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""" |
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The script used to load the dataset from the original source. |
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""" |
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import json |
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import datasets |
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import glob |
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import os |
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_CITATION = """\ |
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@inproceedings{chen2020logical, |
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title={Logical Natural Language Generation from Open-Domain Tables}, |
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author={Chen, Wenhu and Chen, Jianshu and Su, Yu and Chen, Zhiyu and Wang, William Yang}, |
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booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics}, |
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pages={7929--7942}, |
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year={2020} |
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} |
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""" |
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_DESCRIPTION = """\ |
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LogicNLG is a dataset for natural language generation from open-domain tables. |
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LogicNLG is based on TabFact (Chen et al., 2019), which is a table-based fact-checking dataset with rich logical inferences in the annotated statements. |
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""" |
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_URL = "https://github.com/wenhuchen/LogicNLG" |
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_LICENSE = "MIT" |
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class LogicNLG(datasets.GeneratorBasedBuilder): |
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VERSION = "1.0.0" |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({ |
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'table': datasets.Value(dtype='large_string'), |
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"ref": datasets.Value(dtype='string'), |
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"linked_columns": datasets.Value(dtype='string'), |
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"title": datasets.Value(dtype='string'), |
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"template": datasets.Value(dtype='string'), |
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"table_id": datasets.Value(dtype='string'), |
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}), |
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supervised_keys=None, |
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homepage="https://wenhuchen.github.io/logicnlg.github.io/", |
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citation=_CITATION, |
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license=_LICENSE, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "data", "split" : "train"}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "data", "split" : "dev"}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": "data", "split" : "test"}), |
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] |
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def _generate_examples(self, filepath, split): |
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filename = split if split != "dev" else "val" |
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data = [] |
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with open(os.path.join(filepath, f"{filename}_lm.json")) as f: |
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j = json.load(f) |
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for i, (table_id, examples) in enumerate(j.items()): |
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table = [] |
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with open(os.path.join(filepath, "all_csv", table_id)) as f: |
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for line in f.readlines(): |
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table.append(line.rstrip("\n").split("#")) |
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for example in examples: |
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data.append({ |
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"table": table, |
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"ref": example[0], |
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"linked_columns": example[1], |
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"title": example[2], |
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"template": example[3], |
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"table_id": table_id, |
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}) |
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for example_idx, entry in enumerate(data): |
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yield example_idx, {key: str(value) for key, value in entry.items()} |
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if __name__ == '__main__': |
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dataset = datasets.load_dataset(__file__) |
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dataset.push_to_hub("kasnerz/logicnlg") |
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