF Uplands"
]
}
],
[
{
"head": [
"112",
"113",
"PRODUCT",
"Snipe"
],
"tail": [
"101",
"102",
"GPE",
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}
]
] | [
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" PHOTOGRAPHED",
" FLEW\n\n Entities: \n [{'head': ['48",
" FLEW_FOR\n\n Explanation:\n The text states that the",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" FLEW_WITH\n\n Explanation:\n The text states that Hart",
" MEMBER_OF",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
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" PHOTOGRAPHED",
" FLEW_ON\n\n Explanation:\n The text states that Ger",
" FLEW_FOR\n\n Explanation:\n The text states that \"",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" FLEW_ON\n\n Explanation:\n The text states that Hart",
" FLEW_FOR\n\n Explanation:\n The text states that \"",
" LOCATION",
" FLEW_ON\n\n Entities: \n [{'head': ['",
" FLEW_ON\n\n Explanation:\n The text states that \"",
" FLEW",
" OWNED_BY",
" FLEW_IN_WAR_EVENT\n\n Entities: \n [",
" PHOTOGRAPHED",
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" FLEW_FOR\n\n Explanation:\n The text states that \"",
" MENTIONED_BY",
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" BASED_IN",
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" FLEW",
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" FLEW_WITH",
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" BELONGS_TO",
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" PHOTOGRAPHED",
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" FLEW_FROM",
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" FLEW_OVER",
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" FLEW_ON\n\n Entities: \n [{'head': ['",
" FLEW_ON\n\n Explanation:\n Gerry Billing flew",
" PILOT_OF\n\n Entities: \n [{'head': ['1",
" PILOTS\n\n Entities: \n [{'head': ['16",
" FLEW_OVER",
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" PHOTOGRAPHED",
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" FLIES_FROM\n\n Explanation:\n Gerry Billing flies from",
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" FLEW_OVER",
" PILOTS\n\n Entities: \n [{'head': ['48",
" PILOTS\n\n Entities: \n [{'head': ['53",
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" PILOTS_OF\n\n Explanation:\n Gerry Billing is",
" FLIES_FROM\n\n Entities: \n [{'head': ['",
" PILOT_OF",
" FLEW_ON\n\n Entities: \n [{'head': ['",
" FLEW_ON\n\n Explanation:\n The text states that the",
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" PHOTOGRAPHED",
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" LOCATION_AT_TIME",
" BELONGS_TO",
" FLEW_OVER\n\n Entities: \n [{'head':",
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" PHOTOGRAPHED",
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" LOCATION_OF\n\n Entities: \n [{'head': ['",
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" FLIGHT_FROM",
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" FLIES\n\n Entities: \n [{'head': ['79',",
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" LOCATION_AT_TIME",
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" PHOTOGRAPHED",
" FLEW_OVER",
" FLEW_FOR\n\n Explanation:\n The text states that '",
" BELONGS_TO",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
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" NEAR_LOCATION",
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" FLEW_OVER",
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" NEAR.",
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" LOCATION_AT_TIME",
" LOCATION_AT_TIME",
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" FLEW_OVER",
" BACKGROUND_OF\n\n Explanation:\n The text describes the",
" PHOTOGRAPHED",
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" FLIES_OVER",
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" FLIGHT_FROM",
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" NEAR.",
" NEAR\n\n Explanation:\n The text describes the Spitfire plane",
" NEAR\n\n Explanation:\n The text describes the Spitfire plane",
" FLEW_OVER",
" FLIES_OVER",
" FLIES_FOR\n\n Explanation:\n The text describes that Wing",
" NEAR_LOCATION",
" FLEW_OVER",
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" PILOT",
" FLEW_FOR\n\n Explanation:\n The text states that the",
" FLEW_FROM",
" FLEW_OVER",
" FLEW_OVER",
" FLIES_OVER",
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" FLEW_FOR\n\n Explanation:\n The text states that the",
" FLEW_FROM",
" FLEW_OVER",
" FLEW_OVER",
" FLIES_OVER",
" PILOTS_OF\n\n Explanation:\n The text states that '",
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" PHOTOGRAPHED",
" PILOT",
" OWNED_BY",
" BASED_IN",
" BELONGS_TO",
" FLEW_OVER",
" FLIES\n\n Explanation:\n The text states that \"Wing",
" PILOTS_FROM\n\n Explanation:\n The text states that '",
" BELONGS_TO",
" FLEW_ON\n\n Explanation:\n The text states that '",
" FLEW_ON\n\n Explanation:\n The text states that \"",
" MEMBER_OF",
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" PILOTS.",
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" PILOT_OF\n\n Explanation:\n The text states that \"wing",
" PILOT_OF",
" PILOT_OF",
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" BELONGS_TO",
" FLIES_FROM\n\n Explanation:\n The text states that 'wing",
" FLEW_OVER",
" FLEW_OVER",
" PILOT\n\n Explanation:\n The text states that \"wing commander Hart",
" PILOT\n\n Explanation:\n The text states that 'wing commander Hart",
" PILOTS.",
" PILOTS_OF\n\n Explanation:\n The text states that \"",
" PILOTS_FROM\n\n Entities: \n [{'head': ['",
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" FLEW_ON\n\n Explanation:\n The text states that \"",
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" PILOT_OF",
" PILOTS_OF\n\n Explanation:\n The text states that \"",
" PILOT_OF\n\n Explanation:\n The context states that \"wing",
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" FLEW_BY\n\n Explanation:\n The text states that \"",
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" BASED_IN",
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" BASED_IN",
" PILOTED_BY",
" PILOTED_BY",
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" FLIES\n\n Explanation:\n The text states that \"wing commander",
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" LOCATION_AT.\n\n Explanation:\n The text states that",
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" NEAR.",
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" FLEW_FOR\n\n Explanation:\n The text states that \"",
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" FLIES_FROM\n\n Explanation:\n The text states that \"wing",
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" FLIES\n\n Explanation:\n The text states that \"Wing",
" PILOTS_OF\n\n Explanation:\n The text states that '",
" FLIES_FROM\n\n Explanation:\n The text states that \"wing"
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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] | 604 |
606 | [
"ASPEN COMMISSION ™\nTHE CENTER FOR PHILOSOPHY POLITICS SPIRITUALITY AND SCIENCE ™\n\"Far better is it to dare mighty things, to win glorious triumphs, even though checkered by failure... than to rank with those poor spirits who neither enjoy nor suffer much, because they live in a gray twilight that knows not victory nor defeat.\n-- Teddy Roosevelt, 26th President of the United States of America\nAspen Commission ™ All Rights Reserved 1996-2024\nIBS INTERNATIONAL BOARD OF STANDARDS\nAspen Commission Academy of International Relations, Philosphy Politics and Innovation - International Political Foregin Relations Public Policy Council. The Aspen Commission ™ is an Association Registered in Colorado and is also a listed as an Limited Company CO USA."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['ASPEN COMMISSION ™\nTHE CENTER FOR PHILOSOPHY POLITICS SPIRITUALITY AND SCIENCE ™\n"Far better is it to dare mighty things, to win glorious triumphs, even though checkered by failure... than to rank with those poor spirits who neither enjoy nor suffer much, because they live in a gray twilight that knows not victory nor defeat.\n-- Teddy Roosevelt, 26th President of the United States of America\nAspen Commission ™ All Rights Reserved 1996-2024\nIBS INTERNATIONAL BOARD OF STANDARDS\nAspen Commission Academy of International Relations, Philosphy Politics and Innovation - International Political Foregin Relations Public Policy Council. The Aspen Commission ™ is an Association Registered in Colorado and is also a listed as an Limited Company CO USA.']
Entities:
[{'head': ['0', '2', 'ORG', 'ASPEN COMMISSION'], 'tail': ['65', '67', 'PERSON', 'Teddy Roosevelt']}]
Relation:
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}
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}
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[
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[
{
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[
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[
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[
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}
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[
{
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}
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[
{
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}
],
[
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"tail": [
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}
],
[
{
"head": [
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"tail": [
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"114",
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}
],
[
{
"head": [
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"tail": [
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"2",
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}
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[
{
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"108",
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"tail": [
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}
],
[
{
"head": [
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"108",
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"tail": [
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"8",
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}
],
[
{
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}
],
[
{
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"tail": [
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"14",
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]
}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
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"26",
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}
],
[
{
"head": [
"107",
"108",
"GPE",
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],
"tail": [
"44",
"51",
"ORG",
"the Agricultural and Mechanical College of Alabama"
]
}
],
[
{
"head": [
"107",
"108",
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],
"tail": [
"53",
"55",
"ORG",
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}
],
[
{
"head": [
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"108",
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"tail": [
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"58",
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"1895"
]
}
],
[
{
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"108",
"GPE",
"Opelika"
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"tail": [
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"60",
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"1899"
]
}
],
[
{
"head": [
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"108",
"GPE",
"Opelika"
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"tail": [
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"72",
"ORG",
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]
}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
"77",
"78",
"GPE",
"Auburn"
]
}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
"81",
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"Opelika"
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}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
"86",
"87",
"GPE",
"Auburn"
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}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
"90",
"91",
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}
],
[
{
"head": [
"107",
"108",
"GPE",
"Opelika"
],
"tail": [
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"GPE",
"Auburn"
]
}
],
[
{
"head": [
"107",
"108",
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],
"tail": [
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"114",
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}
],
[
{
"head": [
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"114",
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],
"tail": [
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"PERSON",
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}
],
[
{
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"114",
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],
"tail": [
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]
}
],
[
{
"head": [
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"114",
"GPE",
"Auburn"
],
"tail": [
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}
],
[
{
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"114",
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"tail": [
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}
],
[
{
"head": [
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"114",
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"tail": [
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}
],
[
{
"head": [
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"114",
"GPE",
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"tail": [
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]
}
],
[
{
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"114",
"GPE",
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],
"tail": [
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"51",
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"the Agricultural and Mechanical College of Alabama"
]
}
],
[
{
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"114",
"GPE",
"Auburn"
],
"tail": [
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"ORG",
"Auburn University"
]
}
],
[
{
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"114",
"GPE",
"Auburn"
],
"tail": [
"57",
"58",
"DATE",
"1895"
]
}
],
[
{
"head": [
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"114",
"GPE",
"Auburn"
],
"tail": [
"59",
"60",
"DATE",
"1899"
]
}
],
[
{
"head": [
"113",
"114",
"GPE",
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],
"tail": [
"69",
"72",
"ORG",
"Berkshire Hathaway HomeServices"
]
}
],
[
{
"head": [
"113",
"114",
"GPE",
"Auburn"
],
"tail": [
"77",
"78",
"GPE",
"Auburn"
]
}
],
[
{
"head": [
"113",
"114",
"GPE",
"Auburn"
],
"tail": [
"81",
"82",
"GPE",
"Opelika"
]
}
],
[
{
"head": [
"113",
"114",
"GPE",
"Auburn"
],
"tail": [
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"GPE",
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]
}
],
[
{
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],
"tail": [
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}
],
[
{
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"Auburn"
],
"tail": [
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}
],
[
{
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"114",
"GPE",
"Auburn"
],
"tail": [
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}
]
] | [
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" SELF_REFERENCE",
" SELF_REFERENCE",
" BIRTH_YEARS",
" 'PERSON_IS_CREDITED_WITH'",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_UNTIL",
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" COACHED_AT",
" MOVE_TO",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" MOVE_TO",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" NO_RELATION",
" UNIVERSITY_OF_AFFILIATION",
" COACHED_AT",
" SAME_ORGANIZATION",
" COACHED_AT",
" COACHED_AT",
" REAL_ESTATE_AGENCY_OF\n\n Explanation:\n",
" LOCATED_IN",
" NEAR_CITY",
" LOCATION.IN.ORGANIZATION",
" LOCATION.IN.ORGANIZATION",
" LOCATION",
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" COACHED_AT",
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" LIVES_NEARBY",
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" COACHED_AT",
" MOVE_TO",
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" SELF_REFERENCE",
" BIRTH_DATE",
" IS_CREDITED_WITH.",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" LEFT_OF\n\n Explanation:\n The text states that John He",
" ASSOCIATED_WITH",
" COACHED_AT",
" LIVES_NEARBY",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
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" BIRTH_YEARS",
" COACHED_AT",
" BIRTH_YEARS",
" BIRTH_YEARS",
" COACHED_AT",
" COACHED_AT",
" FORMER_EMPLOYER",
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" NO_RELATION",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" MOVED_TO",
" COACHED_AT",
" COCREATED_WITH",
" 'AMONG'\n or\n 'CREDITED_WITH'\n ",
" COCREATED_WITH\n or\n KNOWN_FOR\n or\n ",
" COCREATED_WITH",
" COACHED_AT",
" 'AMONG'\n or\n 'CREDITED_WITH'\n ",
" ORG_FOUNDED_BY_PERSON",
" COUNTRY_OF_ORIGIN_OR_BIRTHPLACE_OF",
" NEAR_CITY",
" COUNTRY_OF_ORIGIN_OR_BIRTHPLACE_OF",
" COUNTRY_OF_ORIGIN_OR_BIRTHPLACE_OF",
" COUNTRY_OF_ORIGIN_OR_BIRTHPLACE_OF",
" NEAR_CITY",
" COUNTRY_OF_ORIGIN_OR_BIRTHPLACE_OF",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_FOR\n Or, if no relation exists:\n NO_REL",
" COACHED_AT",
" COACHED_AT",
" COACHED_UNTIL",
" REAL_ESTATE_AGENCY_OF\n\n Explanation:\n",
" COACHED_AT",
" NEAR_CITY",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" NEAR_CITY",
" COACHED_AT",
" COACHED_AT",
" UNIVERSITY_OF\n or\n ORGANIZATION_OF\n",
" COACHED_AT",
" COACHED_AT",
" EDUCATED_AT",
" UNIVERSITY_OF_ORIGIN_OF_PERSON\n OR:",
" COACHED_AT",
" COACHED_AT",
" COACHED_UNTIL",
" REAL_ESTATE_AGENCY_OF\n\n Explanation:\n",
" LOCATION.IN.ORGANIZATION",
" NEAR_CITY",
" LOCATION.LOCATED_AT",
" LOCATION.LOCATED_AT",
" LOCATION.LOCATED_AT",
" NEAR_CITY",
" LOCATION.IN.ORGANIZATION",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" CO_OWNED_BY",
" COACHED_AT",
" NEAR_CITY",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COLOCATED_IN",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" LATER_WORKED_FOR",
" LEFT_OF\n\n Explanation:\n The text mentions that John",
" LIVES_NEARBY",
" LEFT_OF\n\n Explanation:\n The text mentions that John",
" LEFT_OF\n\n Explanation:\n The text mentions that John",
" LEFT_OF\n\n Explanation:\n The text mentions that John",
" MOVED_TO",
" LEFT_OF\n\n Explanation:\n The text states that John He",
" FORMED_BY",
" REAL_ESTATE_AGENCY_OF\n\n Explanation:\n",
" CO_FOUNDED",
" CO_FOUNDED",
" NO_RELATION",
" ASSOCIATED_WITH",
" 'ORG_NAME_OF'",
" REAL_ESTATE_AGENCY_OF\n\n Explanation:\n",
" EMPLOYED_BY",
" 'PREVIOUSLY_WORKED_FOR'",
" BUSINESS_LOCATED_IN.",
" BUSINESS_LOCATED_IN.",
" PROVIDES_SERVICES_TO",
" BUSINESS_LOCATED_IN",
" BUSINESS_LOCATED_IN.",
" BUSINESS_LOCATED_IN",
" BUSINESS_LOCATED_IN",
" COACHED_AT",
" LOCATION",
" COACHED_AT",
" COACHED_AT",
" NO_RELATION",
" LOCATION_OF\n or\n ORG_FOUNDED_IN\n",
" COACHED_AT",
" LOCATION",
" COACHED_AT",
" END_DATE",
" LOCATION_OF\n\n Explanation:\n The text states that John",
" NEAR_CITY",
" LOCATION_IN_LOCATION",
" LOCATION_IN_LOCATION",
" LOCATION_IN. LOCATION_IN is used when the head entity is a",
" NEAR_CITY",
" LOCATION",
" LIVES_IN",
" NEAR_CITY",
" LIVES_IN",
" LIVES_IN",
" NO_RELATION",
" NEAR_CITY",
" LOCATED_IN",
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" HOMETOWN_BEFORE",
" NEAR_CITY",
" SERVICES_LOCATION",
" NEAR_CITY",
" NEAR_CITY",
" NEAR_CITY",
" NEAR_CITY",
" BEST_REAL_ESTATE_IN_CITY",
" NEAR_CITY",
" COACHED_AT",
" LOCATION",
" COACHED_AT",
" COACHED_AT",
" BORN_IN.",
" Auburn IS_A American_passion.",
" COACHED_AT",
" LOCATION",
" COACHED_AT",
" COACHED_UNTIL",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" LOCATION_IN. LOCATION_IN is used when the head entity is a",
" NEAR_CITY",
" LOCATION_IN. LOCATION_IN is used when the head entity is a",
" LOCATION_IN. LOCATION_IN is used when the head entity is a",
" NEAR_CITY",
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" COACHED_AT",
" LOCATION.OF.ORGANIZATION",
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" LOCATED_IN",
" COACHED_AT",
" LOCATION",
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" LOCATION_OF\n or\n HEAD_OF\n or\n ",
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" LOCATION_IN_LOCATION",
" LOCATED_IN",
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" LOCATED_IN",
" COACHED_AT",
" LOCATION.OF.ORGANIZATION",
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" COACHED_AT",
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" LOCATION_OF\n or\n NO_RELATION (if 'American'",
" COACHED_AT",
" LOCATION.OF.ORGANIZATION",
" COACHED_AT",
" END_DATE",
" LOCATION_OF\n or\n HEAD_OF\n or\n ",
" LOCATION_IN. LOCATION_IN is used when the head entity is a",
" NEAR_CITY",
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" LOCATION_IN_LOCATION",
" NEAR_CITY",
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" LIVES_IN",
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" LOCATED_IN",
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" SERVICES_PROVIDED_BY",
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" COACHED_AT",
" LOCATION",
" COACHED_AT",
" COACHED_AT",
" COACHED_AT",
" LOCATION_OF\n or\n ORG_FOUNDED_IN\n",
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" COACHED_AT",
" COACHED_AT",
" REAL_ESTATE_AGENCY_LOCATED_IN_LOCATION",
" LOCATION",
" NEAR_CITY",
" LOCATED_IN",
" LOCATION",
" LOCATED_IN",
" NEAR_CITY"
] | [
[
"0",
"2",
"PERSON",
"John Heisman"
],
[
"3",
"5",
"ORG",
"Auburn University"
],
[
"6",
"8",
"PERSON",
"John Heisman"
],
[
"8",
"10",
"PERSON",
"John Heisman"
],
[
"11",
"14",
"DATE",
"1869-1936"
],
[
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"American"
],
[
"44",
"51",
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],
[
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"55",
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"Auburn University"
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[
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"1895"
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[
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[
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[
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[
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[
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],
[
"90",
"91",
"GPE",
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],
[
"96",
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"GPE",
"Auburn"
],
[
"107",
"108",
"GPE",
"Opelika"
],
[
"113",
"114",
"GPE",
"Auburn"
]
] | 607 |
609 | [
"A host of additional features include the upgrade 22-inch turbine alloy wheels in silver, 6 seats with easy access to the rear and free supercharging capability and the required charging cables.\nDon’t be fooled by the lack of buttons, controls or knobs in the interior for the 17-inch central screen is a technological haven which can be used by anyone. A full touchscreen including drag and swipe functions, access to features including the enhanced autopilot system, very popular toybox facility and even arcade games (who remembers Asteroids?).\nElon Musk wasn’t all business when building the Tesla Model X, what is life without a little fun along the way?\nFor full details of this vehicle, please click the button to the right or if you wish to speak to one of our sales consultants, please don’t hesitate in contacting us on 02920 761919 or firstname.lastname@example.org."
