Upload e3c.py
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e3c.py
CHANGED
@@ -1,18 +1,19 @@
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import os
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import datasets
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from bs4 import
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from datasets import DownloadManager
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_CITATION = """\
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@report{Magnini2021,
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}
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"""
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@@ -29,14 +30,13 @@ _URL = "https://github.com/hltfbk/E3C-Corpus/archive/refs/tags/v2.0.0.zip"
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class E3CConfig(datasets.BuilderConfig):
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"""BuilderConfig for
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def __init__(self, **kwargs):
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"""BuilderConfig for
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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self.layer = kwargs.pop("layer")
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super(E3CConfig, self).__init__(**kwargs)
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@@ -44,34 +44,9 @@ class E3C(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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E3CConfig(
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name="
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version=VERSION,
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description="this is the split of the layer 1 for English of E3C dataset",
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layer="1",
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),
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E3CConfig(
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name="es",
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version=VERSION,
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description="this is the split of the layer 1 for Spanish of E3C dataset",
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layer="1",
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),
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E3CConfig(
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name="eu",
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version=VERSION,
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description="this is the split of the layer 1 for Basque of E3C dataset",
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layer="1",
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),
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E3CConfig(
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name="fr",
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version=VERSION,
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description="this is the split of the layer 1 for French of E3C dataset",
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layer="1",
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),
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E3CConfig(
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name="it",
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version=VERSION,
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description="this is the split of the layer 1 for Italian of E3C dataset",
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layer="1",
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),
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]
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@@ -118,22 +93,115 @@ class E3C(datasets.GeneratorBasedBuilder):
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"""
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url = _URL
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data_dir = dl_manager.download_and_extract(url)
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"en": "English",
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"es": "Spanish",
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"eu": "Basque",
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"fr": "French",
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"it": "Italian",
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}[self.config.name]
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return [
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datasets.SplitGenerator(
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name=
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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),
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},
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),
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@@ -190,7 +258,7 @@ class E3C(datasets.GeneratorBasedBuilder):
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"TOKENS": self.get_annotations(soup.find_all("type4:Token"), text),
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}
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def _generate_examples(self, filepath) ->
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"""Yields examples as (key, example) tuples.
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Args:
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filepath: The path to the folder containing the files to parse.
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labels[idx_token] = f"{entity_type}"
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else:
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labels[idx_token] = f"{entity_type}"
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guid += 1
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yield guid, {
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"tokens": list(map(lambda tokens: tokens[2], filtered_tokens)),
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"ner_tags": labels,
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}
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import os
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from typing import Iterator
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import datasets
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from bs4 import BeautifulSoup, ResultSet
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from datasets import DownloadManager
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_CITATION = """\
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@report{Magnini2021,
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author = {Bernardo Magnini and Begoña Altuna and Alberto Lavelli and Manuela Speranza
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and Roberto Zanoli and Fondazione Bruno Kessler},
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keywords = {Clinical data,clinical enti-ties,corpus,multilingual,temporal information},
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title = {The E3C Project:
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European Clinical Case Corpus El proyecto E3C: European Clinical Case Corpus},
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url = {https://uts.nlm.nih.gov/uts/umls/home},
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year = {2021},
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}
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"""
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class E3CConfig(datasets.BuilderConfig):
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"""BuilderConfig for NCBIDisease"""
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def __init__(self, **kwargs):
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"""BuilderConfig for NCBIDisease.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(E3CConfig, self).__init__(**kwargs)
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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E3CConfig(
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name="e3c",
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version=VERSION,
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description="this is the split of the layer 1 for English of E3C dataset",
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),
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]
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"""
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url = _URL
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data_dir = dl_manager.download_and_extract(url)
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return [
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datasets.SplitGenerator(
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name="en.layer1",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"English",
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"layer1",
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),
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},
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),
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datasets.SplitGenerator(
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name="en.layer2",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"English",
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"layer2",
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),
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},
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),
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datasets.SplitGenerator(
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name="es.layer1",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Spanish",
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"layer1",
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),
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},
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),
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datasets.SplitGenerator(
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name="es.layer2",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Spanish",
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"layer2",
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),
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},
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),
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datasets.SplitGenerator(
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name="eu.layer1",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Basque",
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"layer1",
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),
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},
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),
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datasets.SplitGenerator(
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name="eu.layer2",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Basque",
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"layer2",
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),
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},
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),
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datasets.SplitGenerator(
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name="fr.layer1",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"French",
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"layer1",
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),
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},
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),
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datasets.SplitGenerator(
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name="fr.layer2",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"French",
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"layer2",
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),
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},
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),
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datasets.SplitGenerator(
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name="it.layer1",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Italian",
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"layer1",
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),
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},
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),
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datasets.SplitGenerator(
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name="it.layer2",
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gen_kwargs={
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"filepath": os.path.join(
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data_dir,
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"E3C-Corpus-2.0.0/data_annotation",
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"Italian",
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"layer2",
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),
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},
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),
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"TOKENS": self.get_annotations(soup.find_all("type4:Token"), text),
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}
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def _generate_examples(self, filepath) -> Iterator:
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"""Yields examples as (key, example) tuples.
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Args:
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filepath: The path to the folder containing the files to parse.
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labels[idx_token] = f"{entity_type}"
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else:
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labels[idx_token] = f"{entity_type}"
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yield guid, {
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"tokens": list(map(lambda tokens: tokens[2], filtered_tokens)),
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"ner_tags": labels,
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}
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guid += 1
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