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Skai TV
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Washington Place (West Virginia)
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IBM Research – Brazil
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Lookin Ass
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Conrad O. Johnson
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Samsung Galaxy S series
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Ned McEvoy
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Portland Golf Club
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Urgut
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Robert K. Huntington
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More (The Sisters of Mercy song)
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Delaware General Assembly
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Allen County, Ohio
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Palestinian National Theatre
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Taiwanese expatriates in Vietnam
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Allen F. Moore
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Johan Gottlieb Gahn
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Siberia Governorate
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Quokka
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Dollar General
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Memogate (Pakistan)
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Live in New York (Laurie Anderson album)
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Norvelt, Pennsylvania
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Beibu Gulf Economic Rim
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Hooshang Seyhoun
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Albemarle County, Virginia
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Kurt Tucholsky
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The Yorkshire Post
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Addy Lee
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Wilhelm Lanzky-Otto
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Jeanne Thérèse du Han
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(I Am) The Seeker
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Queen of Housewives
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Old Loggers Path
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Grand Wing Servo-Tech
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Paul Morphy
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Low Pass, Oregon
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Outline of South Sudan
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Pointr
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Villanova Preparatory School
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America's Sweetheart (album)
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Brooks Pharmacy
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Crouching Tiger, Hidden Dragon: Sword of Destiny
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Bicycles & Tricycles
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Each Time You Break My Heart
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UNESCO Confucius Prize for Literacy
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Chachalaca
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{ "head": [ 2, 3, 3, 0 ], "tail": [ 3, 2, 2, 1 ], "relation_id": [ "P150", "P131", "P17", "P171" ], "relation_text": [ "contains administrative territorial entity", "located in the administrative territorial entity", "country", "parent taxon" ], "evidence": [ [ 1 ], [ 1 ], [ 1 ], [ 0 ] ] }
CBBC
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James De Alwis
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Gershonites
