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id_wsd.py
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import os
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from pathlib import Path
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from typing import Dict, List, Tuple
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from
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from
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import datasets
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import json
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from
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_CITATION = """\
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@inproceedings{mahendra-etal-2018-cross,
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_LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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_LOCAL = False
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_DATASETNAME = "
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_DESCRIPTION = """\
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Word Sense Disambiguation (WSD) is a task to determine the correct sense of an ambiguous word.
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_SOURCE_VERSION = "1.0.0"
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-
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_LABELS = [
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{
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class IndonesianWSD(datasets.GeneratorBasedBuilder):
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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BUILDER_CONFIGS = [
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name="
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version=SOURCE_VERSION,
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description="Indonesian WSD source schema",
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schema="source",
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subset_id="
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),
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name="
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version=
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description="Indonesian WSD Nusantara schema",
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schema="
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subset_id="
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),
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]
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}
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)
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elif self.config.schema == "
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features = schemas.text2text_features
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return datasets.DatasetInfo(
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yield key, example
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key+=1
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elif self.config.schema == "
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key = 0
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for each_data in data:
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example = {
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import os
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from pathlib import Path
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from typing import Dict, List, Tuple
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from seacrowd.utils.constants import Tasks
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from seacrowd.utils import schemas
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import datasets
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import json
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from seacrowd.utils.configs import SEACrowdConfig
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_CITATION = """\
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@inproceedings{mahendra-etal-2018-cross,
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_LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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_LOCAL = False
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_DATASETNAME = "id_wsd"
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_DESCRIPTION = """\
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Word Sense Disambiguation (WSD) is a task to determine the correct sense of an ambiguous word.
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_SOURCE_VERSION = "1.0.0"
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_SEACROWD_VERSION = "2024.06.20"
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_LABELS = [
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{
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class IndonesianWSD(datasets.GeneratorBasedBuilder):
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
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BUILDER_CONFIGS = [
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SEACrowdConfig(
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name="id_wsd_source",
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version=SOURCE_VERSION,
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description="Indonesian WSD source schema",
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schema="source",
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subset_id="id_wsd",
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),
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SEACrowdConfig(
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name="id_wsd_seacrowd_t2t",
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version=SEACROWD_VERSION,
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description="Indonesian WSD Nusantara schema",
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schema="seacrowd_t2t",
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subset_id="id_wsd",
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),
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]
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}
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)
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elif self.config.schema == "seacrowd_t2t":
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features = schemas.text2text_features
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return datasets.DatasetInfo(
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yield key, example
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key+=1
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elif self.config.schema == "seacrowd_t2t":
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key = 0
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for each_data in data:
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example = {
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