|
--- |
|
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, |
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title = "{K}nowledge{N}et: A Benchmark Dataset for Knowledge Base Population", |
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author = "Mesquita, Filipe and |
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Cannaviccio, Matteo and |
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Schmidek, Jordan and |
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Mirza, Paramita and |
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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)", |
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month = nov, |
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year = "2019", |
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address = "Hong Kong, China", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/D19-1069", |
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doi = "10.18653/v1/D19-1069", |
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pages = "749--758",} |
|
``` |
|
|
|
### Contributions |
|
Thanks to [@phucdev](https://github.com/phucdev) for adding this dataset. |