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{ "head": [ 6, 6, 25, 5, 5 ], "tail": [ 4, 5, 4, 4, 6 ], "relation_id": [ "P1441", "P40", "P1441", "P1441", "P22" ], "relation_text": [ "present in work", "child", "present in work", "present in work", "father" ], "evidence": [ [ 1 ], [ 1 ], [ 8, 4 ], [ 1 ], [ 1 ] ] }
Antony Noghès
[ [ "Antony", "Noghès", "(", "13", "September", "1890", "in", "Monaco", "–", "2", "August", "1978", "in", "Monte", "Carlo", ",", "Monaco", ")", "was", "the", "founder", "of", "the", "Monaco", "Grand", "Prix", "." ], [ "He", "also", "helped", "create", "the", "Rallye", "Monte", "-", "Carlo", "in", "1911", "." ], [ "He", "suggested", "the", "international", "adoption", "of", "the", "checkered", "flag", "to", "end", "races", "." ], [ "Since", "1979", ",", "the", "last", "turn", "of", "the", "Monaco", "circuit", "(", "the", "former", "\"", "Gazometer", "turn", "\"", ")", "just", "before", "the", "finish", "line", ",", "has", "been", "named", "\"", "Virage", "Antony", "Noghès", "\"", "after", "him", "." ], [ "As", "\"", "Agent", "general", "de", "la", "Regie", "des", "tabacs", "\"", "he", "was", "the", "Director", "of", "the", "Public", "administration", "responsible", "for", "the", "management", "of", "the", "monopoly", "of", "procurement", ",", "manufacturing", ",", "and", "selling", "of", "tobacco", "in", "the", "Principality", "." ], [ "He", "was", "the", "father", "of", "Alexandre", "-", "Athenase", "Noghès", ",", "himself", "father", "of", "Lionel", "Noghès", ",", "Elisabeth", "-", "Anne", ",", "Christian", "Louis", ",", "and", "Christine", "Alix", "de", "Massy", "and", "the", "father", "of", "Bathilde", "Livieratos", ",", "mother", "of", "Marie", "Livieratos", ",", "Hélène", "Tchomlekdjoglou", "and", "Athanase", "(", "Tasso", ")", "Livieratos", "." ], [ "His", "other", "son", ",", "Gilles", ",", "was", "Monaco", "'s", "first", "ambassador", "to", "the", "United", "States", ",", "father", "of", "journalist", "Yann", "-", "Antony", "Noghès", "." ] ]
[ [ { "name": "Antony Noghès", "pos": [ 0, 2 ], "sent_id": 0, "type": "PER" } ], [ { "pos": [ 3, 6 ], "type": "TIME", "sent_id": 0, "name": "13 September 1890" } ], [ { "name": "Monaco", "pos": [ 7, 8 ], "sent_id": 0, "type": "LOC" }, { "name": "Monaco", "pos": [ 16, 17 ], "sent_id": 0, "type": "LOC" }, { "name": "Monaco", "pos": [ 7, 8 ], "sent_id": 6, "type": "LOC" } ], [ { "pos": [ 9, 12 ], "type": "TIME", "sent_id": 0, "name": "2 August 1978" } ], [ { "name": "Monte Carlo", "pos": [ 13, 15 ], "sent_id": 0, "type": "LOC" } ], [ { "sent_id": 0, "type": "MISC", "pos": [ 23, 26 ], "name": "Monaco Grand Prix" } ], [ { "sent_id": 1, "type": "MISC", "pos": [ 5, 9 ], "name": "Rallye Monte - Carlo" } ], [ { "pos": [ 10, 11 ], "type": "TIME", "sent_id": 1, "name": "1911" } ], [ { "pos": [ 1, 2 ], "type": "TIME", "sent_id": 3, "name": "1979" } ], [ { "sent_id": 3, "type": "LOC", "pos": [ 8, 10 ], "name": "Monaco circuit" }, { "sent_id": 3, "type": "LOC", "pos": [ 14, 16 ], "name": "Gazometer turn" }, { "sent_id": 3, "type": "LOC", "pos": [ 28, 31 ], "name": "Virage Antony Noghès" } ], [ { "pos": [ 5, 9 ], "type": "PER", "sent_id": 5, "name": "Alexandre - Athenase Noghès" } ], [ { "pos": [ 13, 15 ], "type": "PER", "sent_id": 5, "name": "Lionel Noghès" } ], [ { "name": "Elisabeth-Anne", "pos": [ 16, 19 ], "sent_id": 5, "type": "PER" } ], [ { "name": "Christian Louis", "pos": [ 20, 22 ], "sent_id": 5, "type": "PER" } ], [ { "pos": [ 24, 28 ], "type": "PER", "sent_id": 5, "name": "Christine Alix de Massy" } ], [ { "pos": [ 32, 34 ], "type": "PER", "sent_id": 5, "name": "Bathilde Livieratos" } ], [ { "pos": [ 37, 39 ], "type": "PER", "sent_id": 5, "name": "Marie Livieratos" } ], [ { "pos": [ 40, 42 ], "type": "PER", "sent_id": 5, "name": "Hélène Tchomlekdjoglou" } ], [ { "pos": [ 43, 48 ], "type": "PER", "name": "Athanase ( Tasso ) Livieratos", "sent_id": 5 } ], [ { "pos": [ 4, 5 ], "type": "PER", "sent_id": 6, "name": "Gilles" } ], [ { "name": "the United States", "pos": [ 12, 15 ], "sent_id": 6, "type": "LOC" } ], [ { "pos": [ 19, 23 ], "type": "PER", "sent_id": 6, "name": "Yann-Antony Noghès" } ] ]
