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dipteshkanojia commited on
Commit
696ae39
1 Parent(s): d646d9b
Files changed (1) hide show
  1. HiNER-original.py +108 -0
HiNER-original.py ADDED
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+ import os
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+
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+ import datasets
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+ from typing import List
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+ import json
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+
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+ logger = datasets.logging.get_logger(__name__)
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+
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+
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+ _CITATION = """
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+ """
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+
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+ _DESCRIPTION = """
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+ This is the dataset repository for HiNER Dataset accepted to be published at LREC 2022.
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+ The dataset can help build sequence labelling models for the task Named Entity Recognitin for the Hindi language.
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+ """
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+
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+ class HiNERConfig(datasets.BuilderConfig):
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+ """BuilderConfig for HiNER Dataset."""
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+
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+ def __init__(self, **kwargs):
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+ """BuilderConfig for HiNER.
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+ Args:
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(HiNERConfig, self).__init__(**kwargs)
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+
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+
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+ class HiNERConfig(datasets.GeneratorBasedBuilder):
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+ """HiNER dataset."""
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+
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+ BUILDER_CONFIGS = [
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+ HiNERConfig(name="HiNER", version=datasets.Version("0.0.2"), description="Hindi Named Entity Recognition dataset"),
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+ ]
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+
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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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+ {
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+ "id": datasets.Value("string"),
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+ "tokens": datasets.Sequence(datasets.Value("string")),
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+ "ner_tags": datasets.Sequence(
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+ datasets.features.ClassLabel(
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+ names=[
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+ "O",
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+ "B-PERSON",
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+ "I-PERSON",
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+ "B-LOCATION",
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+ "I-LOCATION",
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+ "B-ORGANIZATION",
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+ "I-ORGANIZATION",
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+ "B-FESTIVAL",
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+ "I-FESTIVAL",
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+ "B-GAME",
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+ "I-GAME",
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+ "B-LANGUAGE",
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+ "I-LANGUAGE",
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+ "B-LITERATURE",
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+ "I-LITERATURE",
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+ "B-MISC",
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+ "I-MISC",
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+ "B-NUMEX",
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+ "I-NUMEX",
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+ "B-RELIGION",
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+ "I-RELIGION",
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+ "B-TIMEX",
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+ "I-TIMEX",
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+ ]
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+ )
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+ ),
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+ }
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+ ),
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+ supervised_keys=None,
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+ homepage="https://github.com/cfiltnlp/HiNER",
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+ citation=_CITATION,
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+ )
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+
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+ _URL = "https://github.com/cfiltnlp/HiNER-original/resolve/main/original/"
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+ _URLS = {
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+ "train": _URL + "train.json",
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+ "dev": _URL + "validation.json",
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+ "test": _URL + "test.json"
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+ }
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+
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+ def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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+ urls_to_download = self._URLS
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+ downloaded_files = dl_manager.download_and_extract(urls_to_download)
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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
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+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """This function returns the examples in the raw (text) form."""
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+ logger.info("generating examples from = %s", filepath)
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+ with open(filepath) as f:
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+ hiner = json.load(f)
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+ for object in hiner:
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+ id_ = int(object['id'])
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+ yield id_, {
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+ "id": str(id_),
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+ "tokens": object['tokens'],
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+ "pos_tags": object['pos_tags'],
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+ "ner_tags": object['ner_tags'],
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+ }