| --- |
| annotations_creators: |
| - expert-generated |
| language: |
| - en |
| language_creators: |
| - found |
| license: [] |
| multilinguality: |
| - monolingual |
| pretty_name: KnowledgeNet is a dataset for automatically populating a knowledge base |
| size_categories: |
| - 10K<n<100K |
| source_datasets: [] |
| tags: |
| - knowledgenet |
| task_categories: |
| - text-classification |
| task_ids: |
| - multi-class-classification |
| - entity-linking-classification |
| dataset_info: |
| - config_name: knet |
| features: |
| - name: fold |
| dtype: int32 |
| - name: documentId |
| dtype: string |
| - name: source |
| dtype: string |
| - name: documentText |
| dtype: string |
| - name: passages |
| sequence: |
| - name: passageId |
| dtype: string |
| - name: passageStart |
| dtype: int32 |
| - name: passageEnd |
| dtype: int32 |
| - name: passageText |
| dtype: string |
| - name: exhaustivelyAnnotatedProperties |
| sequence: |
| - name: propertyId |
| dtype: string |
| - name: propertyName |
| dtype: string |
| - name: propertyDescription |
| dtype: string |
| - name: facts |
| sequence: |
| - name: factId |
| dtype: string |
| - name: propertyId |
| dtype: string |
| - name: humanReadable |
| dtype: string |
| - name: annotatedPassage |
| dtype: string |
| - name: subjectStart |
| dtype: int32 |
| - name: subjectEnd |
| dtype: int32 |
| - name: subjectText |
| dtype: string |
| - name: subjectUri |
| dtype: string |
| - name: objectStart |
| dtype: int32 |
| - name: objectEnd |
| dtype: int32 |
| - name: objectText |
| dtype: string |
| - name: objectUri |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 10161415 |
| num_examples: 3977 |
| download_size: 14119313 |
| dataset_size: 10161415 |
| - config_name: knet_tokenized |
| features: |
| - name: doc_id |
| dtype: string |
| - name: passage_id |
| dtype: string |
| - name: fact_id |
| dtype: string |
| - name: tokens |
| sequence: string |
| - name: subj_start |
| dtype: int32 |
| - name: subj_end |
| dtype: int32 |
| - name: subj_type |
| dtype: |
| class_label: |
| names: |
| '0': O |
| '1': PER |
| '2': ORG |
| '3': LOC |
| '4': DATE |
| - name: subj_uri |
| dtype: string |
| - name: obj_start |
| dtype: int32 |
| - name: obj_end |
| dtype: int32 |
| - name: obj_type |
| dtype: |
| class_label: |
| names: |
| '0': O |
| '1': PER |
| '2': ORG |
| '3': LOC |
| '4': DATE |
| - name: obj_uri |
| dtype: string |
| - name: relation |
| dtype: |
| class_label: |
| names: |
| '0': NO_RELATION |
| '1': DATE_OF_BIRTH |
| '2': DATE_OF_DEATH |
| '3': PLACE_OF_RESIDENCE |
| '4': PLACE_OF_BIRTH |
| '5': NATIONALITY |
| '6': EMPLOYEE_OR_MEMBER_OF |
| '7': EDUCATED_AT |
| '8': POLITICAL_AFFILIATION |
| '9': CHILD_OF |
| '10': SPOUSE |
| '11': DATE_FOUNDED |
| '12': HEADQUARTERS |
| '13': SUBSIDIARY_OF |
| '14': FOUNDED_BY |
| '15': CEO |
| splits: |
| - name: train |
| num_bytes: 4511963 |
| num_examples: 10895 |
| download_size: 14119313 |
| dataset_size: 4511963 |
| - config_name: knet_re |
| features: |
| - name: documentId |
| dtype: string |
| - name: passageId |
| dtype: string |
| - name: factId |
| dtype: string |
| - name: passageText |
| dtype: string |
| - name: humanReadable |
| dtype: string |
| - name: annotatedPassage |
| dtype: string |
| - name: subjectStart |
| dtype: int32 |
| - name: subjectEnd |
| dtype: int32 |
| - name: subjectText |
| dtype: string |
| - name: subjectType |
| dtype: |
| class_label: |
| names: |
| '0': O |
| '1': PER |
| '2': ORG |
| '3': LOC |
| '4': DATE |
| - name: subjectUri |
| dtype: string |
| - name: objectStart |
| dtype: int32 |
| - name: objectEnd |
| dtype: int32 |
| - name: objectText |
| dtype: string |
| - name: objectType |
| dtype: |
| class_label: |
| names: |
| '0': O |
| '1': PER |
| '2': ORG |
| '3': LOC |
| '4': DATE |
| - name: objectUri |
| dtype: string |
| - name: relation |
| dtype: |
| class_label: |
| names: |
| '0': NO_RELATION |
| '1': DATE_OF_BIRTH |
| '2': DATE_OF_DEATH |
| '3': PLACE_OF_RESIDENCE |
| '4': PLACE_OF_BIRTH |
| '5': NATIONALITY |
| '6': EMPLOYEE_OR_MEMBER_OF |
| '7': EDUCATED_AT |
| '8': POLITICAL_AFFILIATION |
| '9': CHILD_OF |
| '10': SPOUSE |
| '11': DATE_FOUNDED |
| '12': HEADQUARTERS |
| '13': SUBSIDIARY_OF |
| '14': FOUNDED_BY |
| '15': CEO |
| splits: |
| - name: train |
| num_bytes: 6098219 |
| num_examples: 10895 |
| download_size: 14119313 |
| dataset_size: 6098219 |
| --- |
| # Dataset Card for "KnowledgeNet" |
| ## Table of Contents |
| - [Table of Contents](#table-of-contents) |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
| ## Dataset Description |
| - **Repository:** [knowledge-net](https://github.com/diffbot/knowledge-net) |
| - **Paper:** [KnowledgeNet: A Benchmark Dataset for Knowledge Base Population](https://aclanthology.org/D19-1069/) |
| - **Size of downloaded dataset files:** 12.59 MB |
| - **Size of the generated dataset:** 6.1 MB |
| ### 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](https://github.com/diffbot/knowledge-net/blob/master/knowledgenet-emnlp-cameraready.pdf). |
|
|
| 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 |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
| ### 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: |
| ```json |
| { |
| "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: |
| ```json |
| { |
| "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: |
| ```json |
| { |
| "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, a `int` feature. |
| - `documentId`: the document id, a `string` feature. |
| - `source`: the source, a `string` feature. |