{ "head": [ 0, 0, 0, 4, 6, 6, 12, 12, 13, 13, 9, 14, 14 ], "tail": [ 4, 1, 3, 2, 2, 7, 13, 14, 12, 14, 2, 12, 13 ], "relation_id": [ "P20", "P569", "P570", "P17", "P17", "P571", "P3373", "P3373", "P3373", "P3373", "P17", "P3373", "P3373" ], "relation_text": [ "place of death", "date of birth", "date of death", "country", "country", "inception", "sibling", "sibling", "sibling", "sibling", "country", "sibling", "sibling" ], "evidence": [ [ 0 ], [ 0 ], [ 0 ], [ 0 ], [ 0, 1 ], [ 1 ], [ 5 ], [ 5 ], [ 5 ], [ 5 ], [ 0, 3 ], [ 5 ], [ 5 ] ] }
Rose Porteous
[ [ "Rose", "Porteous", "(", "née", "Lacson", "y", "Ledesma", ",", "formerly", "Teodoro", ",", "Kuan", "and", "Hancock", ",", "born", "Rosario", "Magdalena", "Teresita", "Lacson", ",", "26", "October", "1948", ")", ",", "a", "Filipino", "-", "born", "Australian", ",", "is", "best", "known", "for", "her", "marriage", "to", "Lang", "Hancock", ",", "a", "Western", "Australia", "iron", "ore", "mining", "magnate", ",", "and", "the", "protracted", "legal", "battle", "with", "her", "step", "-", "daughter", ",", "Gina", "Rinehart", ",", "over", "the", "circumstances", "that", "led", "to", "the", "death", "of", "Hancock", ",", "and", "the", "distribution", "of", "his", "estate", "." ], [ "The", "action", ",", "commenced", "by", "Rinehart", "in", "1992", ",", "was", "eventually", "settled", "in", "2003", "following", "a", "coronial", "inquiry", "that", "determined", "Hancock", "died", "of", "natural", "causes", "." ], [ "Porteous", ",", "who", "lives", "in", "Perth", "and", "Melbourne", ",", "Victoria", ",", "is", "often", "referred", "to", "by", "the", "media", "as", "a", "socialite", "." ] ]
[ [ { "pos": [ 0, 2 ], "type": "PER", "sent_id": 0, "name": "Rose Porteous" }, { "pos": [ 4, 7 ], "type": "PER", "sent_id": 0, "name": "Lacson y Ledesma" }, { "name": "Teodoro", "pos": [ 9, 10 ], "sent_id": 0, "type": "PER" }, { "name": "Kuan", "pos": [ 11, 12 ], "sent_id": 0, "type": "PER" }, { "pos": [ 0, 1 ], "type": "PER", "sent_id": 2, "name": "Porteous" } ], [ { "name": "Hancock", "pos": [ 73, 74 ], "sent_id": 0, "type": "PER" }, { "name": "Hancock", "pos": [ 13, 14 ], "sent_id": 0, "type": "PER" }, { "name": "Hancock", "pos": [ 20, 21 ], "sent_id": 1, "type": "PER" } ], [ { "sent_id": 0, "type": "PER", "pos": [ 16, 20 ], "name": "Rosario Magdalena Teresita Lacson" } ], [ { "pos": [ 21, 24 ], "type": "TIME", "sent_id": 0, "name": "26 October 1948" } ], [ { "name": "Filipino", "pos": [ 27, 28 ], "sent_id": 0, "type": "LOC" } ], [ { "name": "Australian", "pos": [ 30, 31 ], "sent_id": 0, "type": "LOC" } ], [ { "name": "Lang Hancock", "pos": [ 39, 41 ], "sent_id": 0, "type": "PER" } ], [ { "name": "Western Australia", "pos": [ 43, 45 ], "sent_id": 0, "type": "LOC" } ], [ { "name": "Gina Rinehart", "pos": [ 61, 63 ], "sent_id": 0, "type": "PER" }, { "name": "Rinehart", "pos": [ 5, 6 ], "sent_id": 1, "type": "PER" } ], [ { "pos": [ 7, 8 ], "type": "TIME", "sent_id": 1, "name": "1992" } ], [ { "pos": [ 13, 14 ], "type": "TIME", "sent_id": 1, "name": "2003" } ], [ { "name": "Perth", "pos": [ 5, 6 ], "sent_id": 2, "type": "LOC" } ], [ { "name": "Melbourne", "pos": [ 7, 8 ], "sent_id": 2, "type": "LOC" } ], [ { "name": "Victoria", "pos": [ 9, 10 ], "sent_id": 2, "type": "LOC" } ] ]
{ "head": [ 8, 13, 13, 0, 0, 6, 6, 12, 2 ], "tail": [ 6, 12, 12, 6, 3, 8, 0, 13, 3 ], "relation_id": [ "P22", "P131", "P150", "P26", "P569", "P40", "P26", "P131", "P569" ], "relation_text": [ "father", "located in the administrative territorial entity", "contains administrative territorial entity", "spouse", "date of birth", "child", "spouse", "located in the administrative territorial entity", "date of birth" ], "evidence": [ [ 0 ], [ 2 ], [ 2 ], [ 0 ], [ 0 ], [ 0 ], [ 0 ], [ 2 ], [ 0 ] ] }

