Datasets:
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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].strip() if splits[2].strip() in self._NER_TAGS else "O"
tokens.append(splits[0])
pos_tags.append(splits[1])
ner_tags.append(ner_tag)
# last example
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"pos_tags": pos_tags,
"ner_tags": ner_tags,
}
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