] | [
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]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['A host of additional features include the upgrade 22-inch turbine alloy wheels in silver, 6 seats with easy access to the rear and free supercharging capability and the required charging cables.\nDon’t be fooled by the lack of buttons, controls or knobs in the interior for the 17-inch central screen is a technological haven which can be used by anyone. A full touchscreen including drag and swipe functions, access to features including the enhanced autopilot system, very popular toybox facility and even arcade games (who remembers Asteroids?).\nElon Musk wasn’t all business when building the Tesla Model X, what is life without a little fun along the way?\nFor full details of this vehicle, please click the button to the right or if you wish to speak to one of our sales consultants, please don’t hesitate in contacting us on 02920 761919 or firstname.lastname@example.org.']
Entities:
[{'head': ['8', '11', 'QUANTITY', '22-inch'], 'tail': ['104', '106', 'PERSON', 'Elon Musk']}]
Relation:
| [
[
{
"head": [
"8",
"11",
"QUANTITY",
"22-inch"
],
"tail": [
"104",
"106",
"PERSON",
"Elon Musk"
]
}
],
[
{
"head": [
"8",
"11",
"QUANTITY",
"22-inch"
],
"tail": [
"113",
"114",
"ORG",
"Tesla"
]
}
],
[
{
"head": [
"17",
"18",
"CARDINAL",
"6"
],
"tail": [
"104",
"106",
"PERSON",
"Elon Musk"
]
}
],
[
{
"head": [
"17",
"18",
"CARDINAL",
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] | 608 |
610 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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Entities:
[{'head': ['3', '8', 'ORG', 'Del Norte Children’s Home'], 'tail': ['55', '56', 'PERSON', 'Daniel']}]
Relation:
| [
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}
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] | [
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" LOCATION_IN.",
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" LOCATION_OF\n\n Explanation:\n The text mentions that",
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" LOCATION_IN\n\n Explanation:\n The text mentions that",
" LOCATION_IN\n\n Explanation:\n The text mentions that",
" LOCATION.\n\n Entities: \n [{'head': ['3",
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],
[
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]
] | 609 |
611 | [
"On 31 January 2020 the United Kingdom left the European Union, losing vote and voice. It was a legal departure. Until the end of 2020 the UK will be treated as a member in economic and financial aspects. The critical date is not 31 January, but 31 December 2020. This is when Brexit will be felt in the world of money and products, states Rudolf Adam, advisor to Berlin Global Advisors."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['On 31 January 2020 the United Kingdom left the European Union, losing vote and voice. It was a legal departure. Until the end of 2020 the UK will be treated as a member in economic and financial aspects. The critical date is not 31 January, but 31 December 2020. This is when Brexit will be felt in the world of money and products, states Rudolf Adam, advisor to Berlin Global Advisors.']
Entities:
[{'head': ['1', '4', 'DATE', '31 January 2020'], 'tail': ['4', '7', 'GPE', 'the United Kingdom']}]
Relation:
| [
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}
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" ATTENDS\n\n Entities: \n [{'head': ['3",
" ATTENDED_BY\n\n Explanation:\n The text mentions",
" PERFORMS_AT\n\n Entities: \n [{'head': ['",
" PERFORMS_AT\n\n Entities: \n [{'head': ['",
" ATTENDED_BY\n\n Entities: \n [{'head':",
" PERFORMS_AT\n\n Entities: \n [{'head': ['",
" COLLABORATOR",
" ATTENDED\n\n Entities: \n [{'head': ['C",
" IF_ATTENDING",
" IF_ATTENDING. This is the relation between the entity \"Council Oak Ste",
" PERFORMS_AT\n\n Explanation:\n The text mentions that",
" PERFORMS_AT\n\n Explanation:\n The text states that \"",
" IF_ATTENDING",
" PART_OF",
" SPECIALIZES_IN",
" PROVIDES_MATERIAL\n\n Explanation:\n The text mentions",
" LOCATION.\n\n Entities: \n [{'head': ['2",
" LOCATION.OF.HEAD_AT.TAIL",
" COLLABORATOR",
" LOCATION.OF.HEAD_AT.TAIL",
" COLLABORATOR",
" COLLABORATED_ON.",
" COLLOCATION",
" HAS_PERFORMANCE\n\n Entities: \n [{'head':",
" HAS_PERFORMANCE.\n\n Entities: \n [{'head",
" PERFORMANCE_AT\n\n Explanation:\n The text mentions that",
" PERFORMS_AT\n\n Explanation:\n The text states that \"",
" FACILITY_OF\n\n Explanation:\n The text mentions that",
" PROVIDES_QUALITY\n\n Entities: \n [{'head':",
" PROVIDES_MATERIAL\n\n Explanation:\n The text mentions",
" LOCATION_IN.\n\n Entities: \n [{'head':",
" LOCATION.OF.LOCATIONS.ORGANIZATIONS.ORG",
" COLLABORATOR",
" LOCATION.\n\n Entities: \n [{'head': ['C",
" COLLABORATOR",
" COLLOCATION",
" FACILITY_OF\n\n Explanation:\n The text states that \"",
" IF_ATTENDING",
" PROVIDES_QUALITY\n\n Explanation:\n The text states that",
" PROVIDES_QUALITY\n\n Explanation:\n The text states that",
" PROVIDES_QUALITY\n\n Explanation:\n The text states that",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" COLLABORATOR",
" PROVIDES_QUALITY_TO\n\n Explanation:\n The text",
" PROVIDES_QUANTITY\n\n Explanation:\n The text mentions",
" PERFORMANCE_AT\n\n Explanation:\n The text mentions that",
" IF_ATTENDING. This is a custom relation for the context. It means that the",
" PROVIDES_PRODUCT\n\n Explanation:\n The text mentions that",
" PROVIDES_MATERIAL\n\n Explanation:\n The text mentions",
" PROVIDES_QUALITY\n\n Explanation:\n The text mentions",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" COLLABORATOR",
" COLLABORATED_ON\n\n Explanation:\n The entities represent the",
" PROVIDES_FROM\n\n Explanation:\n The text states that \"C",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" PERFORMANCE_LOCATION",
" PERFORMANCE_AT\n\n Entities: \n [{'head': ['",
" IF_ATTENDING. This is the standard relation label for the \"if X then Y",
" LOCATION_OF",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" PROVIDES_QUALITY_FOR\n\n Explanation:\n The text",
" PROVIDES_MATERIAL_FOR\n\n Explanation:\n The text",
" LOCATION_NEARBY",
" COLLABORATOR",
" LOCATION_NEARBY",
" COLLABORATED_WITH",
" PREVIOUSLY_OCCURRED_AT",
" LOCATION_FIRST\n\n Entities: \n [{'head':",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" LOCATION_NEARBY\n\n Explanation:\n The text ment",
" PERFORMANCE_AT\n\n Entities: \n [{'head': ['",
" IF_ATTENDING. This is the standard relation label for the \"if X, then",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_PERCENT\n\n Entities: \n [{'head",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" LOCATION_NEARBY",
" COLLABORATOR",
" SAME_LOCATION",
" COLLABORATOR",
" COLLOCATION",
" LOCATION_FIRST_FOR\n\n Explanation:\n The text",
" COLLABORATED_ON.",
" ATTENDED\n\n Entities: \n [{'head': ['C",
" COLLABORATED_ON\n\n Explanation:\n The text states that",
" NO_RELATION",
" CHEF_OF",
" CHEF_OF\n\n Entities: \n [{'head': ['",
" PROVIDES_QUALITY_TO\n\n Explanation:\n The text",
" CHEF_OF\n\n Explanation:\n The text states that Che",
" CHEF_OF\n\n Explanation:\n The text states that Che",
" COLLABORATED_WITH",
" COLLABORATED_WITH",
" COLLABORATOR",
" COLLABORATED_ON.",
" COLLABORATED_ON.",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_NEARBY\n\n Explanation:\n The text ment",
" PERIODIC_EVENT_LOCATION",
" IF_ATTENDING",
" LOCATION_OF",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" NO_RELATION",
" LOCATION_OF\n\n Explanation:\n The text mentions that",
" LOCATION_NEARBY",
" LOCATION_IN_LOCATION",
" COLLABORATED_WITH",
" COLLABORATOR",
" PREVIOUSLY_OCCURRED_AT",
" LOCATION_FIRST_FOR\n\n Explanation:\n The text",
" COLLABORATED_ON\n\n Entities: \n [{'head':",
" GATHERED_WITH\n\n Entities: \n [{'head':",
" COLLABORATED_ON\n\n Explanation:\n The text states that",
" COLLABORATOR",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" CHEF_OF\n\n Entities: \n [{'head': ['",
" CHEF_OF\n\n Entities: \n [{'head': ['",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" CHEF_OF\n\n Entities: \n [{'head': ['",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" COLLABORATOR",
" CHEF_OF\n\n Explanation:\n The text mentions that",
" COLLABORATED_ON\n\n Explanation:\n The entities represent '",
" COLLABORATED_ON.",
" IF_ATTENDING",
" COLLOCATION",
" COLLOCATION",
" COLLABORATED_WITH\n\n Explanation:\n The text states that",
" COLLOCATION",
" COLLABORATED_WITH",
" COLLABORATED_ON.",
" COLLABORATED_WITH",
" COLLABORATED_WITH",
" IF_ATTENDING. This is the standard label for the relation between an event and an",
" FIRST_OF\n\n Explanation:\n The text states that \"",
" PERFORMANCE_OF\n\n Entities: \n [{'head': ['",
" PRD_OF\n\n Explanation:\n The text mentions that '",
" PERFORMANCE_AT\n\n Explanation:\n The text mentions that",
" LIST_ITEM_OF\n\n Explanation:\n The text mentions",
" COLLABORATED_ON.",
" LIST_ITEM_OF\n\n Explanation:\n The text mentions",
" COLLABORATED_WITH"
] | [
[
"4",
"5",
"CARDINAL",
"one"
],
[
"7",
"8",
"CARDINAL",
"three"
],
[
"9",
"11",
"DATE",
"this weekend"
],
[
"12",
"14",
"PERSON",
"Britney Spears"
],
[
"29",
"34",
"ORG",
"Council Oak Steaks & Seafood"
],
[
"35",
"39",
"ORG",
"Seminole Hard Rock’s"
],
[
"43",
"45",
"PERCENT",
"100%"
],
[
"45",
"46",
"ORG",
"USDA"
],
[
"55",
"56",
"GPE",
"Hollywood"
],
[
"58",
"59",
"GPE",
"Tampa"
],
[
"73",
"75",
"PERSON",
"Carl Murphy"
],
[
"76",
"77",
"GPE",
"Tampa"
],
[
"79",
"81",
"PERSON",
"Omar Torres"
],
[
"82",
"84",
"TIME",
"last night"
],
[
"99",
"100",
"ORDINAL",
"first"
]
] | 612 |
614 | [
"A group of trucks enter Sanibel for the first time after Hurricane Ian. The U.S. Justice Department urges the Supreme Court to stay out of the Mar-a-lago documents dispute. Actress Dame Angela Lansbury found dead in her Los Angeles home. NASA’s first planetary defense mission is a success. The final movie of the Slasher sequels comes to theaters this Friday.\nThese stories and more on Newsbreak!"
] | [
[
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"\n",
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"more",
"on",
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]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['A group of trucks enter Sanibel for the first time after Hurricane Ian. The U.S. Justice Department urges the Supreme Court to stay out of the Mar-a-lago documents dispute. Actress Dame Angela Lansbury found dead in her Los Angeles home. NASA’s first planetary defense mission is a success. The final movie of the Slasher sequels comes to theaters this Friday.\nThese stories and more on Newsbreak!']
Entities:
[{'head': ['5', '6', 'GPE', 'Sanibel'], 'tail': ['8', '9', 'ORDINAL', 'first']}]
Relation:
| [
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"8",
"9",
"ORDINAL",
"first"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"11",
"13",
"EVENT",
"Hurricane Ian"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
]
}
],
[
{
"head": [
"5",
"6",
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],
"tail": [
"19",
"22",
"ORG",
"the Supreme Court"
]
}
],
[
{
"head": [
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],
"tail": [
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"32",
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"Mar-a-lago"
]
}
],
[
{
"head": [
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"6",
"GPE",
"Sanibel"
],
"tail": [
"36",
"39",
"PERSON",
"Dame Angela Lansbury"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
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],
"tail": [
"43",
"45",
"GPE",
"Los Angeles"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"47",
"48",
"ORG",
"NASA"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"49",
"50",
"ORDINAL",
"first"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"62",
"63",
"WORK_OF_ART",
"Slasher"
]
}
],
[
{
"head": [
"5",
"6",
"GPE",
"Sanibel"
],
"tail": [
"67",
"69",
"DATE",
"this Friday"
]
}
],
[
{
"head": [
"5",
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],
"tail": [
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"77",
"ORG",
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]
}
],
[
{
"head": [
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"ORDINAL",
"first"
],
"tail": [
"5",
"6",
"GPE",
"Sanibel"
]
}
],
[
{
"head": [
"8",
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"ORDINAL",
"first"
],
"tail": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
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]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
"27",
"32",
"LOC",
"Mar-a-lago"
]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
"36",
"39",
"PERSON",
"Dame Angela Lansbury"
]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
"43",
"45",
"GPE",
"Los Angeles"
]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
"47",
"48",
"ORG",
"NASA"
]
}
],
[
{
"head": [
"8",
"9",
"ORDINAL",
"first"
],
"tail": [
"76",
"77",
"ORG",
"Newsbreak"
]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"5",
"6",
"GPE",
"Sanibel"
]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"19",
"22",
"ORG",
"the Supreme Court"
]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"27",
"32",
"LOC",
"Mar-a-lago"
]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"36",
"39",
"PERSON",
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]
}
],
[
{
"head": [
"11",
"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
"43",
"45",
"GPE",
"Los Angeles"
]
}
],
[
{
"head": [
"11",
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"EVENT",
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],
"tail": [
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]
}
],
[
{
"head": [
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"13",
"EVENT",
"Hurricane Ian"
],
"tail": [
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]
}
],
[
{
"head": [
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"18",
"ORG",
"The U.S. Justice Department"
],
"tail": [
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"6",
"GPE",
"Sanibel"
]
}
],
[
{
"head": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
],
"tail": [
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"first"
]
}
],
[
{
"head": [
"14",
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"The U.S. Justice Department"
],
"tail": [
"11",
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]
}
],
[
{
"head": [
"14",
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],
"tail": [
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]
}
],
[
{
"head": [
"14",
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"ORG",
"The U.S. Justice Department"
],
"tail": [
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"32",
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]
}
],
[
{
"head": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
],
"tail": [
"36",
"39",
"PERSON",
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]
}
],
[
{
"head": [
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"ORG",
"The U.S. Justice Department"
],
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"45",
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]
}
],
[
{
"head": [
"14",
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],
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"48",
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}
],
[
{
"head": [
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],
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]
}
],
[
{
"head": [
"14",
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],
"tail": [
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"Slasher"
]
}
],
[
{
"head": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
],
"tail": [
"67",
"69",
"DATE",
"this Friday"
]
}
],
[
{
"head": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
],
"tail": [
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]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
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"GPE",
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]
}
],
[
{
"head": [
"19",
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"ORG",
"the Supreme Court"
],
"tail": [
"8",
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"ORDINAL",
"first"
]
}
],
[
{
"head": [
"19",
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"ORG",
"the Supreme Court"
],
"tail": [
"11",
"13",
"EVENT",
"Hurricane Ian"
]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"14",
"18",
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]
}
],
[
{
"head": [
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"ORG",
"the Supreme Court"
],
"tail": [
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"LOC",
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]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"36",
"39",
"PERSON",
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]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"43",
"45",
"GPE",
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]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"47",
"48",
"ORG",
"NASA"
]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"49",
"50",
"ORDINAL",
"first"
]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
"62",
"63",
"WORK_OF_ART",
"Slasher"
]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
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"DATE",
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]
}
],
[
{
"head": [
"19",
"22",
"ORG",
"the Supreme Court"
],
"tail": [
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"77",
"ORG",
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]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"5",
"6",
"GPE",
"Sanibel"
]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"8",
"9",
"ORDINAL",
"first"
]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"11",
"13",
"EVENT",
"Hurricane Ian"
]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"14",
"18",
"ORG",
"The U.S. Justice Department"
]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"19",
"22",
"ORG",
"the Supreme Court"
]
}
],
[
{
"head": [
"27",
"32",
"LOC",
"Mar-a-lago"
],
"tail": [
"36",
"39",
"PERSON",
"Dame Angela Lansbury"
]
}
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615 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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616 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
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617 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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[{'head': ['3', '5', 'PERSON', 'Sweetie Darling'], 'tail': ['7', '9', 'QUANTITY', '11 oz']}]
Relation:
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] | 616 |
618 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['2008 Felipe Massa Ferrari race helmet.\nThis original carbon fiber Schuberth RF1 helmet was worn by the Brazilian superstar at the 2008 European GP at Valencia in the race winning Ferrari F2008 (s/n 269). The helmet shows good signs of wear and has been signed on the visor. Not only did Massa win this race, but the Scuderia won the Constructor’s Title that year as well.\nSOLD – enquire on having us find you a similar one.']
