numericnlg / dataset_infos.json
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{"default": {
"description": "NumericNLG is a dataset for table-totext generation focusing on numerical reasoning. \nThe dataset consists of textual descriptions of numerical tables from scientific papers.\n",
"citation": "@inproceedings{suadaa-etal-2021-towards,\n title = \"Towards Table-to-Text Generation with Numerical Reasoning\",\n author = \"Suadaa, Lya Hulliyyatus and\n Kamigaito, Hidetaka and\n Funakoshi, Kotaro and\n Okumura, Manabu and\n Takamura, Hiroya\",\n booktitle = \"Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)\",\n month = aug,\n year = \"2021\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/2021.acl-long.115\",\n doi = \"10.18653/v1/2021.acl-long.115\",\n pages = \"1451--1465\"\n}\n",
"homepage": "https://github.com/titech-nlp/numeric-nlg",
"license": "CC BY-SA 4.0",
"features": {
"table_id_paper": {
"dtype": "string",
"_type": "Value"
},
"caption": {
"dtype": "string",
"_type": "Value"
},
"row_header_level": {
"dtype": "int32",
"_type": "Value"
},
"row_headers": {
"dtype": "large_string",
"_type": "Value"
},
"column_header_level": {
"dtype": "int32",
"_type": "Value"
},
"column_headers": {
"dtype": "large_string",
"_type": "Value"
},
"contents": {
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"_type": "Value"
},
"metrics_loc": {
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"_type": "Value"
},
"metrics_type": {
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"_type": "Value"
},
"target_entity": {
"dtype": "large_string",
"_type": "Value"
},
"table_html_clean": {
"dtype": "large_string",
"_type": "Value"
},
"table_name": {
"dtype": "string",
"_type": "Value"
},
"table_id": {
"dtype": "string",
"_type": "Value"
},
"paper_id": {
"dtype": "string",
"_type": "Value"
},
"page_no": {
"dtype": "int32",
"_type": "Value"
},
"dir": {
"dtype": "string",
"_type": "Value"
},
"valid": {
"dtype": "int32",
"_type": "Value"
}
},
"builder_name": "numericnlg",
"config_name": "default",
"version": {
"version_str": "1.0.0",
"major": 1,
"minor": 0,
"patch": 0
},
"splits": {
"train": {
"name": "train",
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"num_examples": 1084,
"dataset_name": null
},
"validation": {
"name": "validation",
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"num_examples": 136,
"dataset_name": null
},
"test": {
"name": "test",
"num_bytes": 298309,
"num_examples": 135,
"dataset_name": null
}
},
"download_size": 1101061,
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}}