nielsr/coref-bert-base
Updated
•
53
•
4
Datasets:
Tasks:
Text Retrieval
Sub-tasks:
entity-linking-retrieval
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
crowdsourced
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
License:
mit
title
string
| sents
sequence
| vertexSet
list
| labels
sequence
|
|---|---|---|---|
"Skai TV" | [
[
"Skai",
"TV",
"is",
"a",
"Greek",
"free",
"-",
"to",
"-",
"air",
"television",
"network",
"based",
"in",
"Piraeus",
"."
],
[
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"Skai",
"Group",
",",
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"of",
"the",
"largest",
"media",
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"in",
"the",
"country",
"."
],
[
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"on",
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"of",
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"the",
"Athens",
"metropolitan",
"area",
",",
"and",
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"spread",
"its",
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"."
],
[
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",",
"it",
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"the",
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"-",
"based",
"encrypted",
"services",
"of",
"Nova",
"and",
"Cosmote",
"TV",
"."
],
[
"Skai",
"TV",
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"a",
"member",
"of",
"Digea",
",",
"a",
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"of",
"private",
"television",
"networks",
"introducing",
"digital",
"terrestrial",
"transmission",
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"Greece",
"."
],
[
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",",
"Skai",
"TV",
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"all",
"foreign",
"language",
"content",
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"Greek",
",",
"instead",
"of",
"using",
"subtitles",
"."
],
[
"This",
"is",
"very",
"uncommon",
"in",
"Greece",
"for",
"anything",
"except",
"documentaries",
"(",
"using",
"voiceover",
"dubbing",
")",
"and",
"children",
"'s",
"programmes",
"(",
"using",
"lip",
"-",
"synced",
"dubbing",
")",
",",
"so",
"after",
"intense",
"criticism",
"the",
"station",
"switched",
"to",
"using",
"subtitles",
"for",
"almost",
"all",
"foreign",
"shows",
"."
]
] | [
[
{
"pos": [
0,
2
],
"type": "ORG",
"sent_id": 4,
"name": "Skai TV"
},
{
"pos": [
0,
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],
"type": "ORG",
"sent_id": 0,
"name": "Skai TV"
},
{
"pos": [
3,
5
],
"type": "ORG",
"sent_id": 5,
"name": "Skai TV"
}
],
[
{
"name": "Greek",
"pos": [
4,
5
],
"sent_id": 0,
"type": "LOC"
}
],
[
{
"name": "Piraeus",
"pos": [
14,
15
],
"sent_id": 0,
"type": "LOC"
}
],
[
{
"name": "Skai Group",
"pos": [
5,
7
],
"sent_id": 1,
"type": "ORG"
}
],
[
{
"pos": [
8,
12
],
"type": "TIME",
"sent_id": 2,
"name": "1st of April 2006"
}
],
[
{
"name": "Athens",
"pos": [
14,
15
],
"sent_id": 2,
"type": "LOC"
}
],
[
{
"name": "Nova",
"pos": [
16,
17
],
"sent_id": 3,
"type": "ORG"
}
],
[
{
"pos": [
18,
20
],
"type": "ORG",
"sent_id": 3,
"name": "Cosmote TV"
}
],
[
{
"pos": [
7,
8
],
"type": "ORG",
"sent_id": 4,
"name": "Digea"
}
],
[
{
"name": "Greece",
"pos": [
20,
21
],
"sent_id": 4,
"type": "LOC"
},
{
"name": "Greece",
"pos": [
5,
6
],
"sent_id": 6,
"type": "LOC"
}
],
[
{
"sent_id": 5,
"type": "MISC",
"pos": [
13,
14
],
"name": "Greek"
}
]
] | {
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0,
0
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9,
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],
"relation_id": [
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"P17",
"P17",
"P159",
"P127",
"P159",
"P17"
],
"relation_text": [
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"country",
"country",
"headquarters location",
"owned by",
"headquarters location",
"country"
],
"evidence": [
[
0,
4
],
[
0,
1,
4
],
[
0,
2,
4
],
[
0
],
[
0,
1
],
[
0,
2
],
[
0,
4,
5,
6
]
]
} |
"Washington Place (West Virginia)" | [
[
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"(",
"William",
"Washington",
"House",
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"one",
"of",
"the",
"first",
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"by",
"freed",
"slaves",
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"the",
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"Proclamation",
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"in",
"Hampshire",
"County",
",",
"West",
"Virginia",
",",
"United",
"States",
"."
],
[
"Washington",
"Place",
"was",
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"by",
"William",
"and",
"Annie",
"Washington",
"in",
"north",
"Romney",
"between",
"1863",
"and",
"1874",
"on",
"land",
"given",
"to",
"Annie",
"by",
"her",
"former",
"owner",
",",
"Susan",
"Blue",
"Parsons",
"of",
"Wappocomo",
"plantation",
"."
],
[
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"Washington",
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"properties",
"on",
"the",
"hills",
"north",
"of",
"Romney",
"along",
"West",
"Virginia",
"Route",
"28",
"and",
"became",
"the",
"first",
"African",
"-",
"American",
"land",
"developer",
"in",
"the",
"state",
"of",
"West",
"Virginia",
"."
],
[
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"of",
"his",
"subdivisions",
"is",
"the",
"\"",
"Blacks",
"Hill",
"\"",
"neighborhood",
"of",
"Romney",
",",
"adjacent",
"to",
"the",
"Washington",
"Place",
"homestead",
"."
