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""" NER dataset compiled by T-NER library https://github.com/asahi417/tner/tree/master/tner """ |
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import json |
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from itertools import chain |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """[BioNLP2004 NER dataset](https://aclanthology.org/W04-1213.pdf)""" |
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_NAME = "bionlp2" |
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_VERSION = "1.0.0" |
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_CITATION = """ |
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@inproceedings{collier-kim-2004-introduction, |
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title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}", |
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author = "Collier, Nigel and |
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Kim, Jin-Dong", |
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booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B}io{NLP})", |
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month = aug # " 28th and 29th", |
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year = "2004", |
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address = "Geneva, Switzerland", |
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publisher = "COLING", |
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url = "https://aclanthology.org/W04-1213", |
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pages = "73--78", |
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} |
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https://huggingface.co/datasets/chintagunta85/bionlp/raw/main/test_bionlp.json |
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""" |
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_HOME_PAGE = "https://huggingface.co/datasets/chintagunta85" |
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_URL = f'https://huggingface.co/datasets/chintagunta85/{_NAME}/raw/main' |
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_URLS = { |
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str(datasets.Split.TEST): [f'{_URL}/test_bionlp.json'], |
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str(datasets.Split.TRAIN): [f'{_URL}/train_bionlp.json'], |
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str(datasets.Split.VALIDATION): [f'{_URL}/valid_bionlp.json'], |
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} |
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def map_ner_tags(tlist): |
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nlist=[] |
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for indx in tlist: |
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nlist.append(custom_names.index(inv_map[indx])) |
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return nlist |
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class BioNLP2004Config(datasets.BuilderConfig): |
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"""BuilderConfig""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(BioNLP2004Config, self).__init__(**kwargs) |
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class BioNLP2004(datasets.GeneratorBasedBuilder): |
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"""Dataset.""" |
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BUILDER_CONFIGS = [ |
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BioNLP2004Config(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION), |
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] |
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def _split_generators(self, dl_manager): |
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downloaded_file = dl_manager.download_and_extract(_URLS) |
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return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]}) |
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for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]] |
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def _generate_examples(self, filepaths): |
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custom_names = ['O','B-GENE','I-GENE','B-CHEMICAL','I-CHEMICAL','B-DISEASE','I-DISEASE', |
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'B-DNA', 'I-DNA', 'B-RNA', 'I-RNA', 'B-CELL_LINE', 'I-CELL_LINE', 'B-CELL_TYPE', 'I-CELL_TYPE', |
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'B-PROTEIN', 'I-PROTEIN', 'B-SPECIES', 'I-SPECIES'] |
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pre_def = {"O": 0, "B-DNA": 1, "I-DNA": 2, "B-PROTEIN": 3, "I-PROTEIN": 4, |
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"B-CELL_TYPE": 5, "I-CELL_TYPE": 6, "B-CELL_LINE": 7, "I-CELL_LINE": 8, |
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"B-RNA": 9, "I-RNA": 10} |
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inv_map = {0: 'O', 1: 'B-DNA', 2: 'I-DNA', 3: 'B-PROTEIN', 4: 'I-PROTEIN', |
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5: 'B-CELL_TYPE', 6: 'I-CELL_TYPE', 7: 'B-CELL_LINE', 8: 'I-CELL_LINE', 9: 'B-RNA', 10: 'I-RNA'} |
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_key = 0 |
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for filepath in filepaths: |
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logger.info(f"generating examples from = {filepath}") |
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with open(filepath, encoding="utf-8") as f: |
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_list = [i for i in f.read().split('\n') if len(i) > 0] |
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for i in _list: |
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data = json.loads(i) |
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nlist = [] |
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for indx in data['ner_tags']: |
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nlist.append(custom_names.index(inv_map[indx])) |
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data['ner_tags']=nlist |
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xstr = str(_key) |
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yield xstr,{"id":xstr,"tokens":data['tokens'], "ner_tags":data['ner_tags']} |
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_key += 1 |
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def _info(self): |
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custom_names = ['O','B-GENE','I-GENE','B-CHEMICAL','I-CHEMICAL','B-DISEASE','I-DISEASE', |
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'B-DNA', 'I-DNA', 'B-RNA', 'I-RNA', 'B-CELL_LINE', 'I-CELL_LINE', 'B-CELL_TYPE', 'I-CELL_TYPE', |
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'B-PROTEIN', 'I-PROTEIN', 'B-SPECIES', 'I-SPECIES'] |
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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=custom_names |
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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=_HOME_PAGE, |
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citation=_CITATION, |
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) |
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