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[{'head': ['0', '1', 'DATE', '2008'], 'tail': ['1', '3', 'PERSON', 'Felipe Massa']}]
Relation:
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619 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['by Forbes, Andy Chatterley — 23 January 2024\nA new report by consultancy firm Kearney, using MUSO piracy data, is calling on content owners to leverage piracy consumption data and see those who pirate as prospective customers.\nThe report claims that online video content piracy leads to revenue losses of $75 billion per year for the global media sector. This figure is projected to reach $125 billion by 2028, representing an annual growth rate of nearly 11 percent.\nThe report also outlines the three segments which make up the piracy market:\nUnashamed: people who knowingly consumer pirated content\nUnaware: people who might not realise they are pirating\nUnwilling: people who pirate because they don’t believe content is available in their market\nRead the full article here.']
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[{'head': ['1', '2', 'ORG', 'Forbes'], 'tail': ['3', '5', 'PERSON', 'Andy Chatterley']}]
Relation:
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622 | [
"The place where I share career tips, positive psychology tools, stories, metaphors and more!\nLIFE & CAREER COACH\nYou're on the mailing list and I am thrilled!\nA confirmation email is on its way to you but check that naughty Junk inbox folder in case it has gobbled it up, and mark my email address as safe. x\nSubscribe to 'The Straight - talking Newsletter'\nSign up to a ray of sunshine in your inbox every Weds. I write about careers, creativity, psychology, business and life, and truly value each reader on my mailing list.\nLet's do this!\nCoaching the core of who you are so you can make long-term sustainable progress towards realising your potential.\nIs this the year you finally get a coach?\n@ Dina Grishin 2023\nTemplate designed by EM\nCustomized by iamrobifarkas.co.uk\n© Dina grishin"
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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623 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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[
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] | 622 |
624 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['PASTOR KEVIN WEST\nIn “Phantom Phobias” Pastor Kevin discusses three types of phobias that are unseen but which can create a spirit of fear that is not from God. This fear can paralyze your ability to fulfill your destiny. Jesus came to bring us life abundantly, so let your faith overrule fear. Live life!']
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[{'head': ['1', '3', 'PERSON', 'KEVIN WEST'], 'tail': ['6', '8', 'WORK_OF_ART', 'Phantom Phobias']}]
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625 | [
"Fill out the contact form below and we will contact you shortly with more details.\nWe can’t wait to make your vision come alive, and celebrate your life & love with beauty & intention.\nWe will get in touch via email shortly.\nbrand + web design by madeline wiggins.\ncopyright 2023 fieldhouse floral artistry"
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Fill out the contact form below and we will contact you shortly with more details.\nWe can’t wait to make your vision come alive, and celebrate your life & love with beauty & intention.\nWe will get in touch via email shortly.\nbrand + web design by madeline wiggins.\ncopyright 2023 fieldhouse floral artistry']
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] | 624 |
626 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
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627 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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629 | [
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630 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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] | 629 |
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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[{'head': ['0', '2', 'PERSON', 'Victoria Opitz'], 'tail': ['5', '6', 'DATE', '28']}]
Relation:
| [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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633 | [
"KIDS PARTY KARAOKE!\nWe provided Karaoke entertainment at this 13th birthday party. In addition our DJ Munirah entertained the children with a selection of party games.\nINTRODUCING DJ MUNIRAH\nCheck out our most popular children’s party entertainer Munirah. With years of experience and a great personality she’s the perfect host for any kid’s party you’re planning.\nGLOW IN THE DARK PARTY\nWe had so much fun at this Glow in the dark party. We provided UV Lighting and Neon props"
] | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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634 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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[{'head': ['31', '32', 'DATE', 'daily'], 'tail': ['33', '37', 'ORG', 'the European Central Bank']}]
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637 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
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639 | [
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Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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641 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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642 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
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] | 641 |
643 | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Blayze Hallack and his friend Pandora arrive at a diner called “Diner South” after a long journey on their worn-out space barge. They dock their ship and sit at the bar, where they are approached by Amanda, a dark-skinned woman who recognizes them as ITR techs from the Silvani Trace. Amanda explains that she is building a crew for an ITR (Illegal Tech Repair) operation, where they travel to planets within The Federation to fix outdated or illegal equipment. She offers Blayze and Pandora support and a partnership, providing them with their own quarters on her ship and advanced pay. Excited by the opportunity, Blayze and Pandora agree to join Amanda’s crew, and they make plans to depart from bay E at 0500.\nfor more, please visit']
Entities:
[{'head': ['0', '2', 'PERSON', 'Blayze Hallack'], 'tail': ['5', '6', 'PERSON', 'Pandora']}]
Relation:
| [
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{
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]
}
],
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{
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}
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] | [
" FRIEND",
" ARRIVED_AT",
" RECRUITER_AGENT_OF_EMPLOYEE",
" TECH_FROM.",
" RECRUITER_AGENT_OF_EMPLOYEE",
" WITHIN.",
" SELF_REFERENCE",
" FRIEND",
" SELF_REFERENCE",
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644 | [
"Many people are unaware of celebrities that support Zionism. Here are only 6 of them - the most popular ones, and some of what they did to show their support for Isr*el. There are many ways to boycott them, for example: stop listening to their music, stop buying their brands, stop watching their movies. Boycott Black Widow, Wonder Woman, etc. Avoid being a part of activities that require paying for the celebrity. (Friendly reminder than this has nothing to do with a celebrity being Jewish, but has everything to do with their support for the genocide against Pa/estinians)\n- For the Harry Styles slide, the article is called Why I'm Pro-Israeli AND Pro-Palestinian if you want to read how tone deaf it is."
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] | 643 |
645 | [
"Malcolm Gladwell has written a profile of the famous distance runner Alberto Salazar in this week’s New Yorker magazine (unfortunately, most of it is behind a paywall).\nHere’s a passage that struck me (I hope you can see it in an RSS Reader):\nThough I suppose one can connect this some way to school reform issues, I’m more concerned in this post to relating it to the classroom.\nIt seems to me that, though our students can’t really physically exit our classrooms, if we don’t provide genuine opportunities for voice, then they can certainly “check-out” mentally.\nIt’s an interesting framework.\nWhat are your thoughts?"
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Malcolm Gladwell has written a profile of the famous distance runner Alberto Salazar in this week’s New Yorker magazine (unfortunately, most of it is behind a paywall).\nHere’s a passage that struck me (I hope you can see it in an RSS Reader):\nThough I suppose one can connect this some way to school reform issues, I’m more concerned in this post to relating it to the classroom.\nIt seems to me that, though our students can’t really physically exit our classrooms, if we don’t provide genuine opportunities for voice, then they can certainly “check-out” mentally.\nIt’s an interesting framework.\nWhat are your thoughts?']
Entities:
[{'head': ['0', '2', 'PERSON', 'Malcolm Gladwell'], 'tail': ['11', '13', 'PERSON', 'Alberto Salazar']}]
Relation:
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["Neil Kinnock - Politics Quotes\n3 Sourced Quotes\nI'll tell you what happens with impossible promises. You start with far fetched resolutions. They are then pickled into a rigid dogma, a code, and you go through the years sticking to that, out-dated, misplaced, irrelevant to the real needs, and you end in the grotesque chaos of a Labour council—a Labour council—hiring taxis to scuttle round a city handing out redundancy notices to its own workers. I'm telling you - and you'll listen - you can't play politics with people's jobs and with people's services. The people will not abide posturing."]
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[{'head': ['0', '2', 'PERSON', 'Neil Kinnock'], 'tail': ['6', '7', 'CARDINAL', '3']}]
Relation:
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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651 | [
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["You're read Goblin Is Very Strong manga online at Manga18FX.com. Alternative(s) : ゴブリンはもう十分に強い, Goblin wa Mou Juubun ni Tsuyoi - Author(s) : Salamander\nCopyrights and trademarks for the manga, and other promotional materials are held by their respective owners and their use is allowed under the fair use clause of the Copyright Law. © 2024 Manga18FX.COM\nGoblin Is Very Strong\nContains themes or scenes that may not be suitable for very young readers thus is blocked for their protection.\nAre you over 18?\nAs an independent publisher, we rely on ads to support our website. Without ads, we'll go out of business. We need your help!"]
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652 | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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Entities:
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Relation:
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" LOCATION_OF\n\n Explanation:\n The text states that the",
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" LOCATION_NEAR.",
" LOCATED_NEAR",
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" LOCATION_OF\n or\n NO_RELATION (if Triton",
" LOCATION_OF\n Or\n NO_RELATION\n\n Explan",
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" LOCATION_OF\n ORIGIN_OF\n NO_RELATION #",
" LOCATION_OF\n\n Explanation:\n The text states that the",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
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" LOCATION_OF\n or\n NO_RELATION (if 'Trit",
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" NO_RELATION. In this text, there is no clear relation between Doris and the",
" CREATED_BY",
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" INSTALLED_AT",
" INSTALLED_AT",
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[
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[
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[
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[
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[
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[
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],
[
"125",
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]
] | 651 |
653 | [
"Kingmaker is the first book in The Witcham Chronicles, a dark fantasy series with adult language and situations. Reader discretion is advised.\nNot all kings are promised power at birth. Some will lead a long life before such leadership is handed to them.\nDiemos, an ex-soldier and drifter, thought he accepted a routine courier job to make a few gold. However, the quest was anything but “routine.” Instead, he found himself at the center of a growing darkness from beyond the grave. After reconnecting with a friend from his past, they set out to prevent that darkness from consuming the realms. Can Diemos and his band of rangers prevent the destruction of Witcham and the nearby lands?"
] | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Kingmaker is the first book in The Witcham Chronicles, a dark fantasy series with adult language and situations. Reader discretion is advised.\nNot all kings are promised power at birth. Some will lead a long life before such leadership is handed to them.\nDiemos, an ex-soldier and drifter, thought he accepted a routine courier job to make a few gold. However, the quest was anything but “routine.” Instead, he found himself at the center of a growing darkness from beyond the grave. After reconnecting with a friend from his past, they set out to prevent that darkness from consuming the realms. Can Diemos and his band of rangers prevent the destruction of Witcham and the nearby lands?']
Entities:
[{'head': ['0', '1', 'WORK_OF_ART', 'Kingmaker'], 'tail': ['50', '51', 'PERSON', 'Diemos']}]
Relation:
| [
[
{
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}
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}
],
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{
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}
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[
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[
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] | 652 |
654 | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Artisan pencil tray featuring exclusive raised artwork by Juliana Tipton with semi-transparent cream glaze and exposed stoneware base. Packaged in a kraft gift box.\nAs part of our Prairie lookbook, this design was inspired by William Morris and the decorative Arts & Crafts movement using warm and detailed illustrations, appealing sentimentally to those who love the quiet world of nature.\n• 9.125" w x 3" d\n• Artist collaboration with Juliana Tipton\n• Decorative use only\n• Not food safe\n• Stoneware base\n• Comes in a kraft gift box']
Entities:
[{'head': ['8', '10', 'PERSON', 'Juliana Tipton'], 'tail': ['24', '25', 'ORG', 'kraft']}]
Relation:
| [
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{
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{
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" WORKED_FOR",
" WORKED_FOR",
" SELF_REFERENCE",
" MEMBER_OF",
" ACTIVE_MEMBER_OF (PERSON, GPE)",
" HAS_CONNECTIONS_WITH",
" NO_RELATION.",
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" ATTENDS",
" IN_CHARGE_OF",
" IN_CHARGE_OF",
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" 'COMMERCIALIZES' or 'IS_RESPONSIBLE_FOR",
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" INDUSTRY_FOCUS",
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" WORKED_WITH",
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" IN_CHARGE_OF",
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" HAS_CONNECTION",
" EXTENSIVE_CONTACTS_WITH.",
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" WORKED_FOR",
" WORKED_FOR",
" HAS_WORK_EXPERIENCE",
" HAS_MEMBERSHIP",
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" HAS_WORKED_IN\n\n Explanation:\n The text states",
" HAS_EXTENSIVE_NETWORK_WITH",
" ATTENDED",
" HAS_INDUSTRY\n\n Explanation:\n The text states",
" IN_CHARGE_OF",
" IN_CHARGE_OF",
" HAS_INDUSTRY\n\n Explanation:\n The text states",
" HAS_EXPERIENCE",
" RETAIL_PROVIDES_ONLINE_CONTENT",
" HAS_EXPERIENCE_IN.",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_INDUSTRY\n\n Explanation:\n The text states",
" MEMBER_OF",
" HAS_FOCUS_ON\n\n Explanation:\n The text",
" HAS_CONNECTIONS_WITH",
" HAS_BUSINESS_CONNECTIONS_WITH",
" ATTENDS",
" ATTENDS",
" ATTENDS\n\n Explanation:\n The text states that \"You",
" HEAD_OF\n\n Explanation:\n The text states that \"J",
" IN_CHARGE_OF",
" 'HEAD_IS_IN_CHARGE_OF'",
" HEAD_OF\n\n Explanation:\n The text states that \"J",
" HAS_EXPERIENCE",
" ONLINE_CONTENT_PROVIDES_SOLUTIONS_FOR_RE",
" INVOLVED_IN\n\n Explanation:\n The text states that \"",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_FOR",
" WORKED_WITH",
" WORKED_FOR",
" HEAD_OF\n\n Explanation:\n The text states that \"J",
" MEMBER_OF",
" HAS_COMMUNITY_IN.",
" HAS_CONNECTION",
" HAS_EXTENSIVE_NETWORK_WITH",
" ATTENDS",
" ATTENDS",
" ATTENDS",
" HAS_EXPERIENCE_WITH",
" BUILDS_SOLUTIONS_FOR",
" BUILDS_SOLUTIONS_FOR",
" HAS_EXPERIENCE_WITH",
" HAS_EXPERIENCE_WITH",
" HAS_INDUSTRY\n\n Explanation:\n The text states",
" INVOLVED_IN\n\n Explanation:\n The text states that James",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_EXPERIENCE_WITH",
" MEMBER_OF",
" HAS_ACTIVE_COMMUNITY_IN.",
" HAS_EXTENSIVE_CONNECTIONS_WITH",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATION",
" ATTENDS",
" ATTENDS",
" ATTENDS",
" WORKED_FOR",
" WORKED_FOR",
" CLIENT_OF",
" WORKED_FOR",
" HAS_EXPERIENCE_WITH",
" 'WORKED_FOR'",
" 'CLIENT' or 'PARTNER' or 'WORKED_WITH' or 'PROVID",
" WORKED_FOR",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_FOR",
" MEMBER_OF",
" MEMBER_OF\n\n Explanation:\n The text states that James is",
" HAS_CONNECTIONS_WITH",
" NO_RELATION.",
" ATTENDED",
" ATTENDED_EVENT",
" ATTENDED_EVENT",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_EXPERIENCE.",
" worked_with",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" MEMBER_OF",
" MEMBER_OF\n\n Explanation:\n The text states that \"J",
" HAS_CONNECTIONS_WITH",
" HAS_EXTENSIVE_NETWORK_WITH",
" ATTENDED",
" ATTENDED_EVENT",
" ATTENDED",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_EXPERIENCE_WITH",
" 'HEAD_WORKED_FOR'",
" CLIENT_OF",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" MEMBER_OF",
" HAS_MEMBER_IN_COMMUNITY",
" HAS_CONNECTION",
" NO_RELATION.\n\n Explanation:\n The text does not provide",
" ATTENDED",
" ATTENDED_EVENT",
" WORKED_WITH. This is because James has experience working with Carphone Warehouse",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_EXPERIENCE_WITH",
" CLIENT\n\n Explanation:\n The text states that James worked with",
" CLIENT_OF",
" WORKED_FOR",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" MEMBER_OF",
" HAS_EMPLOYED_FROM\n\n Explanation:\n The",
" HAS_CONNECTION",
" HAS_BUSINESS_RELATION\n\n Explanation:\n The",
" ATTENDED",
" ATTENDED_EVENT",
" WORKED_WITH",
" IN_CHARGE_OF",
" IN_CHARGE_OF",
" IN_CHARGE_OF",
" WORKS_FOR",
" HAS_EXPERIENCE",
" HAS_INDUSTRY\n\n Explanation:\n The text states",
" INDUSTRY_FOCUS",
" HAS_EXPERIENCE_WITH",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" IN_CHARGE_OF",
" MEMBER_OF",
" HAS_ACTIVE_MEMBERSHIP",
" HAS_CONNECTIONS_WITH",
" HAS_EXTENSIVE_NETWORK_WITH",
" ATTENDS",
" ATTENDED",
" ATTENDS",
" SELF_REFERENCE",
" IN_CHARGE_OF",
" IN_CHARGE_OF",
" SAME_PERSON",
" HAS_EXPERIENCE",
" 'HEAD_OF'",
" IN_CHARGE_OF",
" HAS_EXPERIENCE_WITH",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" MEMBER_OF",
" ACTIVE_MEMBER_OF_COMMUNITY",
" HAS_CONNECTIONS_WITH",
" HAS_CONNECTIONS_WITH",
" ATTENDS",
" ATTENDS",
" ATTENDS",
" MEMBER_OF",
" HEAD_OF\n or\n HAS_COMMUNITY\n or\n",
" MEMBER_OF",
" MEMBER_OF",
" HAS_EXPERIENCE_WITH\n\n Or, if the entities were revers",
" COMMUNITY_MEMBER_OF\n\n Explanation:\n The",
" COMMUNITY_MEMBER",
" COMMUNITY_MEMBER_OF\n\n Explanation:\n The",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF\n\n Explanation:\n The text states that \"You",
" HAS_MEMBER_WITH_EXTENSIVE_NETWORK_IN",
" MEMBER_OF\n\n Explanation:\n The text states that \"You",
" MEMBER_OF\n\n Explanation:\n The text states that \"You",
" MEMBER_OF\n\n Explanation:\n The text states that \"You",
" LIVES_IN",
" LOCATED_IN",
" LOCATED_IN",
" LIVES_IN",
" HAS_EXPERIENCE.",
" 'LOCATION_OF'",
" HAS_FOCUS",
" HAS_FOCUS_ON",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" HAS_WORKED_FOR",
" LIVES_IN",
" MEMBER_OF",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATIONS\n\n ",
" EXTENSIVE_NETWORK",
" ATTENDS",
" ATTENDS",
" ATTENDS",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" HAS_HEADQUARTERS_IN.",
" HAS_HEADQUARTERS_IN.",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATION",
" HAS_EXPERIENCE_WITH_LOCATION",
" REACHABLE_FROM",
" ORIGIN_FROM",
" REACHABLE_FROM",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" WORKED_FOR",
" EXTENSIVE_NETWORK",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF\n\n Explanation:\n The text states that James",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATIONS\n\n ",
" EXTENSIVE_NETWORK_WITH_LOCATIONS",
" ATTENDS",
" ATTENDS",
" ATTENDS",
" NO_RELATION.",
" FOUNDER_IN_COUNTRY",
" FOUNDER_IN_COUNTRY",
" HAS_EXTENSIVE_NETWORK_WITH",
" HAS_EXPERIENCE_WITH\n\n Entities: \n [",
" FOUND_IN\n or\n LOCATED_IN\n or\n ",
" FOUND_IN\n\n Explanation:\n The text mentions that James",
" HAS_FOCUS_ON\n\n Explanation:\n The text",
" NO_RELATION.\n\n Explanation:\n The text does not provide",
" NO_RELATION.",
" HAS_WORKED_FOR",
" WORKED_FOR",
" HAS_CONNECTION",
" NO_RELATION.",
" MEMBER_OF",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATIONS\n\n ",
" HAS_EXTENSIVE_NETWORK_WITH_LOCATIONS\n\n ",
" MOST_LIKELY_TO_ATTEND",
" 'HEAD_IS_LOCATED_IN' # or 'HEAD_ATTENDS'",
" CAN_ATTEND\n\n Explanation:\n The text states that \"You",
" ATTENDED",
" ATTENDED_CONFERENCE",
" ATTENDS",
" ATTENDED",
" HAS_EXPERIENCE_FOR\n\n Or\n\n Entities:",
" ATTENDED",
" KEY_EVENT_OF\n\n Explanation:\n In the text, it",
" ATTENDS\n\n Explanation:\n The text states that \"You",
" ATTENDED_CONFERENCE",
" ATTENDED_CONFERENCE",
" ATTENDED_BY",
" ATTENDED_CONFERENCE",
" ATTENDED_CONFERENCE",
" ATTENDED",
" MEMBER_OF",
" ATTENDS_CONFERENCE",
" ATTENDS_CONFERENCE_IN. (Note: The label ATTEND",
" ATTENDS_CONFERENCE_IN.",
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" ATTENDS",
" ATTENDED",
" ATTENDED_BY",
" ATTENDED_BY",
" ATTENDED",
" ATTENDED_EVENT",
" ATTENDED_EVENT",
" ATTENDED_BY",
" ATTENDED_EVENT",
" ATTENDED_BY",
" ATTENDED_BY",
" ATTENDED_BY",
" ATTENDED_EVENT",
" ATTENDED",
" MEMBER_OF",
" ATTENDS\n\n Explanation:\n The text states that \"You",
" ATTENDS_LOCATION",
" ATTENDS_EVENT_IN_LOCATION",
" ATTENDED_EVENT",
" ATTENDED",
" ATTENDS\n\n Explanation:\n The text states that \"You",
" ATTENDS",
" ATTENDED",
" ATTENDS\n\n Explanation:\n The text states that \"You",
" ATTENDED_BY",
" ATTENDED_BY",
" ATTENDED_BY",
" WORKED_FOR",
" WORKED_FOR",
" ATTENDED_BY",
" ATTENDED_BY",
" ATTENDED",
" MEMBER_OF",
" You are most likely to find him attending (EVENT:MWC) in (GPE:",
" ATTENDS_FROM\n\n Explanation:\n In the text,",
" ATTENDS_CONFERENCE_IN_LOCATION",
" You_are_most_likely_to_find_him_attending.\n\n"
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[
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"MWC"
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] | 654 |
656 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Testimonial- Manta Marine Design\n"The Orca CFD software and assistance from the Orca3D team has immensely helped us being able to meet specific requirements of a challenging design brief from our client. We will definitely use Orca3D Marine CFD again and we highly recommend it to other designers! “"\n-Pepijn van Schaik']
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[{'head': ['1', '4', 'ORG', 'Manta Marine Design'], 'tail': ['7', '9', 'PRODUCT', 'Orca CFD']}]
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657 | [
"By Pam Winters\nJanuary 27, 2016 at 12:27 pm\nI’m in! I’ll do my best to write and actually mail a few letters in April and beyond!! Thanks for such a gentle reminder of how special sending and receiving handwritten cards and letters makes us all feel."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['By Pam Winters\nJanuary 27, 2016 at 12:27 pm\nI’m in! I’ll do my best to write and actually mail a few letters in April and beyond!! Thanks for such a gentle reminder of how special sending and receiving handwritten cards and letters makes us all feel.']
