from __future__ import absolute_import, division, print_function import datasets _CITATION = """\ @misc{Wannaphong Phatthiyaphaibun_2019, title={wannaphongcom/thai-ner: ThaiNER 1.3}, url={https://zenodo.org/record/3550546}, DOI={10.5281/ZENODO.3550546}, abstractNote={Thai Named Entity Recognition}, publisher={Zenodo}, author={Wannaphong Phatthiyaphaibun}, year={2019}, month={Nov} } """ _LICENSE = "CC-BY 3.0" _DESCRIPTION = """\ ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence [unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by [Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/). It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp). The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/)) for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/). The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`. [@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset. """ class ThaiNerConfig(datasets.BuilderConfig): """BuilderConfig for ThaiNer.""" def __init__(self, **kwargs): """BuilderConfig for ThaiNer. Args: **kwargs: keyword arguments forwarded to super. """ super(ThaiNerConfig, self).__init__(**kwargs) class Thainer(datasets.GeneratorBasedBuilder): _DOWNLOAD_URL = "https://github.com/wannaphong/thai-ner/raw/master/model/1.3/data-pos.conll" _SENTENCE_SPLITTERS = ["", " ", "\n"] _POS_TAGS = [ "ADJ", "ADP", "ADV", "AUX", "CCONJ", "DET", "NOUN", "NUM", "PART", "PRON", "PROPN", "PUNCT", "SCONJ", "VERB", ] _NER_TAGS = [ "B-DATE", "B-EMAIL", "B-LAW", "B-LEN", "B-LOCATION", "B-MONEY", "B-ORGANIZATION", "B-PERCENT", "B-PERSON", "B-PHONE", "B-TIME", "B-URL", "B-ZIP", "B-ไม่ยืนยัน", "I-DATE", "I-EMAIL", "I-LAW", "I-LEN", "I-LOCATION", "I-MONEY", "I-ORGANIZATION", "I-PERCENT", "I-PERSON", "I-PHONE", "I-TIME", "I-URL", "I-ไม่ยืนยัน", "O", ] BUILDER_CONFIGS = [ ThaiNerConfig( name="thainer", version=datasets.Version("1.3.0"), description="Thai Named Entity Recognition for PyThaiNLP (6,456 sentences)", ), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("int32"), "tokens": datasets.Sequence(datasets.Value("string")), "pos_tags": datasets.Sequence(datasets.features.ClassLabel(names=self._POS_TAGS)), "ner_tags": datasets.Sequence(datasets.features.ClassLabel(names=self._NER_TAGS)), } ), supervised_keys=None, homepage="https://github.com/wannaphong/thai-ner/", citation=_CITATION, license=_LICENSE, ) def _split_generators(self, dl_manager): data_path = dl_manager.download_and_extract(self._DOWNLOAD_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_path}, ), ] def _generate_examples(self, filepath): with open(filepath, encoding="utf-8") as f: guid = 0 tokens = [] pos_tags = [] ner_tags = [] for line in f: if line in self._SENTENCE_SPLITTERS: if tokens: yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, "ner_tags": ner_tags, } guid += 1 tokens = [] pos_tags = [] ner_tags = [] else: # thainer tokens are tab separated splits = line.split("\t") # replace junk ner tags ner_tag = splits[2] if splits[2] in self._NER_TAGS else "O" tokens.append(splits[0]) pos_tags.append(splits[1]) ner_tags.append(ner_tag.rstrip()) # last example yield guid, { "id": str(guid), "tokens": tokens, "pos_tags": pos_tags, "ner_tags": ner_tags, }