| - `documenText`: the document text, a `string` feature. |
| - `passages`: the list of passages, a `list` of `dict`. |
| - `passageId`: the passage id, a `string` feature. |
| - `passageStart`: the passage start, a `int` feature. |
| - `passageEnd`: the passage end, a `int` feature. |
| - `passageText`: the passage text, a `string` feature. |
| - `exhaustivelyAnnotatedProperties`: the list of exhaustively annotated properties, a `list` of `dict`. |
| - `propertyId`: the property id, a `string` feature. |
| - `propertyName`: the property name, a `string` feature. |
| - `propertyDescription`: the property description, a `string` feature. |
| - `facts`: the list of facts, a `list` of `dict`. |
| - `factId`: the fact id, a `string` feature. |
| - `propertyId`: the property id, a `string` feature. |
| - `humanReadable`: the human readable annotation, a `string` feature. |
| - `annotatedPassage`: the annotated passage, a `string` feature. |
| - `subjectStart`: the subject start, a `int` feature. |
| - `subjectEnd`: the subject end, a `int` feature. |
| - `subjectText`: the subject text, a `string` feature. |
| - `subjectUri`: the subject uri, a `string` feature. |
| - `objectStart`: the object start, a `int` feature. |
| - `objectEnd`: the object end, a `int` feature. |
| - `objectText`: the object text, a `string` feature. |
| - `objectUri`: the object uri, a `string` feature. |
|
|
| #### knet_re |
| - `documentId`: the document id, a `string` feature. |
| - `passageId`: the passage id, a `string` feature. |
| - `passageText`: the passage text, a `string` feature. |
| - `factId`: the fact id, a `string` feature. |
| - `humanReadable`: human-readable annotation, a `string` features. |
| - `annotatedPassage`: annotated passage, a `string` feature. |
| - `subjectStart`: the index of the start character of the relation subject mention, an `ìnt` feature. |
| - `subjectEnd`: the index of the end character of the relation subject mention, exclusive, an `ìnt` feature. |
| - `subjectText`: the text the subject mention, a `string` feature. |
| - `subjectType`: the NER type of the subject mention, a `string` classification label. |
| |
| ```json |
| {"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4} |
| ``` |
| |
| - `subjectUri`: the Wikidata URI of the subject mention, a `string` feature. |
| - `objectStart`: the index of the start character of the relation object mention, an `ìnt` feature. |
| - `objectEnd`: the index of the end character of the relation object mention, exclusive, an `ìnt` feature. |
| - `objectText`: the text the object mention, a `string` feature. |
| - `objectType`: the NER type of the object mention, a `string` classification label. |
| |
| ```json |
| {"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4} |
| ``` |
| |
| - `objectUri`: the Wikidata URI of the object mention, a `string` feature. |
| - `relation`: the relation label of this instance, a `string` classification label. |
| |
| ```json |
| {"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, a `string` feature. |
| - `passage_id`: the passage id, a `string` feature. |
| - `factId`: the fact id, a `string` feature. |
| - `tokens`: the list of tokens of this passage, obtained with spaCy, a `list` of `string` features. |
| - `subj_start`: the index of the start token of the relation subject mention, an `ìnt` feature. |
| - `subj_end`: the index of the end token of the relation subject mention, exclusive, an `ìnt` feature. |
| - `subj_type`: the NER type of the subject mention, a `string` classification label. |
|
|
| ```json |
| {"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4} |
| ``` |
|
|
|
|
| - `subj_uri`: the Wikidata URI of the subject mention, a `string` feature. |
| - `obj_start`: the index of the start token of the relation object mention, an `ìnt` feature. |
| - `obj_end`: the index of the end token of the relation object mention, exclusive, an `ìnt` feature. |
| - `obj_type`: the NER type of the object mention, a `string` classification label. |
|
|
| ```json |
| {"O": 0, "PER": 1, "ORG": 2, "LOC": 3, "DATE": 4} |
| ``` |
|
|
| - `obj_uri`: the Wikidata URI of the object mention, a `string` feature. |
| - `relation`: the relation label of this instance, a `string` classification label. |
|
|
| ```json |
| {"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 |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ## Dataset Creation |
| ### Curation Rationale |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Source Data |
| #### Initial Data Collection and Normalization |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| #### Who are the source language producers? |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Annotations |
| #### Annotation process |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| are labeled as no_relation. |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Personal and Sensitive Information |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ## Considerations for Using the Data |
| ### Social Impact of Dataset |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Discussion of Biases |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Other Known Limitations |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ## Additional Information |
| ### Dataset Curators |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### Licensing Information |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
| ### 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](https://github.com/phucdev) for adding this dataset. |
