Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Size:
1M - 10M
ArXiv:
License:
Update files from the datasets library (from 1.16.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.16.0
- wikiann.py +31 -28
wikiann.py
CHANGED
@@ -326,24 +326,24 @@ class Wikiann(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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wikiann_dl_dir = dl_manager.download_and_extract(_DATA_URL)
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lang = self.config.name
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-
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return [
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath":
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath":
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),
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"filepath":
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),
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]
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-
def _generate_examples(self, filepath):
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"""Reads line by line format of the NER dataset and generates examples.
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Input Format:
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en:rick B-PER
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@@ -365,27 +365,30 @@ class Wikiann(datasets.GeneratorBasedBuilder):
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Examples with the format listed above.
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"""
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guid_index = 1
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splits = line.split("\t")
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# strip out en: prefix
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langs.append(splits[0].split(":")[0])
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tokens.append(":".join(splits[0].split(":")[1:]))
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if len(splits) > 1:
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ner_tags.append(splits[-1].replace("\n", ""))
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else:
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#
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def _split_generators(self, dl_manager):
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wikiann_dl_dir = dl_manager.download_and_extract(_DATA_URL)
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lang = self.config.name
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+
lang_archive = os.path.join(wikiann_dl_dir, lang + ".tar.gz")
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return [
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath": "dev", "files": dl_manager.iter_archive(lang_archive)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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+
gen_kwargs={"filepath": "test", "files": dl_manager.iter_archive(lang_archive)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={"filepath": "train", "files": dl_manager.iter_archive(lang_archive)},
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),
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]
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+
def _generate_examples(self, filepath, files):
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"""Reads line by line format of the NER dataset and generates examples.
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Input Format:
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en:rick B-PER
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Examples with the format listed above.
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"""
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guid_index = 1
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for path, f in files:
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if path == filepath:
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tokens = []
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ner_tags = []
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langs = []
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for line in f:
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line = line.decode("utf-8")
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if line == "" or line == "\n":
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if tokens:
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spans = self._get_spans(tokens, ner_tags)
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yield guid_index, {"tokens": tokens, "ner_tags": ner_tags, "langs": langs, "spans": spans}
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guid_index += 1
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tokens = []
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ner_tags = []
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langs = []
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else:
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# wikiann data is tab separated
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splits = line.split("\t")
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# strip out en: prefix
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langs.append(splits[0].split(":")[0])
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tokens.append(":".join(splits[0].split(":")[1:]))
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if len(splits) > 1:
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ner_tags.append(splits[-1].replace("\n", ""))
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else:
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# examples have no label in test set
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ner_tags.append("O")
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break
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