],
[
"Washington",
"Place",
"was",
"bought",
"and",
"restored",
"by",
"Ralph",
"W.",
"Haines",
",",
"a",
"local",
"attorney",
"and",
"historic",
"preservationist",
"."
]
] | [
[
{
"pos": [
0,
2
],
"type": "LOC",
"sent_id": 0,
"name": "Washington Place"
},
{
"name": "William Washington House",
"pos": [
3,
6
],
"sent_id": 0,
"type": "LOC"
},
{
"pos": [
0,
2
],
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19
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},
{
"pos": [
0,
2
],
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}
],
[
{
"name": "Emancipation Proclamation",
"pos": [
19,
21
],
"sent_id": 0,
"type": "MISC"
}
],
[
{
"pos": [
22,
23
],
"type": "TIME",
"sent_id": 0,
"name": "1863"
},
{
"pos": [
13,
14
],
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}
],
[
{
"name": "Hampshire County",
"pos": [
24,
26
],
"sent_id": 0,
"type": "LOC"
}
],
[
{
"name": "West Virginia",
"pos": [
27,
29
],
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},
{
"name": "West Virginia",
"pos": [
30,
32
],
"sent_id": 2,
"type": "LOC"
}
],
[
{
"name": "United States",
"pos": [
30,
32
],
"sent_id": 0,
"type": "LOC"
}
],
[
{
"name": "William",
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5,
6
],
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}
],
[
{
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7,
9
],
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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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21
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"type": "PER"
}
],
[
{
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"name": "Susan Blue Parsons"
}
],
[
{
"sent_id": 1,
"type": "LOC",
"pos": [
30,
32
],
"name": "Wappocomo plantation"
}
],
[
{
"name": "William Washington",
"pos": [
0,
2
],
"sent_id": 2,
"type": "PER"
}
],
[
{
"name": "West Virginia Route 28",
"pos": [
13,
17
],
"sent_id": 2,
"type": "LOC"
}
],
[
{
"name": "African",
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21,
22
],
"sent_id": 2,
"type": "LOC"
}
],
[
{
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23,
24
],
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"name": "American"
}
],
[
{
"pos": [
7,
9
],
"type": "MISC",
"name": "Blacks Hill",
"sent_id": 3
}
],
[
{
"pos": [
7,
10
],
"type": "PER",
"sent_id": 4,
"name": "Ralph W. Haines"
}
]
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3,
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4,
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"relation_text": [
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"country",
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"located in the administrative territorial entity",
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"country of citizenship",
"country of citizenship",
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0
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0
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} |
"IBM Research – Brazil" | [
[
"IBM",
"Research",
"–",
"Brazil",
"is",
"one",
"of",
"twelve",
"research",
"laboratories",
"comprising",
"IBM",
"Research",
",",
"its",
"first",
"in",
"South",
"America",
"."
],
[
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"established",
"in",
"June",
"2010",
",",
"with",
"locations",
"in",
"São",
"Paulo",
"and",
"Rio",
"de",
"Janeiro",
"."
],
[
"Research",
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"Technology",
"and",
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",",
"Systems",
"of",
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"and",
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",",
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"and",
"Natural",
"Resources",
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"."
],
[
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",",
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"12",
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",",
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"the",
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"."
],
[
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",",
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"large",
"-",
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"."
],
[
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":",
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",",
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"gas",
",",
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"."
],
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"]",
",",
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"."
],
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"area",
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],
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",",
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],
[
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"one",
"is",
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"cities",
".",
"\""
]
] | [
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],
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{
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"type": "MISC",
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{
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],
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{
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}
],
[
{
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],
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],
"relation_text": [
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0
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5
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0
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]
} |
"Lookin Ass" | [
[
"\"",
"Lookin",
"Ass",
"\"",
"(",
"originally",
"titled",
"\"",
"Lookin",
"Ass",
"Nigga",
"\"",
")",
"is",
"a",
"song",
"by",
"American",
"rapper",
"and",
"singer",
"Nicki",
"Minaj",
"."
],
[
"It",
"was",
"produced",
"by",
"Detail",
"and",
"Choppa",
"Boi",
"."
],
[
"It",
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"recorded",
"by",
"Minaj",
"for",
"the",
"Young",
"Money",
"Entertainment",
"compilation",
"album",
"(",
"2014",
")",
"."
],
[
"The",
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"video",
"for",
"the",
"track",
"was",
"released",
"on",
"February",
"14",
",",
"2014",
"."
],
[
"The",
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"a",
"hip",
"hop",
"song",
"whose",
"lyrics",
"criticize",
"stereotypical",
"behaviors",
"commonly",
"associated",
"with",
"men",
"."
],
[
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"cover",
"also",
"generated",
"controversy",
"for",
"placing",
"an",
"image",
"of",
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{
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"Rose Porteous" | [
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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
Languages
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: astringfeature.sents: a dictionary feature containing:feature: astringfeature.
name: astringfeature.sent_id: aint32feature.pos: alistofint32features.type: astringfeature.labels: a dictionary feature containing:head: aint32feature.tail: aint32feature.relation_id: astringfeature.relation_text: astringfeature.evidence: alistofint32features.
Data Splits
| name | train_annotated | train_distant | validation | test |
|---|---|---|---|---|
| default | 3053 | 101873 | 998 | 1000 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
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.
- Downloads last month
- 922
Repository:
github.com
Paper:
DocRED: A Large-Scale Document-Level Relation Extraction Dataset
Size of downloaded dataset files:
95.6 MB
Size of the auto-converted Parquet files:
106 MB
Number of rows:
106,924