import json import datasets import os _CITATION = """\\ @article{shahshahani2018peyma, title={PEYMA: A Tagged Corpus for Persian Named Entities}, author={Mahsa Sadat Shahshahani and Mahdi Mohseni and Azadeh Shakery and Heshaam Faili}, year=2018, journal={ArXiv}, volume={abs/1801.09936} } """ _DESCRIPTION = """PEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.""" _DATA_PATH = { 'train': os.path.join('data', 'train.txt'), 'test': os.path.join('data', 'test.txt'), 'val': os.path.join('data', 'dev.txt') } class PEYMAConfig(datasets.BuilderConfig): """BuilderConfig for PEYMA.""" def __init__(self, **kwargs): super(PEYMAConfig, self).__init__(**kwargs) class PEYMA(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ PEYMAConfig(name="PEYMA", version=datasets.Version("1.0.0"), description="persian ner dataset"), ] def _info(self): return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # datasets.features.FeatureConnectors features=datasets.Features( { "tokens": datasets.Sequence(datasets.Value("string")), "tags": datasets.Sequence( datasets.ClassLabel( names=[ "O", "B_DAT", "B_LOC", "B_MON", "B_ORG", "B_PCT", "B_PER", "B_TIM", "I_DAT", "I_LOC", "I_MON", "I_ORG", "I_PCT", "I_PER", "I_TIM", ] ) ), } ), supervised_keys=('tokens', 'tags'), # Homepage of the dataset for documentation homepage="https://hooshvare.github.io/docs/datasets/ner#peyma", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={ "filepath": dl_manager.download_and_extract(_DATA_PATH["train"]), "split": "train", },), datasets.SplitGenerator( name=datasets.Split.TEST, # These kwargs will be passed to _generate_examples gen_kwargs={ "filepath": dl_manager.download_and_extract(_DATA_PATH["test"]), "split": "test"},), datasets.SplitGenerator( name=datasets.Split.VALIDATION, # These kwargs will be passed to _generate_examples gen_kwargs={ "filepath": dl_manager.download_and_extract(_DATA_PATH["val"]), "split": "validation", }, ), ] def _generate_examples(self, filepath, split): with open(filepath, "r", encoding="utf-8") as f: id_ = 0 tokens = [] ner_labels = [] for line in f: stripped_line = line.strip(" \n") # strip away whitespaces AND new line characters if len(stripped_line) == 0: # If line is empty, it means we reached the end of a sentence. # We can yield the tokens and labels if len(tokens) > 0 and len(ner_labels) > 0: yield id_, { "tokens": tokens, "tags": ner_labels, } else: # Do not yield if tokens or ner_labels is empty # It can be the case if several empty lines are contiguous continue # Then we need to increment the _id and reset the tokens and ner_labels list id_ += 1 tokens = [] ner_labels = [] else: try: token, ner_label = line.split("|") # Retrieve token and label tokens.append(token) ner_labels.append(ner_label) except: continue