Entities:
[{'head': ['1', '3', 'PERSON', 'Pam Winters'], 'tail': ['4', '8', 'DATE', 'January 27, 2016']}]
Relation:
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[
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] | 656 |
658 | [
"Skip to content\nmatt hart bowen therapy\na website design case study\nWhat’s it like to work with findability?\nWatch our case study in website design.\nReputation is the ultimate currency.\nHow you make your money is more important than how much you make.\nUtilisation, recovery, cleanliness.\nAll progress depends on the number of uncomfortable conversations you're willing to have.\nIn business today, you're a media company first, and a __________ business second.\nWork in facts, not opinions.\nIf it's not in writing, it doesn't exist.\nProgress is non-linear.\nSelf care, self respect, pay yourself first.\nbusiness listing management\nScroll to Top"
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["Skip to content\nmatt hart bowen therapy\na website design case study\nWhat’s it like to work with findability?\nWatch our case study in website design.\nReputation is the ultimate currency.\nHow you make your money is more important than how much you make.\nUtilisation, recovery, cleanliness.\nAll progress depends on the number of uncomfortable conversations you're willing to have.\nIn business today, you're a media company first, and a __________ business second.\nWork in facts, not opinions.\nIf it's not in writing, it doesn't exist.\nProgress is non-linear.\nSelf care, self respect, pay yourself first.\nbusiness listing management\nScroll to Top"]
Entities:
[{'head': ['4', '6', 'PERSON', 'matt hart'], 'tail': ['81', '82', 'DATE', 'today']}]
Relation:
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[
{
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659 | [
"Aleksandr Lukashenko visits House of Charity in Minsk\nOn Christmas Day, 7 January, President of Belarus Aleksandr Lukashenko visited the House of Charity in Minsk and met with Metropolitan of Minsk and Slutsk Filaret, Patriarchal Exarch of All Belarus.\nThe President visited the Orthodox Church and lit up a Christmas candle.\nAleksandr Lukashenko and Metropolitan Filaret exchanged gifts. The President donated a unique copy of the Gospels. The book is made in old liturgical traditions and is designed to be used during services. The text of the book is in Old Church Slavonic. This present will be kept in Metropolitan Filaret's private library.\nAleksandr Lukashenko and Metropolitan Filaret talked about the spiritual revival of the society, the interaction of the state and the Belarusian Orthodox Church, the development of the Christian civilization in the modern world."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["Aleksandr Lukashenko visits House of Charity in Minsk\nOn Christmas Day, 7 January, President of Belarus Aleksandr Lukashenko visited the House of Charity in Minsk and met with Metropolitan of Minsk and Slutsk Filaret, Patriarchal Exarch of All Belarus.\nThe President visited the Orthodox Church and lit up a Christmas candle.\nAleksandr Lukashenko and Metropolitan Filaret exchanged gifts. The President donated a unique copy of the Gospels. The book is made in old liturgical traditions and is designed to be used during services. The text of the book is in Old Church Slavonic. This present will be kept in Metropolitan Filaret's private library.\nAleksandr Lukashenko and Metropolitan Filaret talked about the spiritual revival of the society, the interaction of the state and the Belarusian Orthodox Church, the development of the Christian civilization in the modern world."]
Entities:
[{'head': ['0', '2', 'PERSON', 'Aleksandr Lukashenko'], 'tail': ['3', '6', 'ORG', 'House of Charity']}]
Relation:
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] | 658 |
660 | [
"(W) John Allison (A) Max Sarin (CA) John Allison\nAn Agatha Christie-style murder mystery set in the world of English competitive baking from Giant Days' John Allison and Max Sarin.\nWhen she enters her country's most beloved baking competition, Shauna Wickle's goal is to delight the judges, charm the nation, and make a few friends along the way. But when a fellow contestant is poisoned, it falls to her to apprehend the culprit while avoiding premature elimination from the UK Bakery Tent... and being the poisoner's next victim!\nIn Shops: Apr 12, 2023\nView All Items In This Series"
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["(W) John Allison (A) Max Sarin (CA) John Allison\nAn Agatha Christie-style murder mystery set in the world of English competitive baking from Giant Days' John Allison and Max Sarin.\nWhen she enters her country's most beloved baking competition, Shauna Wickle's goal is to delight the judges, charm the nation, and make a few friends along the way. But when a fellow contestant is poisoned, it falls to her to apprehend the culprit while avoiding premature elimination from the UK Bakery Tent... and being the poisoner's next victim!\nIn Shops: Apr 12, 2023\nView All Items In This Series"]
Entities:
[{'head': ['3', '5', 'PERSON', 'John Allison'], 'tail': ['8', '10', 'PERSON', 'Max Sarin']}]
Relation:
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}
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" LOCATION_OF\n ORGANIZED_BY\n (Note:",
" CREATED_BY",
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" CREATED_BY",
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" CREATED_BY",
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" PUBLISHER_OF",
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" SAME_PERSON",
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" AUTHOR_OF\n\n Explanation:\n The text describes John Allison",
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" HOSTED_BY",
" IN_EVENT",
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" IN_SHOPS_ON",
" IN_LOCATION"
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[
"3",
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],
[
"8",
"10",
"PERSON",
"Max Sarin"
],
[
"13",
"15",
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"John Allison"
],
[
"17",
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],
[
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[
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],
[
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[
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],
[
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],
[
"97",
"101",
"ORG",
"the UK Bakery Tent"
],
[
"114",
"118",
"DATE",
"Apr 12, 2023"
]
] | 659 |
661 | [
"The Special Kobe Bryant Jersey will be available to purchase through special ticket event link through the Dodgers website and will be given out on September 1st for the Lakers Night Promotion. It will have the No. 8 in the front and the No. 24 in the back with a snake skin type print on them. What are your thoughts?"
] | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['The Special Kobe Bryant Jersey will be available to purchase through special ticket event link through the Dodgers website and will be given out on September 1st for the Lakers Night Promotion. It will have the No. 8 in the front and the No. 24 in the back with a snake skin type print on them. What are your thoughts?']
Entities:
[{'head': ['2', '4', 'PERSON', 'Kobe Bryant'], 'tail': ['17', '18', 'ORG', 'Dodgers']}]
Relation:
| [
[
{
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}
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[
{
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}
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[
{
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}
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[
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}
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}
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}
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}
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{
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}
],
[
{
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],
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}
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[
{
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}
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}
],
[
{
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"24"
],
"tail": [
"29",
"32",
"ORG",
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]
}
]
] | [
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" HAS_BACK_NUMBER",
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" GIVEN_OUT_BY",
" HAS_NUMBER\n\n Explanation:\n The text states that the jer",
" GIVEN_OUT_BY",
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] | [
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[
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[
"39",
"40",
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"8"
],
[
"47",
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]
] | 660 |
662 | [
"Midget Mane from Statesville NC founded his Record Label Hidden Abilities. With his catchy hooks and grown content, he’s definitely a hit maker. He strives to make good music and his story telling is off the charts. Midget Mane’s new release “Don’t Fail Me” is a song about a guy that finds out his girl has been unfaithful. Check it out below!"
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Midget Mane from Statesville NC founded his Record Label Hidden Abilities. With his catchy hooks and grown content, he’s definitely a hit maker. He strives to make good music and his story telling is off the charts. Midget Mane’s new release “Don’t Fail Me” is a song about a guy that finds out his girl has been unfaithful. Check it out below!']
Entities:
[{'head': ['0', '2', 'PERSON', 'Midget Mane'], 'tail': ['3', '4', 'GPE', 'Statesville']}]
Relation:
| [
[
{
"head": [
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"2",
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],
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}
],
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{
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}
],
[
{
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}
],
[
{
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],
"tail": [
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]
}
],
[
{
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}
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[
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],
"tail": [
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}
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[
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}
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[
{
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],
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]
}
],
[
{
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],
"tail": [
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}
],
[
{
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],
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}
],
[
{
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}
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[
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}
],
[
{
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}
],
[
{
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],
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}
],
[
{
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],
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{
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}
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}
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}
],
[
{
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],
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"Hidden Abilities"
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}
],
[
{
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{
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[
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]
] | 661 |
663 | [
"Meningitis has killed no fewer than ten persons in Shagari Local Government Area of Sokoto State in the last few weeks. Chairman of the local government, Alhaji Jabbi Shagari, today said the deaths were recorded out of the several cases that are being treated across the local government.\nHe however said the epidemic has been brought under control in the area, just like in many other parts of the state. Shagari also commended the state government for donating assorted drugs and medicament worth over two million naira to the local government.\nHe said the drugs have helped tremendously in combating the menace, saying they were distributed to all the health facilities in the area and administered to victims free of charge."
] | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Meningitis has killed no fewer than ten persons in Shagari Local Government Area of Sokoto State in the last few weeks. Chairman of the local government, Alhaji Jabbi Shagari, today said the deaths were recorded out of the several cases that are being treated across the local government.\nHe however said the epidemic has been brought under control in the area, just like in many other parts of the state. Shagari also commended the state government for donating assorted drugs and medicament worth over two million naira to the local government.\nHe said the drugs have helped tremendously in combating the menace, saying they were distributed to all the health facilities in the area and administered to victims free of charge.']
