Datasets:
The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for "KnowledgeNet"
Dataset Summary
KnowledgeNet is a benchmark dataset for the task of automatically populating a knowledge base (Wikidata) with facts expressed in natural language text on the web. KnowledgeNet provides text exhaustively annotated with facts, thus enabling the holistic end-to-end evaluation of knowledge base population systems as a whole, unlike previous benchmarks that are more suitable for the evaluation of individual subcomponents (e.g., entity linking, relation extraction).
For instance, the dataset contains text expressing the fact (Gennaro Basile; RESIDENCE; Moravia), in the passage: "Gennaro Basile was an Italian painter, born in Naples but active in the German-speaking countries. He settled at Brünn, in Moravia, and lived about 1756..."
For a description of the dataset and baseline systems, please refer to their EMNLP paper.
Note: This Datasetreader currently only supports the train
split and does not contain negative examples.
In addition to the original format this repository also provides two version (knet_re
, knet_tokenized
) that are
easier to use for simple relation extraction. You can load them with
datasets.load_dataset("DFKI-SLT/knowledge_net", name="<config>")
.
Supported Tasks and Leaderboards
Languages
The language in the dataset is English.
Dataset Structure
Data Instances
knet
- Size of downloaded dataset files: 12.59 MB
- Size of the generated dataset: 10.16 MB
An example of 'train' looks as follows:
{
"fold": 2,
"documentId": "8313",
"source": "DBpedia Abstract",
"documentText": "Gennaro Basile\n\nGennaro Basile was an Italian painter, born in Naples but active in the German-speaking countries. He settled at Brünn, in Moravia, and lived about 1756. His best picture is the altar-piece in the chapel of the chateau at Seeberg, in Salzburg. Most of his works remained in Moravia.",
"passages": [
{
"passageId": "8313:16:114",
"passageStart": 16,
"passageEnd": 114,
"passageText": "Gennaro Basile was an Italian painter, born in Naples but active in the German-speaking countries.",
"exhaustivelyAnnotatedProperties": [
{
"propertyId": "12",
"propertyName": "PLACE_OF_BIRTH",
"propertyDescription": "Describes the relationship between a person and the location where she/he was born."
}
],
"facts": [
{
"factId": "8313:16:30:63:69:12",
"propertyId": "12",
"humanReadable": "<Gennaro Basile> <PLACE_OF_BIRTH> <Naples>",
"annotatedPassage": "<Gennaro Basile> was an Italian painter, born in <Naples> but active in the German-speaking countries.",
"subjectStart": 16,
"subjectEnd": 30,
"subjectText": "Gennaro Basile",
"subjectUri": "http://www.wikidata.org/entity/Q19517888",
"objectStart": 63,
"objectEnd": 69,
"objectText": "Naples",
"objectUri": "http://www.wikidata.org/entity/Q2634"
}
]
},
{
"passageId": "8313:115:169",
"passageStart": 115,
"passageEnd": 169,
"passageText": "He settled at Brünn, in Moravia, and lived about 1756.",
"exhaustivelyAnnotatedProperties": [
{
"propertyId": "11",
"propertyName": "PLACE_OF_RESIDENCE",
"propertyDescription": "Describes the relationship between a person and the location where she/he lives/lived."
},
{
"propertyId": "12",
"propertyName": "PLACE_OF_BIRTH",
"propertyDescription": "Describes the relationship between a person and the location where she/he was born."
