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"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages.""" |
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import os |
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import json |
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import pandas as pd |
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import datasets |
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from datasets import DownloadManager |
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_CITATION = """\ |
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@misc{aggarwal2023evaluating, |
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title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, |
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author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan}, |
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year={2023}, |
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eprint={2304.13005}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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""" |
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_DESCRIPTION = """\ |
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IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages |
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""" |
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_LANGUAGES = ( |
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'hi', |
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'bn', |
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'mr', |
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'as', |
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'ta', |
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'te', |
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'or', |
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'ml', |
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'pa', |
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'gu', |
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'kn' |
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) |
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_DATASETS = ( |
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'iTOP', |
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'indic-atis', |
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'indic-TOP' |
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) |
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_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/" |
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class IESemParseConfig(datasets.BuilderConfig): |
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"""BuilderConfig for IE-SemParse.""" |
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def __init__(self, dataset: str, language: str, **kwargs): |
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"""BuilderConfig for IE-SemParse. |
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Args: |
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language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(IESemParseConfig, self).__init__(**kwargs) |
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self.dataset = dataset |
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self.language = language |
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self.languages = _LANGUAGES |
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self.datasets = _DATASETS |
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self._URLS = [os.path.join(_URL, "unfiltered_data", dataset, f"{language}.json")] |
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class IESemParse(datasets.GeneratorBasedBuilder): |
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"""IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0.""" |
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VERSION = datasets.Version("1.0.0", "") |
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BUILDER_CONFIG_CLASS = IESemParseConfig |
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BUILDER_CONFIGS = [ |
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IESemParseConfig( |
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name=f"{dataset}_{language}", |
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language=language, |
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dataset = dataset, |
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version=datasets.Version("1.0.0", ""), |
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description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset", |
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) |
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for language, dataset in zip(_LANGUAGES, _DATASETS) |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"premise": datasets.Value("string"), |
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"hypothesis": datasets.Value("string"), |
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"label": datasets.ClassLabel(names=["entailment", "neutral", "contradiction"]), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage="https://github.com/divyanshuaggarwal/IE-SemParse", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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urls_to_download = self.config._URLS |
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downloaded_file = dl_manager.download_and_extract(urls_to_download)[0] |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"split_key": "train", |
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"file_path": downloaded_file, |
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"data_format": "IE-SemParse" |
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} |
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, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"split_key": "test", |
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"files": downloaded_file, |
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"data_format": "IE-SemParse" |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"split_key": "val", |
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"files": downloaded_file, |
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"data_format": "IE-SemParse" |
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}, |
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), |
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] |
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def _generate_examples(self, data_format, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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with open(filepath, "r") as f: |
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data = json.load(f) |
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data = data[list(data.keys())[0]] |
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for idx, row in enumerate(data): |
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yield idx, { |
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k:v for k,v in data.items() |
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} |
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