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""" |
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""" |
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try: |
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import ir_datasets |
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except ImportError as e: |
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raise ImportError('ir-datasets package missing; `pip install ir-datasets`') |
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import datasets |
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|
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IRDS_ID = 'trec-cast/v1/2020' |
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IRDS_ENTITY_TYPES = {'queries': {'query_id': 'string', 'raw_utterance': 'string', 'automatic_rewritten_utterance': 'string', 'manual_rewritten_utterance': 'string', 'manual_canonical_result_id': 'string', 'topic_number': 'int64', 'turn_number': 'int64'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}} |
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|
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_CITATION = '@inproceedings{Dalton2020Cast,\n title={CAsT 2020: The Conversational Assistance Track Overview},\n author={Jeffrey Dalton and Chenyan Xiong and Jamie Callan},\n booktitle={TREC},\n year={2020}\n}' |
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|
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_DESCRIPTION = "" |
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|
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class trec_cast_v1_2020(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}), |
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homepage=f"https://ir-datasets.com/trec-cast#trec-cast/v1/2020", |
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citation=_CITATION, |
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) |
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|
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def _split_generators(self, dl_manager): |
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return [datasets.SplitGenerator(name=self.config.name)] |
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|
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def _generate_examples(self): |
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dataset = ir_datasets.load(IRDS_ID) |
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for i, item in enumerate(getattr(dataset, self.config.name)): |
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key = i |
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if self.config.name == 'docs': |
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key = item.doc_id |
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elif self.config.name == 'queries': |
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key = item.query_id |
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yield key, item._asdict() |
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|
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def as_dataset(self, split=None, *args, **kwargs): |
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split = self.config.name |
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return super().as_dataset(split, *args, **kwargs) |
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|