}
],
"facts": [
{
"factId": "8313:115:117:129:134:11",
"propertyId": "11",
"humanReadable": "<He> <PLACE_OF_RESIDENCE> <Brünn>",
"annotatedPassage": "<He> settled at <Brünn>, in Moravia, and lived about 1756.",
"subjectStart": 115,
"subjectEnd": 117,
"subjectText": "He",
"subjectUri": "http://www.wikidata.org/entity/Q19517888",
"objectStart": 129,
"objectEnd": 134,
"objectText": "Brünn",
"objectUri": "http://www.wikidata.org/entity/Q14960"
},
{
"factId": "8313:115:117:139:146:11",
"propertyId": "11",
"humanReadable": "<He> <PLACE_OF_RESIDENCE> <Moravia>",
"annotatedPassage": "<He> settled at Brünn, in <Moravia>, and lived about 1756.",
"subjectStart": 115,
"subjectEnd": 117,
"subjectText": "He",
"subjectUri": "http://www.wikidata.org/entity/Q19517888",
"objectStart": 139,
"objectEnd": 146,
"objectText": "Moravia",
"objectUri": "http://www.wikidata.org/entity/Q43266"
}
]
}
]
}
knet_re
- Size of downloaded dataset files: 12.59 MB
- Size of the generated dataset: 6.1 MB
An example of 'train' looks as follows:
{
"documentId": "7",
"passageId": "7:23:206",
"factId": "7:23:44:138:160:1",
"passageText": "Tata Chemicals Europe (formerly Brunner Mond (UK) Limited) is a UK-based chemicals company that is a subsidiary of Tata Chemicals Limited, itself a part of the India-based Tata Group.",
"humanReadable": "<Tata Chemicals Europe> <SUBSIDIARY_OF> <Tata Chemicals Limited>",
"annotatedPassage": "<Tata Chemicals Europe> (formerly Brunner Mond (UK) Limited) is a UK-based chemicals company that is a subsidiary of <Tata Chemicals Limited>, itself a part of the India-based Tata Group.",
"subjectStart": 0,
"subjectEnd": 21,
"subjectText": "Tata Chemicals Europe",
"subjectType": 2,
"subjectUri": "",
"objectStart": 115,
"objectEnd": 137,
"objectText": "Tata Chemicals Limited",
"objectType": 2,
"objectUri": "http://www.wikidata.org/entity/Q2331365",
"relation": 13
}
knet_tokenized
- Size of downloaded dataset files: 12.59 MB
- Size of the generated dataset: 4.5 MB
An example of 'train' looks as follows:
{
"doc_id": "7",
"passage_id": "7:23:206",
"fact_id": "7:162:168:183:205:1",
"tokens": ["Tata", "Chemicals", "Europe", "(", "formerly", "Brunner", "Mond", "(", "UK", ")", "Limited", ")", "is", "a", "UK", "-", "based", "chemicals", "company", "that", "is", "a", "subsidiary", "of", "Tata", "Chemicals", "Limited", ",", "itself", "a", "part", "of", "the", "India", "-", "based", "Tata", "Group", "."],
"subj_start": 28,
"subj_end": 29,
"subj_type": 2,
"subj_uri": "http://www.wikidata.org/entity/Q2331365",
"obj_start": 33,
"obj_end": 38,
"obj_type": 2,
"obj_uri": "http://www.wikidata.org/entity/Q331715",
"relation": 13
}
Data Fields
knet
fold
: the fold, aint
feature.documentId
: the document id, astring
feature.source
: the source, astring
feature.documenText
: the document text, astring
feature.passages
: the list of passages, alist
ofdict
.passageId
: the passage id, astring
feature.passageStart
: the passage start, aint
feature.passageEnd
: the passage end, aint
feature.passageText
: the passage text, astring
feature.exhaustivelyAnnotatedProperties
: the list of exhaustively annotated properties, alist
ofdict
.propertyId
: the property id, astring
feature.propertyName
: the property name, astring
feature.propertyDescription
: the property description, astring
feature.
facts
: the list of facts, alist
ofdict
.factId
: the fact id, astring
feature.propertyId
: the property id, astring
feature.humanReadable
: the human readable annotation, astring
feature.annotatedPassage
: the annotated passage, astring
feature.subjectStart
: the subject start, aint
feature.subjectEnd
: the subject end, aint
feature.subjectText
: the subject text, astring
feature.subjectUri
: the subject uri, astring
feature.objectStart
: the object start, aint
feature.objectEnd
: the object end, aint
feature.objectText
: the object text, astring
feature.objectUri
: the object uri, astring
feature.