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664 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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"136",
"GPE",
"Springfield"
],
"tail": [
"74",
"76",
"ORG",
"Springfield South"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"78",
"81",
"ORG",
"Outlaw Gentlemen Barbershop"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"83",
"84",
"ORDINAL",
"second"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"89",
"91",
"ORG",
"Stretch Zone"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"94",
"95",
"GPE",
"Glendale"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"105",
"106",
"NORP",
"Italian"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"109",
"112",
"ORG",
"Farmer's Wife"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"121",
"123",
"ORG",
"SBJ\n"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"123",
"126",
"ORG",
"J.E. Dunn Construction"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"127",
"128",
"LOC",
"Midwest"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"131",
"133",
"PERSON",
"Crumbl Cookies"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"138",
"139",
"ORDINAL",
"2nd"
]
}
],
[
{
"head": [
"135",
"136",
"GPE",
"Springfield"
],
"tail": [
"141",
"142",
"GPE",
"Springfield"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"12",
"14",
"PERSON",
"Derek Ankrom"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"74",
"76",
"ORG",
"Springfield South"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"78",
"81",
"ORG",
"Outlaw Gentlemen Barbershop"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"89",
"91",
"ORG",
"Stretch Zone"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"94",
"95",
"GPE",
"Glendale"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"109",
"112",
"ORG",
"Farmer's Wife"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"121",
"123",
"ORG",
"SBJ\n"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"123",
"126",
"ORG",
"J.E. Dunn Construction"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"127",
"128",
"LOC",
"Midwest"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"131",
"133",
"PERSON",
"Crumbl Cookies"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"135",
"136",
"GPE",
"Springfield"
]
}
],
[
{
"head": [
"138",
"139",
"ORDINAL",
"2nd"
],
"tail": [
"141",
"142",
"GPE",
"Springfield"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"12",
"14",
"PERSON",
"Derek Ankrom"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"15",
"17",
"DATE",
"Feb. 14"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"35",
"36",
"DATE",
"Annual"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"37",
"38",
"DATE",
"monthly"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"74",
"76",
"ORG",
"Springfield South"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"78",
"81",
"ORG",
"Outlaw Gentlemen Barbershop"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"83",
"84",
"ORDINAL",
"second"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"89",
"91",
"ORG",
"Stretch Zone"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"94",
"95",
"GPE",
"Glendale"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"105",
"106",
"NORP",
"Italian"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"109",
"112",
"ORG",
"Farmer's Wife"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"121",
"123",
"ORG",
"SBJ\n"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"123",
"126",
"ORG",
"J.E. Dunn Construction"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"127",
"128",
"LOC",
"Midwest"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"131",
"133",
"PERSON",
"Crumbl Cookies"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"135",
"136",
"GPE",
"Springfield"
]
}
],
[
{
"head": [
"141",
"142",
"GPE",
"Springfield"
],
"tail": [
"138",
"139",
"ORDINAL",
"2nd"
]
}
]
] | [
" HEARING_ON_DATE",
" HEARS_ON\n\n Explanation:\n The text states that \"",
" HEARS_ON\n\n Explanation:\n The text mentions that",
" HEARS_CASE_AGAINST",
" HEARS_CASE_AGAINST",
" HEARS_CASE_ON\n or\n JUDGES_CASE\n",
" HEARS_CASE\n\n Entities: \n [{'head': ['",
" ARGUMENTS_HEARD_BY",
" HEARS\n\n Explanation:\n The text mentions that arguments are",
" HEARS_CASE",
" HEARS_CASE_FROM",
" ARGUMENTS_HEARD_BY",
" HEARS_CASE_AT\n\n Explanation:\n The text ment",
" ARGUMENTS_HEARD_BY",
" HEARS_AT_LOCATION",
" ARGUMENTS_HEARD_BY",
" ARGUMENTS_HEARD_IN",
" HEARS_CASE",
" OPENED_ON",
" ARGUMENT_HEARD_BY",
" OPENED",
" ARG_IN_COURT_IN\n\n Explanation:\n ",
" ARGUMENT_HEARD_BY",
" HEARING_ON_CASE",
" ARGUMENTS_HEARD_BY",
" ARGUMENTS_HEARD_BY\n\n Explanation:\n The",
" ARGUMENT_HEARD_BY",
" ARG_IN_LOCATION",
" ARG_IN_LOCATION",
" HEARING_DATE",
" OPENED_ON",
" OPENED",
" OPENED",
" GRADUATED_FROM",
" CASE_HEARD_BY",
" ARGUMENTS_HEARD_BY",
" ARGUMENTS_HEARD_BY",
" APPOINTS",
" OPENING_DATE_FOR_ORGANIZATION",
" SCHEDULED_FOR\n\n Explanation:\n The text mentions",
" SCHEDULED_FOR",
" HEARING_DATE",
" OPENED_ON",
" OPENED",
" OPENED",
" GRADUATED_FROM",
" CHANGED_HANDS",
" ARGUMENTS_HEARD_BY",
" APPOINTS",
" APPOINTS",
" OPENING_DATE_OF_ENTITY",
" SCHEDULED_FOR",
" SCHEDULED_FOR",
" HEARS_CASE_FROM",
" OPENED_ON",
" OPENED_ON\n\n Explanation:\n The text mentions that",
" OPENED_ON\n\n Explanation:\n The text mentions that",
" OPENED_BY",
" OPENED_AT\n\n Explanation:\n The text mentions that",
" OPENED_BY",
" OPENED_IN",
" SHUTTERS",
" OPENED_BY",
" OPENED_BY",
" OPENED_BY",
" OPENED_IN",
" OPENED_BY",
" LOCATED_IN",
" OPENED\n\n Entities: \n [{'head': ['11",
" OPENED_IN",
" HEARS\n\n Explanation:\n The text mentions that arguments are",
" HEARING_ON_DATE",
" OPENED_AT_TIMES",
" OPENED_MONTHLY",
" OPENED_AT. In this context, \"opened\" implies a relationship of \"",
" OPENED_AT\n\n Explanation:\n The text mentions that",
" ADD_LOCATION",
" LOCATED_IN",
" ADDED_LOCATION",
" SAME_ORGANIZATION",
" OTHER_MENTIONED_IN. This relation indicates that the head entity is mentioned in the",
" NO_RELATION",
" LOCATION_IN. 'Midwest' is the location for 'Outlaw Gent",
" ADDED_LOCATION",
" OPENED_IN",
" ADDS_LOCATION",
" OPENED_IN",
" HEARS\n\n Explanation:\n The text states that \"Arguments are",
" OPENED_AT.\n\n Entities: \n [{'head':",
" OPENED_AT. The 'second location' of 'Outlaw Gentlemen Bar",
" LAUNCHED",
" GRADUATED_FROM",
" SECOND_LOCATION",
" OPENED_BY",
" APPOINTS",
" APPOINTS",
" OPENING_DELAYED",
" OPENED_IN",
" ARGUMENTS_HEARD_AT",
" HEARS_CASE_FROM",
" LAUNCHED_ON",
" LAUNCHED",
" LAUNCHED",
" LAUNCHED",
" LAUNCHED_BY",
" LAUNCHED",
" LAUNCHED_IN",
" LAUNCHED",
" LAUNCHED_BY",
" LAUNCHED",
" LAUNCHED_AFTER",
" LAUNCHED_IN",
" LAUNCHED_AFTER",
" LAUNCHED",
" LAUNCHED",
" LAUNCHED",
" JUDGE_OF",
" SCHEDULED_ON",
" GRADUATED_FROM",
" GRADUATED_FROM",
" OPENED_IN",
" GLENDEALE_GRADUATE_OF_OUTLAW_GENTLE",
" GLENDEALE_GRADUATE_IS_CEO_OF_SECOND",
" OPENED",
" GRADUATED_FROM",
" LOCATION_OF",
" GLENDEALE_GRADUATE_NAMED_CEO_OF_SB",
" 'LOCATION_OF'",
" APPOINTS",
" OPENED_BY",
" GRADUATED_FROM",
" GLENDEALE_GRADUATE_2ND_CEO",
" LOCATION_IN. 'Glendale' is the location_in 'Springfield",
" JUDGES_HEARS_CASE",
" SHUTTERS",
" OPENED_BY",
" LAUNCHED",
" GRAD_FROM",
" 'OWNER'",
" SHUTTERS",
" NO_RELATION",
" The Italian restaurant is located in the Midwest.",
" SHUTTERS",
" CLOSED_IN_LOCATION",
" SHUTTERS_IN_LOCATION",
" HEARS_CASE_FROM",
" CASE_HEARD_ON",
" CHANGED_OWNERSHIP_ANNUALLY",
" CHANGED_HANDS_MONTHLY",
" OPENED_AT\n\n Explanation:\n The text mentions that",
" SOLD_TO",
" CHANGES_HANDS_AT\n\n Explanation:\n The text",
" CHANGED_HANDS",
" LOCATED_IN",
" CHANGED_HANDS\n\n Explanation:\n The text mentions",
" CHANGES_OWNERSHIP",
" CHANGES_HANDS",
" LOCATION_IN. 'Midwest' is located in 'Farmer'",
" CHANGES_HANDS",
" LOCATED_IN",
" CHANGES_HANDS_AT\n\n Explanation:\n The text",
" LOCATED_IN",
" HEARS_CASE_FROM",
" HEARING_ON_DATE",
" ARGUMENT_SCHEDULED_ON",
" ARGUMENT_SCHEDULED_ON",
" OPENED",
" OPENED_BY",
" OPENED_AT\n\n Explanation:\n The text mentions that",
" LAUNCHED",
" GRAD_FROM",
" SHUTTERS",
" CHANGES_HANDS",
" APPOINTS",
" APPOINTS",
" OPENING_OF",
" LOCATION_IN.",
" OPENING_AT_TIME",
" ARGUMENTS_HEARD_IN",
" APPOINTS",
" ARG_1_HAS_EVENT\n OR\n EVENT_IS_FOR_",
" APPOINTS",
" APPOINTS",
" APPOINTS",
" APPOINTED_BY",
" APPOINTS",
" APPOINTED_BY",
" J_E_Dunn_Construction_is_located_in_Glend",
" APPOINTS",
" APPOINTED_BY",
" APPOINTS",
" APPOINTS\n\n Entities: \n [{'head': ['12",
" APPOINTS",
" APPOINTS_IN_LOCATION",
" APPOINTS",
" APPOINTS_IN_LOCATION",
" HEARS\n\n Explanation:\n The text mentions that arguments are",
" HEARING_ON_DATE",
" APPOINTS",
" APPOINTS",
" OPENED_IN",
" LOCATION_OF",
" APPOINTS",
" LAUNCHED",
" LOCATION_IN. 'Glendale' is located in the 'Midwest",
" REGION_OF\n\n Explanation:\n The text mentions that J",
" LOCATION_IN\n\n Explanation:\n The text mentions that",
" APPOINTS",
" APPOINTS",
" APPOINTS",
" REGION_IN\n\n Explanation:\n The text mentions \"J",
" APPOINTS",
" APPOINTS_TO\n\n Explanation:\n The text mentions that",
" ARGUMENTS_HEARD_BY",
" OPENING_ON\n\n Explanation:\n The text mentions that",
" OPENS_ON\n\n Explanation:\n The text mentions that Cr",
" OPENS_ON\n\n Explanation:\n The text mentions that \"",
" OPENS_AT\n\n Explanation:\n The text mentions that \"",
" OPPOSED_BY",
" PUSHES_BACK_OPENING_SECOND_TIME",
" OPENED_BY",
" OPENED_IN",
" OPENED_BY",
" CHANGES_HANDS",
" OPENED_BY",
" APPOINTS",
" APPOINTS_REGION_PRESIDENT",
" OPENING_IN",
" PUSHES_BACK_OPENING_A_SECOND_TIME",
" OPENS_IN",
" HEARS_CASE_FROM",
" HEARING_ON_DATE",
" LOCATION_OF\n or\n HOSTS\n\n Explanation",
" OPENED_ON",
" LOCATED_IN",
" LOCATED_IN",
" OPENED_AT\n\n Explanation:\n The text mentions that",
" LAUNCHED",
" LOCATION_IN\n\n Explanation:\n The text mentions that",
" SHUTTERS",
" LOCATED_IN",
" LOCATION_OF\n or\n PUBLISHER_OF\n ",
" LOCATION_OF",
" APPOINTS\n\n Explanation:\n The text mentions that J.",
" OPENING_AT\n\n Explanation:\n The text mentions that",
" OPENING_AT_TIME",
" LOCATION_IN. \n\n Explanation:\n The text ment",
" HEARS\n\n Explanation:\n The text states that \"Arguments are",
" OPENED_BY",
" OPENED_AT. The 'head' entity represents the time when the 'tail'",
" LAUNCHED",
" OPENED_IN",
" CHANGES_HANDS",
" PRECEDES",
" OPENED_BY",
" APPOINTS",
" OPENING_DELAYED",
" OPENING_AT.",
" OPENING_IN.",
" HEARS_CASE_FROM",
" DISCOURSE_EVENT_DATE",
" SCHEDULED_ON",
" ARGUMENT_SCHEDULED_ON",
" OPENED_AT",
" OPENED_AT. In this context, \"This item is for subscribers only",
" The arguments are scheduled to be heard on the second.",
" LAUNCHED",
" LOCATION_IN. \n\n Explanation:\n The text ment",
" SHUTTERS",
" LOCATED_IN",
" ARGUMENTS_HEARD_BY",
" The arguments are scheduled to be heard by Judge Derek Ankrom in Springfield.\n",
" APPOINTS\n\n Explanation:\n The text mentions that J.",
" OPENING_AT\n\n Explanation:\n The text mentions that",
" arguments_are_scheduled_to_be_heard_in",
" OPENING_ON\n\n Explanation:\n The text mentions that"
] | [
[
"12",
"14",
"PERSON",
"Derek Ankrom"
],
[
"15",
"17",
"DATE",
"Feb. 14"
],
[
"35",
"36",
"DATE",
"Annual"
],
[
"37",
"38",
"DATE",
"monthly"
],
[
"74",
"76",
"ORG",
"Springfield South"
],
[
"78",
"81",
"ORG",
"Outlaw Gentlemen Barbershop"
],
[
"83",
"84",
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"second"
],
[
"89",
"91",
"ORG",
"Stretch Zone"
],
[
"94",
"95",
"GPE",
"Glendale"
],
[
"105",
"106",
"NORP",
"Italian"
],
[
"109",
"112",
"ORG",
"Farmer's Wife"
],
[
"121",
"123",
"ORG",
"SBJ\n"
],
[
"123",
"126",
"ORG",
"J.E. Dunn Construction"
],
[
"127",
"128",
"LOC",
"Midwest"
],
[
"131",
"133",
"PERSON",
"Crumbl Cookies"
],
[
"135",
"136",
"GPE",
"Springfield"
],
[
"138",
"139",
"ORDINAL",
"2nd"
],
[
"141",
"142",
"GPE",
"Springfield"
]
] | 664 |
666 | [
"PHOTOGRAPHER SCOTT KRYCIA WINS AWARD\nOne Eye Land Photography Awards - Black & White\nOne EyeLand is an annual competition for photographers on a global scale, creating one of the most ambitious and comprehensive competitions in the photography world today.\nKrycia’s moody Black & White photography titled Rhyolite, won a bronze in the Landscape Category.\nKrycia's image is series of 300 frames stacked into a 'Star Trails' shot of the old hotel. The image was shot in January 2022.\nRhyolite is a ghost town in Nye County, in the U.S. state of Nevada. It is in the Bullfrog Hills, about 120 miles northwest of Las Vegas, near the eastern boundary of Death Valley National Park."
] | [
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]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["PHOTOGRAPHER SCOTT KRYCIA WINS AWARD\nOne Eye Land Photography Awards - Black & White\nOne EyeLand is an annual competition for photographers on a global scale, creating one of the most ambitious and comprehensive competitions in the photography world today.\nKrycia’s moody Black & White photography titled Rhyolite, won a bronze in the Landscape Category.\nKrycia's image is series of 300 frames stacked into a 'Star Trails' shot of the old hotel. The image was shot in January 2022.\nRhyolite is a ghost town in Nye County, in the U.S. state of Nevada. It is in the Bullfrog Hills, about 120 miles northwest of Las Vegas, near the eastern boundary of Death Valley National Park."]
Entities:
[{'head': ['1', '3', 'PERSON', 'SCOTT KRYCIA'], 'tail': ['4', '6', 'WORK_OF_ART', 'AWARD\n']}]
Relation:
| [
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"20",
"21",
"DATE",
"annual"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"42",
"43",
"DATE",
"today"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"48",
"51",
"WORK_OF_ART",
"Black & White"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"53",
"54",
"WORK_OF_ART",
"Rhyolite"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"70",
"71",
"CARDINAL",
"300"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"76",
"78",
"WORK_OF_ART",
"Star Trails"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"90",
"92",
"DATE",
"January 2022"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"117",
"119",
"CARDINAL",
"about 120"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"20",
"21",
"DATE",
"annual"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"42",
"43",
"DATE",
"today"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"48",
"51",
"WORK_OF_ART",
"Black & White"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"53",
"54",
"WORK_OF_ART",
"Rhyolite"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"70",
"71",
"CARDINAL",
"300"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"76",
"78",
"WORK_OF_ART",
"Star Trails"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"90",
"92",
"DATE",
"January 2022"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"117",
"119",
"CARDINAL",
"about 120"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"12",
"15",
"ORG",
"Black & White"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"20",
"21",
"DATE",
"annual"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
],
[
{
"head": [
"42",
"43",
"DATE",
"today"
],
"tail": [
"130",
"134",
"LOC",
"Death Valley National Park"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"12",
"15",
"ORG",
"Black & White"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"20",
"21",
"DATE",
"annual"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"42",
"43",
"DATE",
"today"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"48",
"51",
"WORK_OF_ART",
"Black & White"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"53",
"54",
"WORK_OF_ART",
"Rhyolite"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"70",
"71",
"CARDINAL",
"300"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"76",
"78",
"WORK_OF_ART",
"Star Trails"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"90",
"92",
"DATE",
"January 2022"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"45",
"46",
"PERSON",
"Krycia"
],
"tail": [
"117",
"119",
"CARDINAL",
"about 120"
]
}
],
[
{
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"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"20",
"21",
"DATE",
"annual"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"42",
"43",
"DATE",
"today"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"45",
"46",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"48",
"51",
"WORK_OF_ART",
"Black & White"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"53",
"54",
"WORK_OF_ART",
"Rhyolite"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"64",
"65",
"PERSON",
"Krycia"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"70",
"71",
"CARDINAL",
"300"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"76",
"78",
"WORK_OF_ART",
"Star Trails"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"90",
"92",
"DATE",
"January 2022"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"94",
"95",
"GPE",
"Rhyolite"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"100",
"102",
"GPE",
"Nye County"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"105",
"106",
"GPE",
"U.S."