Dataset Card for DocRED

Dataset Summary

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs. In order to accelerate the research on document-level RE, we introduce DocRED, a new dataset constructed from Wikipedia and Wikidata with three features: - DocRED annotates both named entities and relations, and is the largest human-annotated dataset for document-level RE from plain text. - DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing all information of the document. - Along with the human-annotated data, we also offer large-scale distantly supervised data, which enables DocRED to be adopted for both supervised and weakly supervised scenarios.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

  • Size of downloaded dataset files: 21.00 MB
  • Size of the generated dataset: 20.12 MB
  • Total amount of disk used: 41.14 MB

An example of 'train_annotated' looks as follows.

{
    "labels": {
        "evidence": [[0]],
        "head": [0],
        "relation_id": ["P1"],
        "relation_text": ["is_a"],
        "tail": [0]
    },
    "sents": [["This", "is", "a", "sentence"], ["This", "is", "another", "sentence"]],
    "title": "Title of the document",
    "vertexSet": [[{
        "name": "sentence",
        "pos": [3],
        "sent_id": 0,
        "type": "NN"
    }, {
        "name": "sentence",
        "pos": [3],
        "sent_id": 1,
        "type": "NN"
    }], [{
        "name": "This",
        "pos": [0],
        "sent_id": 0,
        "type": "NN"
    }]]
}

Data Fields

The data fields are the same among all splits.

default

  • title: a string feature.
  • sents: a dictionary feature containing:
    • feature: a string feature.
  • name: a string feature.
  • sent_id: a int32 feature.
  • pos: a list of int32 features.
  • type: a string feature.
  • labels: a dictionary feature containing:
    • head: a int32 feature.
    • tail: a int32 feature.
    • relation_id: a string feature.
    • relation_text: a string feature.
    • evidence: a list of int32 features.

Data Splits

name train_annotated train_distant validation test
default 3053 101873 998 1000

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

More Information Needed

Annotations

Annotation process

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Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

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Licensing Information

More Information Needed

Citation Information

@inproceedings{yao-etal-2019-docred,
    title = "{D}oc{RED}: A Large-Scale Document-Level Relation Extraction Dataset",
    author = "Yao, Yuan  and
      Ye, Deming  and
      Li, Peng  and
      Han, Xu  and
      Lin, Yankai  and
      Liu, Zhenghao  and
      Liu, Zhiyuan  and
      Huang, Lixin  and
      Zhou, Jie  and
      Sun, Maosong",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/P19-1074",
    doi = "10.18653/v1/P19-1074",
    pages = "764--777",
}

Contributions

Thanks to @ghomasHudson, @thomwolf, @lhoestq for adding this dataset.

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