knet_re
documentId
: the document id, astring
feature.passageId
: the passage id, astring
feature.passageText
: the passage text, astring
feature.factId
: the fact id, astring
feature.humanReadable
: human-readable annotation, astring
features.annotatedPassage
: annotated passage, astring
feature.subjectStart
: the index of the start character of the relation subject mention, anìnt
feature.subjectEnd
: the index of the end character of the relation subject mention, exclusive, anìnt
feature.subjectText
: the text the subject mention, astring
feature.subjectType
: the NER type of the subject mention, astring
classification label.
{"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4}
subjectUri
: the Wikidata URI of the subject mention, astring
feature.objectStart
: the index of the start character of the relation object mention, anìnt
feature.objectEnd
: the index of the end character of the relation object mention, exclusive, anìnt
feature.objectText
: the text the object mention, astring
feature.objectType
: the NER type of the object mention, astring
classification label.
{"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4}
objectUri
: the Wikidata URI of the object mention, astring
feature.relation
: the relation label of this instance, astring
classification label.
{"NO_RELATION": 0, "DATE_OF_BIRTH": 1, "DATE_OF_DEATH": 2, "PLACE_OF_RESIDENCE": 3, "PLACE_OF_BIRTH": 4, "NATIONALITY": 5, "EMPLOYEE_OR_MEMBER_OF": 6, "EDUCATED_AT": 7, "POLITICAL_AFFILIATION": 8, "CHILD_OF": 9, "SPOUSE": 10, "DATE_FOUNDED": 11, "HEADQUARTERS": 12, "SUBSIDIARY_OF": 13, "FOUNDED_BY": 14, "CEO": 15}
knet_tokenized
doc_id
: the document id, astring
feature.passage_id
: the passage id, astring
feature.factId
: the fact id, astring
feature.tokens
: the list of tokens of this passage, obtained with spaCy, alist
ofstring
features.subj_start
: the index of the start token of the relation subject mention, anìnt
feature.subj_end
: the index of the end token of the relation subject mention, exclusive, anìnt
feature.subj_type
: the NER type of the subject mention, astring
classification label.
{"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4}
subj_uri
: the Wikidata URI of the subject mention, astring
feature.obj_start
: the index of the start token of the relation object mention, anìnt
feature.obj_end
: the index of the end token of the relation object mention, exclusive, anìnt
feature.obj_type
: the NER type of the object mention, astring
classification label.
{"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4}
obj_uri
: the Wikidata URI of the object mention, astring
feature.relation
: the relation label of this instance, astring
classification label.
{"NO_RELATION": 0, "DATE_OF_BIRTH": 1, "DATE_OF_DEATH": 2, "PLACE_OF_RESIDENCE": 3, "PLACE_OF_BIRTH": 4, "NATIONALITY": 5, "EMPLOYEE_OR_MEMBER_OF": 6, "EDUCATED_AT": 7, "POLITICAL_AFFILIATION": 8, "CHILD_OF": 9, "SPOUSE": 10, "DATE_FOUNDED": 11, "HEADQUARTERS": 12, "SUBSIDIARY_OF": 13, "FOUNDED_BY": 14, "CEO": 15}
Data Splits
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
More Information Needed are labeled as no_relation. More Information Needed
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{mesquita-etal-2019-knowledgenet,
title = "{K}nowledge{N}et: A Benchmark Dataset for Knowledge Base Population",
author = "Mesquita, Filipe and
Cannaviccio, Matteo and
Schmidek, Jordan and
Mirza, Paramita and
Barbosa, Denilson",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1069",
doi = "10.18653/v1/D19-1069",
pages = "749--758",}
Contributions
Thanks to @phucdev for adding this dataset.
- Downloads last month
- 42