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"108",
"109",
"GPE",
"Nevada"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"113",
"116",
"LOC",
"the Bullfrog Hills"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"117",
"119",
"CARDINAL",
"about 120"
]
}
],
[
{
"head": [
"130",
"134",
"LOC",
"Death Valley National Park"
],
"tail": [
"122",
"124",
"GPE",
"Las Vegas"
]
}
]
] | [
" WON_AWARD",
" WON_AWARD",
" WIN_AWARD",
" One EyeLand_is_an_annual_competition_for_photograph",
" NO_RELATION",
" SAME_AS",
" CREATED_BY",
" CREATED_BY",
" SAME_AS",
" TAKEN_PHOTO_OF\n\n Explanation:\n The",
" CREATED_BY",
" PHOTOGRAPHED_ON",
" TAKEN_PHOTO_OF",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_NEAR.",
" NEAR_CITY",
" NEAR.",
" WIN_AWARD",
" WON_AWARD",
" WIN_AWARD",
" CREATED_AWARD\n\n Explanation:\n The text states",
" CREATED_IN",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF",
" WIN_AWARD",
" HOSTED_BY",
" WIN_AWARD",
" WON_AWARD",
" AWARDED_AT\n\n Explanation:\n The text states that \"",
" LOCATION_OF.",
" HOSTED_IN",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" HOSTED_IN",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" HOSTED_AT",
" WINNER_OF\n\n Explanation:\n The text states that \"S",
" CATEGORY_WINNER",
" HOSTED_BY",
" ANNUAL_EVENT_HAS_TIME\n\n Entities: \n [",
" ANNUAL_EVENT_OCCURS_ON\n\n Entities: ",
" WINNER_OF\n\n Explanation:\n The text states that \"K",
" CATEGORY_WINNER",
" CATEGORY_WINNER",
" WINNER_OF\n\n Explanation:\n The text states that \"K",
" NUMBER_OF_FRAMES",
" CATEGORY_WINNER",
" TEMP_EVENT_STARTED\n\n Entities: \n [{'head",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_IN.",
" LOCATION.\n\n Explanation:\n The text states that \"R",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_NEAR.",
" NEAR_CITY",
" NEAR.",
" WIN\n\n Entities: \n [{'head': ['One EyeLand'],",
" ANNUAL_EVENT_CATEGORY",
" WIN_AWARD",
" WIN\n\n Entities: \n [{'head': ['64', '",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" ANNUAL_IN_COUNTRY",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_NEAR.",
" NO_RELATION.",
" NEAR.",
" NO_RELATION",
" COMPETITION_WON\n\n Entities: \n [{'head",
" NO_RELATION",
" NO_RELATION",
" LOCATION_OF\n or\n NO_RELATION (if 'Rhy",
" LOCATION_OF",
" LOCATION_IN.",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_NEARBY",
" NO_RELATION.",
" NEAR_LOCATION",
" 'WIN'",
" WIN\n\n Entities: \n [{'head': ['4', '6",
" WIN_AWARD",
" WIN_AWARD",
" ANNUAL_EVENT_HAS_START_DATE",
" NO_RELATION",
" CREATED_BY",
" CREATED_BY",
" SELF_REFERENCE",
" TAKEN_PHOTO_OF\n\n Explanation:\n The",
" CREATED_BY",
" Took_Place_On",
" TAKEN_AT_LOCATION",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that K",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_DISTANCE",
" NEAR_CITY",
" NEAR_LOCATION",
" CREATED_BY",
" WIN_AWARD",
" CREATED_BY",
" CREATED_BY",
" CREATED_IN",
" LOCATION_OF",
" LOCATION_OF. (The work of art is located in the country.)",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF. (The work of art is located in Las Vegas.)",
" LOCATION_OF",
" CREATED_BY",
" WON_AWARD_IN",
" CREATED_BY",
" CREATED_BY",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF. (The work of art Rhyolite is located in the",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" LOCATION_OF",
" WIN\n\n Entities: \n [{'head': ['1', '3",
" WIN\n\n Entities: \n [{'head': ['4', '6",
" WIN_AWARD",
" WIN_AWARD",
" ANNUAL_EVENT_STARTS_YEAR",
" NO_RELATION",
" SELF_REFERENCE",
" CREATED_BY",
" CREATED_BY",
" TAKEN_PHOTO_OF\n\n Explanation:\n The",
" CREATED_BY",
" PHOTOGRAPHED_ON",
" TAKEN_PHOTO_OF",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that K",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_NEAR.",
" NEAR_CITY",
" NEAR_LOCATION",
" TAKEN_PHOTO_OF",
" WIN\n\n Entities: \n [{'head': ['Scott Kry",
" TAKEN_PHOTO_OF",
" TAKEN_PHOTO_OF",
" TAKEN_AT_LOCATION",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" LOCATION_OF",
" LOCATION_OF",
" NEAR_CITY",
" NEAR.",
" CREATED_BY",
" WON_AWARD_IN",
" CREATED_BY",
" CREATED_BY",
" CREATED_IN",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF",
" PHOTOGRAPHED_ON",
" AWARDED_BY",
" PHOTOGRAPHED_ON",
" PHOTOGRAPHED_ON",
" PHOTOGRAPHED_AT",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" EVENT_LOCATION",
" LOCATION_OF\n\n Explanation:\n The text states that the",
" THE_EVENT_TOOK_PLACE_AT\n\n Explanation:\n",
" EVENT_LOCATION",
" IMAGE_TAKEN_AT_LOCATION",
" LOCATION_OF\n OR\n PHOTOGRAPHED_AT\n",
" LOCATION_OF\n OR\n PRODUCED_AT\n\n ",
" WIN_AWARD",
" WIN_AWARD_IN\n\n Explanation:\n The text states",
" LOCATION_OF\n OR\n HOST_OF\n OR\n ",
" LOCATION_TIME\n\n Explanation:\n The text states that R",
" LOCATION_OF\n or\n PHOTO_TAKEN_AT\n",
" LOCATION_OF\n OR\n SUBJECT_OF\n OR\n ",
" WORK_OF_ART_IS_LOCATED_IN\n or\n LO",
" LOCATION_OF\n or\n PHOTO_TAKEN_AT\n",
" SUBJECT_OF_WORK_FOR_PHOTOGRAPHER",
" LOCATION_OF\n or\n SUBJECT_OF\n or\n ",
" LOCATION_TIME",
" LOCATED_IN",
" LOCATED_IN",
" LOCATION_IN\n\n Explanation:\n The text states that R",
" LOCATION_NEARS\n\n Explanation:\n The text states",
" LOCATION_NEAR.",
" NEAR_CITY",
" NEAR.",
" LOCATED_IN",
" LOCATION_OF\n\n Explanation:\n The text states that N",
" LOCATION_OF\n\n Explanation:\n The text states that N",
" LOCATION_OF\n\n Explanation:\n The text states that N",
" LOCATION_OF\n\n Explanation:\n The text states that N",
" LOCATION_NEAR\n\n Explanation:\n The text mentions",
" LOCATION_OF",
" LOCATION_OF\n OR\n BELONGS_TO\n\n ",
" LOCATION_OF",
" LOCATION_OF",
" NEAR.",
" LOCATION_OF\n or\n PRODUCED_AT\n\n ",
" LOCATION_TIME",
" LOCATION_OF",
" LOCATED_IN",
" LOCATION_IN\n\n Explanation:\n The text states that N",
" LOCATION_IN\n\n Explanation:\n The text states that N",
" NEAR.",
" NEAR_CITY",
" NEAR.",
" LOCATION_OF.",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" HOSTED_BY",
" HOST_THEME\n\n Explanation:\n The text mentions that",
" ANNUAL_EVENT_IN_LOCATION",
" NO_RELATION",
" LOCATION_OF\n\n Explanation:\n The text states that K",
" LOCATION_OF\n or\n PRODUCED_AT\n\n ",
" LOCATION_OF",
" LOCATION_OF. (The location is where the photographer is from or based.)",
" NEAR_LOCATION",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" EVENT_DATE",
" LOCATION_IN.",
" LOCATION_IN.",
" LOCATION_IN.",
" LOCATION_IN.",
" NEAR.",
" NEAR.",
" NEAR.",
" LOCATION_OF",
" LOCATION_OF.",
" HOSTED_BY",
" LOCATION_OF\n OR LOCATED_IN (both are valid)",
" LOCATION_OF\n OR\n HOST_OF\n\n [{'",
" LOCATION_NEAR\n\n Explanation:\n The text mentions",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_OF\n Or\n NO_RELATION\n\n Explan",
" LOCATION_OF\n\n Explanation:\n The text states that R",
" LOCATION_IN\n\n Explanation:\n The text states that R",
" LOCATION_IN.",
" LOCATION_IN.",
" LOCATION_IN\n\n Explanation:\n The text states that R",
" LOCATION_IN.",
" NEAR.",
" NEAR_CITY",
" NEAR.",
" LOCATION_OF",
" LOCATION_OF\n\n Explanation:\n The text states that \"",
" LOCATION_OF\n OR\n HOSTED_AT\n\n The",
" LOCATION_OF\n\n [{'head': ['113', '1",
" LOCATION_OF\n OR\n HOSTED_AT\n\n [",
" LOCATION_NEAR\n\n Explanation:\n The text mentions",
" LOCATION_OF",
" LOCATION_OF\n\n [{'head': ['48', '51",
" LOCATION_OF",
" LOCATION_OF",
" LOCATION_NEAR\n\n Explanation:\n The text states that",
" LOCATION_OF\n Or\n LOCATION_WAS_PHOT",
" LOCATION_AT_TIME",
" LOCATION_OF",
" LOCATION_IN.\n This relation indicates that the Bullfrog Hills is a",
" LOCATED_IN",
" LOCATION_IN.",
" LOCATION_NEARBY",
" NEAR_CITY",
" NEAR_BY",
" LOCATED_IN",
" LOCATION_NEAR. This is because the location is near the competition, not the",
" LOCATION_NEAR.",
" LOCATION_NEAR.",
" LOCATION_NEAR.",
" LOCATION_OF",
" NEAR_LOCATION",
" NEAR.",
" LOCATION_NEAR.",
" APPROXIMATE_LOCATION",
" NEAR.",
" NEAR_CITY",
" NEAR_LOCATION",
" NEAR_LOCATION",
" NEAR_CITY",
" NO_RELATION",
" NO_RELATION",
" NEAR_CITY",
" NEAR_LOCATION",
" NEAR_LOCATION",
" NEAR_CITY",
" NEAR_CITY",
" NEAR_LOCATION",
" LOCATION_NEAR\n\n Explanation:\n The text mentions",
" NEAR_CITY",
" NEAR_LOCATION",
" NO_RELATION. The text does not provide enough context to determine a relation between 'L",
" NEAR_LOCATION",
" NEAR_LOCATION",
" DISTANCE",
" NEARBY",
" NEAR.",
" NEAR_LOCATION",
" LOCATION_OF\n OR\n HOST_OF\n OR\n ",
" NEAR_LOCATION",
" HOST_OF",
" NEAR_LOCATION",
" NEAR.",
" NEAR_LOCATION",
" NEAR.",
" NEAR.",
" NEAR.",
" NEAR. This text does not provide enough context to determine a specific relation between the entities,",
" NEAR_LOCATION",
" NEAR_BY",
" NEAR_BY",
" NEAR_LOCATION",
" NEAR_BY",
" NEARBY",
" NEAR.",
" NEARBY"
] | [
[
"1",
"3",
"PERSON",
"SCOTT KRYCIA"
],
[
"4",
"6",
"WORK_OF_ART",
"AWARD\n"
],
[
"6",
"11",
"WORK_OF_ART",
"One Eye Land Photography Awards"
],
[
"12",
"15",
"ORG",
"Black & White"
],
[
"20",
"21",
"DATE",
"annual"
],
[
"42",
"43",
"DATE",
"today"
],
[
"45",
"46",
"PERSON",
"Krycia"
],
[
"48",
"51",
"WORK_OF_ART",
"Black & White"
],
[
"53",
"54",
"WORK_OF_ART",
"Rhyolite"
],
[
"64",
"65",
"PERSON",
"Krycia"
],
[
"70",
"71",
"CARDINAL",
"300"
],
[
"76",
"78",
"WORK_OF_ART",
"Star Trails"
],
[
"90",
"92",
"DATE",
"January 2022"
],
[
"94",
"95",
"GPE",
"Rhyolite"
],
[
"100",
"102",
"GPE",
"Nye County"
],
[
"105",
"106",
"GPE",
"U.S."
],
[
"108",
"109",
"GPE",
"Nevada"
],
[
"113",
"116",
"LOC",
"the Bullfrog Hills"
],
[
"117",
"119",
"CARDINAL",
"about 120"
],
[
"122",
"124",
"GPE",
"Las Vegas"
],
[
"130",
"134",
"LOC",
"Death Valley National Park"
]
] | 665 |
667 | [
"I love a party and I am always delighted to be invited to capture a celebration particularly when it involves taking photographs of gorgeous, fun loving people enjoying themselves, having a fabulous time and I get to get onto the dance floor with my cameras!\nEach celebration and story is unique. This gorgeous lady, Thea, celebrated her 21st birthday in style with a themed “Back to the Future” party in a stunning teepee tent in Yorkshire. The main theme to have been adopted was Indian in flavour which created a wonderful colourful backdrop to capture.\nI love my work!\nIf you are planning a celebration and looking for a photographer please contact the studio on 020 8748 1988 or email firstname.lastname@example.org if you would like any further information."
] | [
[
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"\n",
"I",
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"!",
"\n",
"If",
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"please",
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"email",
"firstname.lastname@example.org",
"if",
"you",
"would",
"like",
"any",
"further",
"information",
"."
]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['I love a party and I am always delighted to be invited to capture a celebration particularly when it involves taking photographs of gorgeous, fun loving people enjoying themselves, having a fabulous time and I get to get onto the dance floor with my cameras!\nEach celebration and story is unique. This gorgeous lady, Thea, celebrated her 21st birthday in style with a themed “Back to the Future” party in a stunning teepee tent in Yorkshire. The main theme to have been adopted was Indian in flavour which created a wonderful colourful backdrop to capture.\nI love my work!\nIf you are planning a celebration and looking for a photographer please contact the studio on 020 8748 1988 or email firstname.lastname@example.org if you would like any further information.']
Entities:
[{'head': ['60', '61', 'PERSON', 'Thea'], 'tail': ['64', '65', 'ORDINAL', '21st']}]
Relation:
| [
[
{
"head": [
"60",
"61",
"PERSON",
"Thea"
],
"tail": [
"64",
"65",
"ORDINAL",
"21st"
]
}
],
[
{
"head": [
"60",
"61",
"PERSON",
"Thea"
],
"tail": [
"84",
"85",
"GPE",
"Yorkshire"
]
}
],
[
{
"head": [
"60",
"61",
"PERSON",
"Thea"
],
"tail": [
"94",
"95",
"NORP",
"Indian"
]
}
],
[
{
"head": [
"64",
"65",
"ORDINAL",
"21st"
],
"tail": [
"60",
"61",
"PERSON",
"Thea"
]
}
],
[
{
"head": [
"64",
"65",
"ORDINAL",
"21st"
],
"tail": [
"84",
"85",
"GPE",
"Yorkshire"
]
}
],
[
{
"head": [
"84",
"85",
"GPE",
"Yorkshire"
],
"tail": [
"60",
"61",
"PERSON",
"Thea"
]
}
],
[
{
"head": [
"84",
"85",
"GPE",
"Yorkshire"
],
"tail": [
"64",
"65",
"ORDINAL",
"21st"
]
}
],
[
{
"head": [
"84",
"85",
"GPE",
"Yorkshire"
],
"tail": [
"94",
"95",
"NORP",
"Indian"
]
}
],
[
{
"head": [
"94",
"95",
"NORP",
"Indian"
],
"tail": [
"60",
"61",
"PERSON",
"Thea"
]
}
],
[
{
"head": [
"94",
"95",
"NORP",
"Indian"
],
"tail": [
"84",
"85",
"GPE",
"Yorkshire"
]
}
]
] | [
" BIRTHDAY",
" CELEBRATED_IN",
" THEME_OF",
" CELEBRATED_BY",
" CELEBRATED_IN",
" CELEBRATED_IN",
" THEME_OF\n\n Explanation:\n The text mentions that \"",
" THEME_OF",
" THEME_OF",
" THEME_OF\n\n Explanation:\n The text mentions that the"
] | [
[
"60",
"61",
"PERSON",
"Thea"
],
[
"64",
"65",
"ORDINAL",
"21st"
],
[
"84",
"85",
"GPE",
"Yorkshire"
],
[
"94",
"95",
"NORP",
"Indian"
]
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[
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] | 667 |
669 | [
"Kroya by Chef Chanrith\nKroya which means “food” in the Khmer Royal language is the Shinta Mani Angkor’s unique restaurant inspired by Shinta Mani’s heritage. Our menu blends local products, combines fresh ingredients, native herbs and spices to create innovative, palette pleasing flavours.\nChef Chanrith has used his lifelong wealth of experience to create a new fine dining concept featuring modern interpretations of the Khmer recipes from his youth. Presented with flair and\nprepared with modern techniques, Chef Chanrith will take you on a culinary exploration of his vision for the future of Khmer cuisine.\nSet Menus & Signature Cocktails\n- Email: firstname.lastname@example.org"
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Kroya by Chef Chanrith\nKroya which means “food” in the Khmer Royal language is the Shinta Mani Angkor’s unique restaurant inspired by Shinta Mani’s heritage. Our menu blends local products, combines fresh ingredients, native herbs and spices to create innovative, palette pleasing flavours.\nChef Chanrith has used his lifelong wealth of experience to create a new fine dining concept featuring modern interpretations of the Khmer recipes from his youth. Presented with flair and\nprepared with modern techniques, Chef Chanrith will take you on a culinary exploration of his vision for the future of Khmer cuisine.\nSet Menus & Signature Cocktails\n- Email: firstname.lastname@example.org']
Entities:
[{'head': ['0', '1', 'ORG', 'Kroya'], 'tail': ['3', '4', 'PERSON', 'Chanrith']}]
Relation:
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Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['yarn: (1) a continuous strand of twisted fibers used in weaving or knitting, (2) a narrative of adventures.\nSaturday, December 8, 2012\nA Little Bit of Cheer\nLast night, The Man and I went to downtown Atascadero to see their "Winter Wonderland". Over 50 tons of shave ice was used to make a snow mountain for the kids and adults to sled down. I looked at The Man but he said, "don\'t even think about it" just before a couple of kids tumbled off their sleds. Instead of risking bodily injury we opted for free hot cocoa (and literature) from one of the church boothsand bought cotton candy freshly-made by the Pozo 4-H club. Huge cones of pink awesomeness. Feeling very festiveafter so much sugar,we drove to downtown San Luis Obispo and watched their Christmas parade. Perfect weather as usual.']
