Datasets:
Tasks:
Text Classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
expert-generated
| 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. |