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import os |
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import xml.etree.ElementTree as ET |
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import datasets |
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from datasets import GeneratorBasedBuilder, DatasetInfo, Split, SplitGenerator, Features, Value, Sequence |
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_BASE_URL = "https://drive.google.com/uc?export=download&id=15YklLKAaNXomOAkEAMmLAIIFhS9o-ywS" |
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class UzABSA(GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="uzabsa", version=VERSION, |
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description="UZABSA dataset for sentiment analysis in Uzbek"), |
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] |
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def _info(self): |
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return DatasetInfo( |
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features=Features({ |
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"sentence_id": Value("string"), |
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"text": Value("string"), |
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"aspect_terms": Sequence({ |
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"term": Value("string"), |
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"polarity": Value("string"), |
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"from": Value("int32"), |
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"to": Value("int32"), |
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}), |
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"aspect_categories": Sequence({ |
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"category": Value("string"), |
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"polarity": Value("string"), |
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}), |
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}) |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_file = dl_manager.download_and_extract(_BASE_URL) |
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return [ |
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SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": downloaded_file}), |
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] |
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def _generate_examples(self, filepath): |
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tree = ET.parse(filepath) |
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root = tree.getroot() |
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for sentence in root.findall("sentence"): |
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sentence_id = sentence.get("ID") |
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text = sentence.find("text").text |
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aspect_terms = [] |
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for aspect_term in sentence.findall("./aspectTerms/aspectTerm"): |
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aspect_terms.append({ |
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"term": aspect_term.get("term"), |
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"polarity": aspect_term.get("polarity"), |
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"from": int(aspect_term.get("from")), |
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"to": int(aspect_term.get("to")), |
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}) |
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aspect_categories = [] |
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for aspect_category in sentence.findall("./aspectCategories/aspectCategory"): |
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aspect_categories.append({ |
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"category": aspect_category.get("category"), |
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"polarity": aspect_category.get("polarity"), |
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}) |
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yield sentence_id, { |
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"sentence_id": sentence_id, |
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"text": text, |
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"aspect_terms": aspect_terms, |
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"aspect_categories": aspect_categories, |
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} |
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