Entities:
[{'head': ['3', '4', 'CARDINAL', '1'], 'tail': ['49', '50', 'GPE', 'Atascadero']}]
Relation:
| [
[
{
"head": [
"3",
"4",
"CARDINAL",
"1"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"3",
"4",
"CARDINAL",
"1"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"3",
"4",
"CARDINAL",
"1"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"3",
"4",
"CARDINAL",
"1"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"18",
"19",
"CARDINAL",
"2"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"18",
"19",
"CARDINAL",
"2"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"18",
"19",
"CARDINAL",
"2"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"18",
"19",
"CARDINAL",
"2"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"39",
"41",
"TIME",
"Last night"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"39",
"41",
"TIME",
"Last night"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"39",
"41",
"TIME",
"Last night"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"39",
"41",
"TIME",
"Last night"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"3",
"4",
"CARDINAL",
"1"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"18",
"19",
"CARDINAL",
"2"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"39",
"41",
"TIME",
"Last night"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"49",
"50",
"GPE",
"Atascadero"
],
"tail": [
"166",
"167",
"DATE",
"Christmas"
]
}
],
[
{
"head": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"3",
"4",
"CARDINAL",
"1"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"18",
"19",
"CARDINAL",
"2"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"39",
"41",
"TIME",
"Last night"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"83",
"85",
"PERSON",
"The Man"
],
"tail": [
"166",
"167",
"DATE",
"Christmas"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"3",
"4",
"CARDINAL",
"1"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"18",
"19",
"CARDINAL",
"2"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"39",
"41",
"TIME",
"Last night"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
],
[
{
"head": [
"138",
"141",
"ORG",
"4-H"
],
"tail": [
"166",
"167",
"DATE",
"Christmas"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"3",
"4",
"CARDINAL",
"1"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"18",
"19",
"CARDINAL",
"2"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"39",
"41",
"TIME",
"Last night"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"58",
"61",
"QUANTITY",
"Over 50 tons"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"160",
"163",
"GPE",
"San Luis Obispo"
],
"tail": [
"166",
"167",
"DATE",
"Christmas"
]
}
],
[
{
"head": [
"166",
"167",
"DATE",
"Christmas"
],
"tail": [
"49",
"50",
"GPE",
"Atascadero"
]
}
],
[
{
"head": [
"166",
"167",
"DATE",
"Christmas"
],
"tail": [
"83",
"85",
"PERSON",
"The Man"
]
}
],
[
{
"head": [
"166",
"167",
"DATE",
"Christmas"
],
"tail": [
"138",
"141",
"ORG",
"4-H"
]
}
],
[
{
"head": [
"166",
"167",
"DATE",
"Christmas"
],
"tail": [
"160",
"163",
"GPE",
"San Luis Obispo"
]
}
]
] | [
" WE_WENT_TO",
" WENT_WITH",
" MADE_BY",
" WENT_TO",
" WE_WENT_TO",
" WENT_WITH",
" MADE_BY",
" WENT_TO",
" LOCATION.IN.EVENT",
" WENT_TO",
" MADE_BY",
" WENT_TO",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" AUTHOR_OF\n\n Explanation:\n The text describes an event where",
" PRODUCED_BY",
" WENT_TO",
" LOCATION_AT_TIME",
" WENT_WITH",
" MADE_BY",
" WENT_TO",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" WE_SAW\n\n Explanation:\n The text describes The Man and",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" LOCATION_OF\n or\n VENUE_OF\n or\n",
" SETTING",
" LOCATION_OF\n OR\n HOST_OF\n OR\n ",
" USED_FOR\n\n Explanation:\n The text states that \"Over",
" WENT_TO",
" MADE_BY",
" NEAR_CITY",
" EVENT_STARTED_ON_LOCATION",
" LOCATION_OF\n\n Entities: \n [{'head': ['",
" WENT_TO",
" PRODUCED_BY",
" WENT_TO",
" USED_FOR_PRODUCING",
" PROVIDES_QUANTITY",
" USED_BY",
" WENT_TO",
" WENT_TO",
" WENT_TO",
" GOES_ON\n\n Explanation:\n The relation GOES_ON",
" WROTE\n\n Explanation:\n The text describes 'The Man'",
" EVENT_STARTED\n\n Entities: \n [{'head': ['3",
" WENT_TO",
" WENT_TO",
" USED_FOR\n\n Explanation:\n The text states that \"Over",
" MADE_BY",
" WENT_TO",
" WENT_TO\n\n Explanation:\n The entities represent 'The Man",
" MADE_BY",
" MADE_BY",
" PROVIDES_MATERIAL\n\n Explanation:\n The context mentions",
" PRODUCED_BY",
" MADE_FOR\n\n Explanation:\n The text describes how the ",
" PROVIDES_SERVICE",
" MADE_BY",
" USED_FOR\n\n Explanation:\n The text states that \"the",
" SOLD_BY",
" SOLD_GOODS_AT\n\n Explanation:\n The text",
" SOLD_GOODS_BY\n\n Explanation:\n The text",
" WATCHED",
" WATCHED",
" LOCATION_OF\n Or\n NO_RELATION (if no relation exists",
" LOCATION_OF\n or\n EVENT_LOCATION\n or\n ",
" WE_SAW\n\n Explanation:\n The text describes an event where",
" FROM_LOCATION\n\n Explanation:\n The text describes The Man and",
" LOCATION_OF\n or\n HOST_OF\n or\n ",
" HAS_QUANTITY\n\n Entities: \n [{'head':",
" WATCHED",
" SOLD_BY",
" PARTI_OF \n\n Explanation:\n The text describes the authors",
" WE_SAW\n\n Entities: \n [{'head': ['4",
" WENT_TO",
" SOLD_GOODS_BY",
" WATCHED_IN\n\n Explanation:\n The text describes The"
] | [
[
"3",
"4",
"CARDINAL",
"1"
],
[
"18",
"19",
"CARDINAL",
"2"
],
[
"26",
"32",
"DATE",
"Saturday, December 8, 2012"
],
[
"33",
"38",
"WORK_OF_ART",
"A Little Bit of Cheer"
],
[
"39",
"41",
"TIME",
"Last night"
],
[
"49",
"50",
"GPE",
"Atascadero"
],
[
"54",
"56",
"WORK_OF_ART",
"Winter Wonderland"
],
[
"58",
"61",
"QUANTITY",
"Over 50 tons"
],
[
"83",
"85",
"PERSON",
"The Man"
],
[
"138",
"141",
"ORG",
"4-H"
],
[
"160",
"163",
"GPE",
"San Luis Obispo"
],
[
"166",
"167",
"DATE",
"Christmas"
]
] | 670 |
672 | [
"Originally from Madrid, Antonio Merinero is a graphic illustrator. He also travels the world on a motorcycle. Traveling feeds Antonio's imagination and much of his inspiration comes from his visits to Asia. He has worked with artists who create the Bollywood film posters, but also painters of trucks in India and Thailand.\nDrawing, airbrushing, photography and collage are the mediums that this artist blends to produce his unique and illuminated style.\nAntonio is riding down up from Madrid to join us in Biarritz for Wheels and Waves on his old Electra Glide and sleeping beneath the stars... Bon voyage!\nDon't miss Antonio's exhibition next Friday"
] | [
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"Biarritz",
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"and",
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"on",
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"Electra",
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"and",
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"beneath",
"the",
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"...",
"Bon",
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"!",
"\n",
"Do",
"n't",
"miss",
"Antonio",
"'s",
"exhibition",
"next",
"Friday"
]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["Originally from Madrid, Antonio Merinero is a graphic illustrator. He also travels the world on a motorcycle. Traveling feeds Antonio's imagination and much of his inspiration comes from his visits to Asia. He has worked with artists who create the Bollywood film posters, but also painters of trucks in India and Thailand.\nDrawing, airbrushing, photography and collage are the mediums that this artist blends to produce his unique and illuminated style.\nAntonio is riding down up from Madrid to join us in Biarritz for Wheels and Waves on his old Electra Glide and sleeping beneath the stars... Bon voyage!\nDon't miss Antonio's exhibition next Friday"]
Entities:
[{'head': ['2', '3', 'GPE', 'Madrid'], 'tail': ['4', '6', 'PERSON', 'Antonio Merinero']}]
Relation:
| [
[
{
"head": [
"2",
"3",
"GPE",
"Madrid"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
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"Madrid"
],
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"Antonio"
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}
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{
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"84",
"PERSON",
"Antonio"
],
"tail": [
"120",
"122",
"DATE",
"next Friday"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"94",
"95",
"GPE",
"Biarritz"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"96",
"99",
"ORG",
"Wheels and Waves"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"102",
"104",
"PRODUCT",
"Electra Glide"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"117",
"118",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"89",
"90",
"GPE",
"Madrid"
],
"tail": [
"120",
"122",
"DATE",
"next Friday"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"89",
"90",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"96",
"99",
"ORG",
"Wheels and Waves"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"102",
"104",
"PRODUCT",
"Electra Glide"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"117",
"118",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"94",
"95",
"GPE",
"Biarritz"
],
"tail": [
"120",
"122",
"DATE",
"next Friday"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"89",
"90",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"94",
"95",
"GPE",
"Biarritz"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"102",
"104",
"PRODUCT",
"Electra Glide"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"117",
"118",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"96",
"99",
"ORG",
"Wheels and Waves"
],
"tail": [
"120",
"122",
"DATE",
"next Friday"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"89",
"90",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"94",
"95",
"GPE",
"Biarritz"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"96",
"99",
"ORG",
"Wheels and Waves"
]
}
],
[
{
"head": [
"102",
"104",
"PRODUCT",
"Electra Glide"
],
"tail": [
"117",
"118",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"89",
"90",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"94",
"95",
"GPE",
"Biarritz"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"96",
"99",
"ORG",
"Wheels and Waves"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"102",
"104",
"PRODUCT",
"Electra Glide"
]
}
],
[
{
"head": [
"117",
"118",
"PERSON",
"Antonio"
],
"tail": [
"120",
"122",
"DATE",
"next Friday"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"2",
"3",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"4",
"6",
"PERSON",
"Antonio Merinero"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"22",
"23",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"35",
"36",
"LOC",
"Asia"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"45",
"46",
"GPE",
"Bollywood"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"55",
"56",
"GPE",
"India"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"57",
"58",
"GPE",
"Thailand"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"83",
"84",
"PERSON",
"Antonio"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"89",
"90",
"GPE",
"Madrid"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"94",
"95",
"GPE",
"Biarritz"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"96",
"99",
"ORG",
"Wheels and Waves"
]
}
],
[
{
"head": [
"120",
"122",
"DATE",
"next Friday"
],
"tail": [
"117",
"118",
"PERSON",
"Antonio"
]
}
]
] | [
" ORIGIN_FROM",
" ORIGIN_FROM",
" INSPIRATION_FROM",
" WORKED_WITH",
" INSPIRATION_FROM",
" INSPIRATION_FROM",
" ORIGIN_FROM",
" ORIGIN_FROM",
" TRAVELS_FROM",
" JOURNEY_FROM",
" RIDES\n\n Explanation:\n The text states that Antonio is riding",
" ORIGIN_FROM",
" HAS_EXHIBITION",
" ORIGIN_FROM",
" SAME_PERSON",
" INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" INSPIRATION_FROM",
" SAME_PERSON",
" ORIGIN_FROM",
" JOURNEY_TO",
" JOINS",
" RIDES\n\n Explanation:\n The text states that \"Antonio",
" SAME_PERSON",
" HAS_EXHIBITION",
" ORIGIN_FROM",
" IDENTICAL\n\n Explanation:\n The entities refer to the same person",
" INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" INSPIRATION_FROM",
" SAME_PERSON",
" ORIGIN_FROM",
" JOURNEY_TO",
" JOINS",
" RIDES\n\n Explanation:\n The text states that \"Antonio",
" SAME_PERSON",
" EXHIBITION\n\n Entities: \n [{'head': ['1",
" FROM_LOCATION",
" INSPIRATION_FROM",
" INSPIRATION_FROM",
" WORKED_WITH",
" INSPIRATION_FROM",
" IN_LOCATION",
" INSPIRATION_FROM",
" FROM_LOCATION",
" TRAVELS_TO",
" TRAVELS_TO",
" TRAVELS_WITH",
" INSPIRATION_FROM",
" INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" TRAVELS_TO",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" FROM_LOCATION\n\n Explanation:\n The text states that Antonio travels",
" WORKED_WITH",
" WORKED_WITH",
" IN_LOCATION",
" WORKED_WITH",
" TRAVELLED_TO",
" WORKED_WITH",
" FROM_LOCATION\n\n Explanation:\n The text states that Antonio travels",
" TRAVELS_FROM",
" IN_EVENT",
" TRAVELLED_WITH",
" WORKED_WITH",
" INSPIRATION_FROM",
" FROM_LOCATION\n\n Explanation:\n The text states that Antonio travels",
" WORKED_WITH",
" WORKED_WITH",
" IN_LOCATION",
" WORKED_WITH",
" TRAVELLED_TO",
" WORKED_WITH",
" FROM_LOCATION\n\n Explanation:\n The text states that Antonio travels",
" TRAVELS_FROM",
" TRAVELLED_TO",
" TRAVELLED_WITH\n\n Explanation:\n The text states that",
" WORKED_WITH",
" INSPIRATION_FROM",
" ORIGIN_FROM",
" SAME_AS",
" SAME_PERSON",
" INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" WORKED_WITH",
" ORIGIN_FROM",
" JOURNEY_TO",
" JOINS",
" RIDES\n\n Explanation:\n The text states that Antonio is riding",
" SAME_PERSON",
" EXHIBITION\n\n Entities: \n [{'head': ['8",
" ORIGIN\n\n Entities: \n [{'head': ['2',",
" ORIGIN_FROM",
" ORIGIN_FROM",
" INSPIRATION_FROM",
" WORKED_WITH",
" INSPIRATION_FROM",
" INSPIRATION_FROM",
" ORIGIN_FROM",
" TRAVELS_FROM",
" ORGANIZER",
" ORIGIN_FROM",
" ORIGIN_FROM",
" EXHIBITION\n The head entity is Madrid and the tail entity is next Friday.",
" JOURNEY_FROM",
" JOINS",
" JOINS",
" TRAVELS_TO",
" WORKED_WITH",
" Antonio_has_been_to_India.",
" INSPIRATION_FROM",
" JOINS",
" JOURNEY_FROM",
" JOINED_BY",
" JOURNEY_FROM",
" JOINS",
" JOINED_BY",
" FROM_LOCATION",
" JOINS",
" JOINS",
" INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" ART_INFLUENCE\n\n Explanation:\n Antonio has been",
" JOINS",
" FROM_LOCATION",
" JOINED_BY\n\n Explanation:\n Antonio is joining Wheels",
" JOINS\n\n Explanation:\n The text states that Antonio is riding his",
" JOINS",
" EXHIBITION\n\n Entities: \n [{'head': ['1",
" RIDES_FROM",
" OWNER",
" OWNS",
" TRAVELS_TO",
" WORKED_WITH",
" TRAVELLED_TO",
" TRAVELLED_TO",
" OWNER_OF",
" RIDES_FROM",
" JOURNEY_FROM",
" JOURNEYS_TO",
" OWNER",
" ORIGIN_FROM",
" IDENTICAL\n\n Explanation:\n The entities refer to the same person",
" SAME_PERSON",
" INSPIRATION_FROM",
" WORKED_WITH",
" INSPIRATION_FROM",
" INSPIRATION_FROM",
" SAME_PERSON",
" ORIGIN_FROM",
" JOURNEY_TO",
" JOINS",
" OWNS\n\n Explanation:\n Antonio owns an old Electra Gl",
" EXHIBITION\n\n Entities: \n [{'head': ['1",
" TRAVELS_FROM",
" HAS_EXHIBITION",
" HAS_EXHIBITION",
" MUCH_OF_INSPIRATION_FROM",
" WORKED_WITH",
" WORKED_WITH",
" INSPIRATION_FROM",
" HAS_EXHIBITION",
" TRAVELS_FROM",
" TRAVELS_TO",
" EXHIBITION\n This is the correct answer. The relation is 'EXHIB",
" HAS_EXHIBITION"
] | [
[
"2",
"3",
"GPE",
"Madrid"
],
[
"4",
"6",
"PERSON",
"Antonio Merinero"
],
[
"22",
"23",
"PERSON",
"Antonio"
],
[
"35",
"36",
"LOC",
"Asia"
],
[
"45",
"46",
"GPE",
"Bollywood"
],
[
"55",
"56",
"GPE",
"India"
],
[
"57",
"58",
"GPE",
"Thailand"
],
[
"83",
"84",
"PERSON",
"Antonio"
],
[
"89",
"90",
"GPE",
"Madrid"
],
[
"94",
"95",
"GPE",
"Biarritz"
],
[
"96",
"99",
"ORG",
"Wheels and Waves"
],
[
"102",
"104",
"PRODUCT",
"Electra Glide"
],
[
"117",
"118",
"PERSON",
"Antonio"
],
[
"120",
"122",
"DATE",
"next Friday"
]
] | 671 |
673 | [
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" CAUSED_BY",
" CAUSED_BY",
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" LOCATION_AFFECTED_BY_PERSON",
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" WORKS_FOR",
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" HAS_PROCESSED_X_FLIGHTS",
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" SELF_RELATION\n\n Explanation:\n The text describes the",
" NO_RELATION",
" The customer has taken 'hundreds' of flights FROM Chicago.",
" TAKEN_FROM\n\n Explanation:\n The text states that the",
" WRITTEN_COMPLIMENT_BY\n (Note: The entities are",
" WRITTEN_COMPLIMENT_BY",
" WRITTEN_COMPLIMENT_BY",
" WRITTEN_COMPLIMENT_BY",
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] | 674 |
676 | [
"Rob is a talented batsman from Lancashire. He was a member of the 2014 England Under 19s World Cup team. Rob made his First Class debut in 2016 and, in his 3rd game ,he made his maiden first class century. He has since gone on to play all 3 formats for Lancashire.\nRob spends much of his time enjoying the great outdoors be that by the coast, in the mountains or a forest.\nHis main love is walking the UK Peaks where he can completely immerse himself in nature. Rob does this solo and also with walking and climbing groups adding a social element to his adventures. Come rain or shine, he’s out there exploring whenever he gets the chance and loves sharing it with the people around him."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Rob is a talented batsman from Lancashire. He was a member of the 2014 England Under 19s World Cup team. Rob made his First Class debut in 2016 and, in his 3rd game ,he made his maiden first class century. He has since gone on to play all 3 formats for Lancashire.\nRob spends much of his time enjoying the great outdoors be that by the coast, in the mountains or a forest.\nHis main love is walking the UK Peaks where he can completely immerse himself in nature. Rob does this solo and also with walking and climbing groups adding a social element to his adventures. Come rain or shine, he’s out there exploring whenever he gets the chance and loves sharing it with the people around him.']
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Relation:
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{
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}
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{
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{
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[
{
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{
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}
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{
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}
],
[
{
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{
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{
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],
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}
],
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{
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],
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}
],
[
{
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"101",
"PERSON",
"Rob"
],
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"first"
]
}
],
[
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],
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}
],
[
{
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"101",
"PERSON",
"Rob"
],
"tail": [
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"GPE",
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]
}
],
[
{
"head": [
"100",
"101",
"PERSON",
"Rob"
],
"tail": [
"59",
"60",
"PERSON",
"Rob"
]
}
],
[
{
"head": [
"100",
"101",
"PERSON",
"Rob"
],
"tail": [
"88",
"91",
"LOC",
"the UK Peaks"
]
}
]
] | [
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" SAME_PERSON",
" DEBUTED_IN",
" MADE_DEBUT",
" MAIDEN_CENTURY_GAME",
" MAIDEN_OF_EVENT",
" MADE_FIRST_CLASS_DEBUT_IN",
" MEMBER_OF",
" SAME_PERSON",
" ENJOYS_LOCATION",
" SELF_REFERENCE",
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" MEMBER_OF",
" MEMBER_OF",
" BELONGS_TO",
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" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" DEBUTED_IN",
" MEMBER_OF",
" MEMBER_OF",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
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" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" DEBUTED_IN",
" MEMBER_OF",
" MEMBER_OF",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
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" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
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" MADE_MAIDEN_CENTURY_IN_GAME_NUMBER",
" MEMBER_OF",
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" ENJOYS_LOCATION",
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" MADE_DEBUT",
" PLAYS_FOR",
" MADE_DEBUT",
" DEBUTED_FOR",
" MEMBER_OF",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_FIRST_APPEARANCE_IN",
" MADE_DEBUT",
" PLAYS_FOR",
" MADE_DEBUT",
" ENJOYS_LOCATION",
" DEBUTED_FOR",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" MADE_DEBUT",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" MAIDEN_CENTURY",
" MAIDEN_CENTURY",
" DEBUTED_IN",
" MEMBER_OF",
" MAIDEN_CENTURY",
" MADE_DEBUT",
" DEBUTS_IN",
" MAIDEN_CENTURY",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" MAIDEN_CENTURY",
" MAIDEN_OF\n\n Explanation:\n The text states that \"",
" PLAYS_FOR",
" MEMBER_OF",
" MADE_FIRST_CLASS_DEBUT",
" DEBUTED_IN",
" PLAYS_FOR",
" MAIDEN_OF\n\n Explanation:\n The text states that \"",
" ENJOYS\n\n Explanation:\n The text states that \"His",
" MAIDEN_OF\n\n Explanation:\n The text states that \"",
" PLAYED_FOR",
" MEMBER_OF",
" MEMBER_OF",
" SPOUSE_OF\n\n Explanation:\n I'm sorry,",
" DEBUTED_IN",
" BELONGS_TO",
" SPOUSE_OR_CHILD\n\n (This is incorrect, the text does",
" ENJOYS_LOCATION",
" MAIDEN_OF_CENTURY",
" BELONGS_TO",
" LOCATION_IN_LOCATION",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" PLAYS_IN",
" DEBUTED_IN",
" DEBUTED_IN",
" PLAYS_FOR",
" PLAYED_FOR",
" MEMBER_OF",
" ENJOYS_LOCATION",
" MEMBER_OF",
" SELF_REFERENCE",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" SAME_PERSON",
" DEBUTED_IN",
" MADE_DEBUT",
" MAIDEN_CENTURY_GAME",
" MAIDEN_FIRST_CLASS_CENTURY",
" MADE_MAIDEN_CENTURY_IN_GAME_NUMBER",
" MEMBER_OF",
" ENJOYS_LOCATION",
" SELF_REFERENCE",
" LOVES\n\n Explanation:\n The text states that \"Rob does",
" LOCATION_IN_LOCATION",
" LOCATION_OF\n or\n NO_RELATION",
" LOCATION_IN_REGION",
" NO_RELATION.",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" NO_RELATION",
" ENJOYS_ACTIVITY_AT_LOCATION",
" LOVES_TO_DO\n\n Explanation:\n The text states",
" LOVES_PLACE_WITH_QUANTITY",
" LOCATION_IN_LOCATION",
" LOVES\n\n Explanation:\n The text states that \"Rob does",
" ENJOYS\n\n Explanation:\n The text states that \"Rob",
" SAME_PERSON",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" MEMBER_OF",
" SAME_PERSON",
" DEBUTED_FOR",
" MADE_DEBUT",
" MAIDEN_CENTURY",
" MAIDEN_CENTURY",
" MADE_MAIDEN_CENTURY_IN_GAME_NUMBER",
" MEMBER_OF",
" SAME_PERSON",
" ENJOYS_LOCATION"
] | [
[
"0",
"1",
"PERSON",
"Rob"
],
[
"6",
"7",
"GPE",
"Lancashire"
],
[
"14",
"15",
"DATE",
"2014"
],
[
"15",
"16",
"GPE",
"England"
],
[
"18",
"20",
"EVENT",
"World Cup"
],
[
"22",
"23",
"PERSON",
"Rob"
],
[
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"27",
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"First Class"
],
[
"29",
"30",
"DATE",
"2016"
],
[
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"35",
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],
[
"41",
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[
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] | 677 |
679 | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Google is the most popular and most visited Search Engine in the World. Every day over 5,000,000,000 visitors visit Google for their search queries. buy do you know when and who founded Google?\nGoogle was founded by Larry Page and Sergey Brin while students at Stanford University. It was first incorporated as a privately held company on September 4, 1998. The initial public offering was on August 19, 2004. It raised $1.67 billion, implying a total value of $23 billion. Google’s rapid growth has sparked a sequence of new products, acquisitions and partnerships beyond its core search engine. Environmentalism, philanthropy and positive employee relations were from the start assigned an important role in establishing brand image. Google has been repeatedly named Fortune Magazine’s Number One Best Place to Work and most powerful brand in the world. According to Alexa website ranking service, Google is the most visited website in the World.']
