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30 lines
1.2 KiB
Python
30 lines
1.2 KiB
Python
names = [
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['1-1', 'article_recitation'],
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['1-2', 'knowledge_question_answering'],
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['2-1', 'document_proofreading'],
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['2-2', 'dispute_focus_identification'],
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['2-3', 'marital_disputes_identification'],
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['2-4', 'issue_topic_identification'],
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['2-5', 'reading_comprehension'],
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['2-6', 'named_entity_recognition'],
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['2-7', 'opinion_summarization'],
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['2-8', 'argument_mining'],
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['2-9', 'event_detection'],
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['2-10', 'trigger_word_extraction'],
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['3-1', 'fact_based_article_prediction'],
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['3-2', 'scene_based_article_prediction'],
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['3-3', 'charge_prediction'],
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['3-4', 'prison_term_prediction_wo_article'],
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['3-5', 'prison_term_prediction_w_article'],
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['3-6', 'case_analysis'],
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['3-7', 'criminal_damages_calculation'],
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['3-8', 'consultation'],
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]
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lawbench_summary_groups = []
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_lawbench_0_shot = ['lawbench-' + index + '-' + name + '-0-shot' for index, name in names]
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lawbench_summary_groups.append({'name': 'lawbench-0-shot', 'subsets': _lawbench_0_shot})
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_lawbench_1_shot = ['lawbench-' + index + '-' + name + '-1-shot' for index, name in names]
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lawbench_summary_groups.append({'name': 'lawbench-1-shot', 'subsets': _lawbench_1_shot})
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