Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
Polish
Size:
1K - 10K
License:
File size: 2,799 Bytes
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# coding=utf-8
"""CEN dataset."""
import csv
import datasets
_DESCRIPTION = "CEN dataset."
_URLS = {
"train": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/train.iob",
"valid": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/valid.iob",
"test": "https://huggingface.co/datasets/clarin-knext/cen/resolve/main/data/test.iob",
}
_HOMEPAGE = "https://clarin-pl.eu/dspace/handle/11321/6"
with open('data/n82_tagset.txt', 'r') as fin:
_N82_TAGS = fin.read().split('\n')
_NER_IOB_TAGS = ['O']
for tag in _N82_TAGS:
_NER_IOB_TAGS.extend([f'B-{tag}', f'I-{tag}'])
class CenDataset(datasets.GeneratorBasedBuilder):
def _info(self) -> datasets.DatasetInfo:
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"tokens": datasets.Sequence(datasets.Value('string')),
"lemmas": datasets.Sequence(datasets.Value('string')),
"mstags": datasets.Sequence(datasets.Value('string')),
"ner": datasets.Sequence(datasets.features.ClassLabel(names=_NER_IOB_TAGS))
}
),
homepage=_HOMEPAGE
)
def _split_generators(self, dl_manager: datasets.DownloadManager):
downloaded_files = dl_manager.download_and_extract(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepath': downloaded_files['train']}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={'filepath': downloaded_files['valid']}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={'filepath': downloaded_files['test']})
]
def _generate_examples(self, filepath: str):
with open(filepath, 'r', encoding='utf-8') as fin:
reader = csv.reader(fin, delimiter='\t', quoting=csv.QUOTE_NONE)
tokens = []
lemmas = []
mstags = []
ner = []
gid = 0
for line in reader:
if not line:
yield gid, {
"tokens": tokens,
"lemmas": lemmas,
"mstags": mstags,
"ner": ner
}
gid += 1
tokens = []
lemmas = []
mstags = []
ner = []
elif len(line) == 1: # ignore --DOCSTART lines
continue
else:
tokens.append(line[0])
lemmas.append(line[1])
mstags.append(line[2])
ner.append(line[3])
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