Entities:
[{'head': ['0', '1', 'ORG', 'Google'], 'tail': ['14', '16', 'DATE', 'Every day']}]
Relation:
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{
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}
],
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{
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}
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}
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}
],
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{
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}
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}
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}
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],
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}
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" FOUNDED_BY",
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" FOUNDED_BY",
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" FOUNDED_BY",
" FOUNDER",
" FOUNDED_AT.\n\n Explanation:\n The text states that",
" FOUNDED_ON",
" FOUNDED",
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" FOUNDER_OF",
" FOUNDER",
" FOUNDER",
" HAS_BEEN_NAMED",
" FOUNDER_OF",
" MOST_VISITED_BY",
" FOUNDED_BY",
" FOUNDER_OF",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" STARTED_AT",
" STUDENT_AT\n OR\n FOUNDED_BY\n\n Ex",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" FOUNDED_BY",
" FOUNDER",
" FOUNDED_ON",
" FOUNDING_DATE",
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" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" REPEATEDLY_NAMED",
" FOUNDED_AT",
" MOST_VISITED_BY",
" FOUNDED_AT\n\n Explanation:\n The text states that \"",
" EDUCATION_PLACE_OF\n\n Explanation:\n The",
" INcorporated_ON.",
" INcorporated_ON.",
" INcorporated_ON.",
" INcorporated_ON.",
" FOUNDED_BY",
" FOUNDED_BY",
" FOUNDED_AT",
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" FOUNDATION.DATE_OF_FOUNDING.LOCATION",
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" IPO\n\n Explanation:\n The text mentions that 'Google was",
" IPO\n\n Explanation:\n The text mentions that 'Google was",
" IPO\n\n Explanation:\n The text states that \"Google's",
" IPO_BY\n\n [{'head': ['73', '77',",
" IPO_BY.",
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" IPO\n\n Explanation:\n The text mentions that \"Google’",
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" VALUE_OF",
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" MOST_VISITED_WEBSITE",
" SAME_ORGANIZATION",
" MOST_VISITED_WEBSITE_IN_THE_WORLD",
" NUMBER_ONE_BEST_PLACE_TO_WORK",
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" NUMBER_OF_VISITORS",
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" REPEATEDLY_NAMED_NUMBER_ONE_BEST_PLACE_TO",
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" FOUNDING_DATE",
" NUMBER_ONE_BEST_PLACE_WORKED_ON\n\n ",
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" MOST_VISITED_WEBSITE_OF.",
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" MOST_VISITED_WEBSITE",
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] | 678 |
680 | [
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['by Erika Fatland\nAn unforgettable journey through Central Asia, one of the most mysterious and history-laden regions of the world.\nTurkmenistan, Kazakhstan, Tajikistan, Kyrgyzstan, and Uzbekistan became free of the Soviet Union in 1991. But though they are new to modern statehood, this is a region rich in ancient history, culture, and landscapes unlike anywhere else in the world.\nTraveling alone, Erika Fatland is a true adventurer in every sense. In Sovietistan, she takes the reader on a compassionate and insightful journey to explore how their Soviet heritage has influenced these countries, with governments experimenting with both democracy and dictatorships.']
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Relation:
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" NEIGHBOR.",
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" 'was_part_of'",
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" AUTHOR_OF\n ORIGINATED_FROM\n OR: NO_REL",
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" SOVIET_OF\n\n Explanation:\n The text mentions that",
" INFLUENCED_BY",
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[
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[
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"90",
"GPE",
"Sovietistan"
],
[
"105",
"106",
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681 | [
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["Cute Little Lenormand Fortune Telling Deck & Book - Signed!\nCute Little Lenormand is a modern take on a traditional divination method - and it's signed by the author and illustrator Sara M. Lyons!\nCute Little Lenormand includes a comprehensive guidebook along with a complete 36 card Lenormand deck, so you can start working with the cards right away.\nIt's written with the newbie in mind, so you’ll be interpreting with ease.\nThe book includes explanations for each of the cards and walks you through how to read them, from your first three-card vignette all the way up to a 36-card grand tableau."]
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[{'head': ['34', '37', 'PERSON', 'Sara M. Lyons'], 'tail': ['39', '42', 'ORG', 'Cute Little Lenormand']}]
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[
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]
] | 680 |
682 | [
"NEW DESIGN! “Swish Fish.” Artist. Kimberly Sumerel.\nYou don’t have to live in Florida to enjoy the color and beauty of ocean life! Take this fun fashion zippered clutch wherever you go! It comes in 3 different sizes. You can tuck the smaller bag in a purse or tote or carry it alone as a handbag. You will be amazed at the compliments you will get when you show off your NEW fashion clutch bag!\nAvailable as an 8 x 10 print and greeting card."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['NEW DESIGN! “Swish Fish.” Artist. Kimberly Sumerel.\nYou don’t have to live in Florida to enjoy the color and beauty of ocean life! Take this fun fashion zippered clutch wherever you go! It comes in 3 different sizes. You can tuck the smaller bag in a purse or tote or carry it alone as a handbag. You will be amazed at the compliments you will get when you show off your NEW fashion clutch bag!\nAvailable as an 8 x 10 print and greeting card.']
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[{'head': ['10', '12', 'PERSON', 'Kimberly Sumerel'], 'tail': ['21', '22', 'GPE', 'Florida']}]
Relation:
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" SIZE_OF\n\n Explanation:\n The text mentions that the",
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] | 681 |
683 | [
"NEW HAVEN, Conn. (WTNH) – The New Haven Chalk Art Festival is kicking off at CT Style. Artist Michael Micinilio demonstrates fun chalk art you can expect to see at the free event happening on Sunday from 10am-6pm at the Shops at Yale in New Haven.\nThe event is open to all age groups. Each participant will be given a 3′ x 3′ square space for their artwork. The surface is asphalt. Knee pads and/or towels are recommended."
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Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
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" DOUBLED_HEADLINE_TOUR",
" ALBUM_RELEASE_DATE",
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" TOUR\n\n Explanation:\n The text mentions a 'monument"
] | [
[
"0",
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[
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[
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[
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[
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[
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[
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[
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[
"69",
"70",
"LOC",
"Europe"
],
[
"87",
"89",
"PERSON",
"Beast In"
]
] | 684 |
686 | [
"Pro Fencers Hand Tools – James from Walters Fencing Tamworth\nFarm Learning with Tim Thompson | 7 May 2022 | Back to All Videos\nCheck out my website for even more content https://timthompson.ag/\nSubscribe for a new video each week! New content uploaded every weekend.\nMy Channel https://www.youtube.com/channel/UCdtlC5DtsgZKCM8gislyDJw"
] | [
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]
] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Pro Fencers Hand Tools – James from Walters Fencing Tamworth\nFarm Learning with Tim Thompson | 7 May 2022 | Back to All Videos\nCheck out my website for even more content https://timthompson.ag/\nSubscribe for a new video each week! New content uploaded every weekend.\nMy Channel https://www.youtube.com/channel/UCdtlC5DtsgZKCM8gislyDJw']
Entities:
[{'head': ['5', '6', 'PERSON', 'James'], 'tail': ['7', '10', 'ORG', 'Walters Fencing Tamworth']}]
Relation:
| [
[
{
"head": [
"5",
"6",
"PERSON",
"James"
],
"tail": [
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"ORG",
"Walters Fencing Tamworth"
]
}
],
[
{
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],
"tail": [
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"Tim Thompson"
]
}
],
[
{
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"PERSON",
"James"
],
"tail": [
"17",
"20",
"DATE",
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]
}
],
[
{
"head": [
"5",
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"PERSON",
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],
"tail": [
"41",
"43",
"DATE",
"each week"
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}
],
[
{
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}
],
[
{
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],
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}
],
[
{
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{
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}
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[
{
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}
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[
{
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[
{
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}
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[
{
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}
],
[
{
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}
],
[
{
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}
],
[
{
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}
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[
{
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[
{
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}
],
[
{
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}
],
[
{
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"16",
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}
],
[
{
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}
],
[
{
"head": [
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"every weekend"
],
"tail": [
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}
],
[
{
"head": [
"47",
"49",
"DATE",
"every weekend"
],
"tail": [
"14",
"16",
"PERSON",
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]
}
]
] | [
" WORKS_FOR",
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" WEEKLY_EVENT",
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" EMPLOYED_BY",
" OWNER_OF",
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" WORKS_ON\n\n Explanation:\n The text mentions that",
" WEEKLY_EVENTS_WITH",
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[
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],
[
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],
[
"41",
"43",
"DATE",
"each week"
],
[
"47",
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"DATE",
"every weekend"
]
] | 685 |
687 | [
"APx Acquisition Corp. I is a company formed for the purpose of effecting a merger, amalgamation, share exchange, asset acquisition, share purchase, reorganization or similar business combination with one or more businesses. The Company intends to seek a business combination with a technology-enabled Latin American company.\nAPx Acquisition Corp. I closed a $172.5 Million Initial Public Offering, Including Full Exercise by Underwriter to Purchase Additional Shares on December 9th 2021. The Class A ordinary shares and warrants are listed on the Nasdaq under the symbols “APXI” and “APXIW,” respectively.\nAPx’s key individuals include Daniel Braatz (Chief Executive Officer and Chairman) and Xavier Martinez (Chief Financial Officer)."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['APx Acquisition Corp. I is a company formed for the purpose of effecting a merger, amalgamation, share exchange, asset acquisition, share purchase, reorganization or similar business combination with one or more businesses. The Company intends to seek a business combination with a technology-enabled Latin American company.\nAPx Acquisition Corp. I closed a $172.5 Million Initial Public Offering, Including Full Exercise by Underwriter to Purchase Additional Shares on December 9th 2021. The Class A ordinary shares and warrants are listed on the Nasdaq under the symbols “APXI” and “APXIW,” respectively.\nAPx’s key individuals include Daniel Braatz (Chief Executive Officer and Chairman) and Xavier Martinez (Chief Financial Officer).']
Entities:
[{'head': ['0', '4', 'ORG', 'APx Acquisition Corp. I'], 'tail': ['33', '34', 'CARDINAL', 'one']}]
Relation:
| [
[
{
"head": [
"0",
"4",
"ORG",
"APx Acquisition Corp. I"
],
"tail": [
"33",
"34",
"CARDINAL",
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]
}
],
[
{
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],
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]
}
],
[
{
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],
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]
}
],
[
{
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]
}
],
[
{
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],
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]
}
],
[
{
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}
],
[
{
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],
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]
}
],
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{
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}
],
[
{
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}
],
[
{
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{
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{
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{
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[
{
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[
{
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}
],
[
{
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}
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{
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}
],
[
{
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}
],
[
{
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{
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}
],
[
{
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}
],
[
{
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[
{
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[
{
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[
{
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}
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[
{
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{
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}
],
[
{
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]
}
],
[
{
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}
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{
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[
{
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[
{
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{
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689 | [
"Why wonder or worry about the future?\nWith all thats transpiring in the world, people cant help but wonder what the future holds. Will there ever be peace on earth? How long will the world live under the threat of terrorism? Is a one-world ruler on the horizon?\nGod has already provided answers to these questions in the book of Daniel, which sets forth His blueprints for the future. In fact, when you understand the prophecies Daniel reveals, every other prophecy in the Bible will fit somewhere in the plan. If you want to understand the future, if you want to know what will happen [ … ]"
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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] | 693 |
695 | [
"Parish Life & Community Events\nAll Saints has a wide array of events - something for everyone!\nParish Life Events\nAll Saints is committed to providing opportunities for fellowship throughout the year to those who wish to participate. When the building is open again and we are once again together; we will get back to hosting events to help bring us all closer.\nAll Saints is a strong believer in supporting our local community. We know that sometimes local groups need help in getting the word out about upcoming events. If you have an event you would like for us to include on our community calendar of events please click here to email our Director of Communications, Jessica McIlwee, with the details of the event."
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ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
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}
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[
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}
],
[
{
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"tail": [
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}
]
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" PROVENANCE_FROM",
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" PRODUCES_FROM",
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" CLIENT_OF",
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" CLIENT_OF\n # This model is a relation extractor, not a text",
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[
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[
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[
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[
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"PERSON",
"Amber"
],
[
"103",
"105",
"ORG",
"Bouchard Cooperages"
]
] | 696 |
698 | [
"What are people saying about us..\nAaron - Amazon Review 01/2020\nIts the best, clean label protein bar I've found. The new packaging is much easier to open (THANK YOU) and the bar is my go to protein/breakfast! AWESOME BAR!\nAmazon Review 07/2019\nThe Bia bar is delicious! My favorite is the peanut butter fudge but they are all tasty! This bar is high in protein, flavorful, and gluten free! Very filling and satisfying!"
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
["What are people saying about us..\nAaron - Amazon Review 01/2020\nIts the best, clean label protein bar I've found. The new packaging is much easier to open (THANK YOU) and the bar is my go to protein/breakfast! AWESOME BAR!\nAmazon Review 07/2019\nThe Bia bar is delicious! My favorite is the peanut butter fudge but they are all tasty! This bar is high in protein, flavorful, and gluten free! Very filling and satisfying!"]
Entities:
[{'head': ['8', '9', 'PERSON', 'Aaron'], 'tail': ['12', '13', 'DATE', '01/2020']}]
Relation:
| [
[
{
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"PERSON",
"Aaron"
],
"tail": [
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}
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[
{
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}
],
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{
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}
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}
],
[
{
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"59",
"PRODUCT",
"Bia"
],
"tail": [
"8",
"9",
"PERSON",
"Aaron"
]
}
]
] | [
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" WROTE_REVIEW",
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" WRITTEN_REVIEW",
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[
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],
[
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],
[
"55",
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"DATE",
"07/2019"
],
[
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"Bia"
]
] | 697 |
699 | [
"Login to BlackFacts.com using your favorite Social Media Login. Click the appropriate button below and you will be redirected to your Social Media Website for confirmation and then back to Blackfacts.com once successful.\nEnter the email address and password you used to join BlackFacts.com. If you cannot remember your login information, click the “Forgot Password” link to reset your password.\nABOVE: Congresswoman Sheila Jackson Lee (left) and State Sen. John Whitmire (right) are vying to…\nThe post Early Voting Begins In Runoff appeared first on Forward Times."
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] | mistralai/Mistral-7B-Instruct-v0.2 | You are a fantastic relation extraction model who only outputs valid JSON.
Extract the relation between the given entities using the context in the below text. If no relation exists, use the label NO_RELATION.
ONLY RETURN THE RELATION LABEL. Do not add additional text.
Pay VERY close attention to which entity is the head and tail; this dictates the direction of the relationship.
Text:
['Login to BlackFacts.com using your favorite Social Media Login. Click the appropriate button below and you will be redirected to your Social Media Website for confirmation and then back to Blackfacts.com once successful.\nEnter the email address and password you used to join BlackFacts.com. If you cannot remember your login information, click the “Forgot Password” link to reset your password.\nABOVE: Congresswoman Sheila Jackson Lee (left) and State Sen. John Whitmire (right) are vying to…\nThe post Early Voting Begins In Runoff appeared first on Forward Times.']
Entities:
[{'head': ['2', '3', 'ORG', 'BlackFacts.com'], 'tail': ['31', '32', 'ORG', 'Blackfacts.com']}]
Relation:
| [
[
{
"head": [
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"BlackFacts.com"
],
"tail": [
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}
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}
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[
{
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[
{
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],
[
{
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[
{
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[
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],
[
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}
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[
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[
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}
],
[
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[
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[
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[
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[
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[
{
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[
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