Datasets:
update descriptions
Browse files- zero_scrolls.py +3 -3
zero_scrolls.py
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@@ -36,7 +36,7 @@ https://scrolls-benchmark.com/
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"""
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_SUMM_SCREEN_DESCRIPTION = """
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SummScreenFD (Chen et al.,
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Given a transcript of a specific episode, the goal is to produce the episode's recap.
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The original dataset is divided into two complementary subsets, based on the source of its community contributed transcripts.
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For SCROLLS, we use the ForeverDreaming (FD) subset, as it incorporates 88 different shows,
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@@ -57,7 +57,7 @@ Annotators were tasked with writing queries about the broad contents of the meet
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while ensuring that the relevant text for answering each query spans at least 200 words or 10 turns."""
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_NARRATIVE_QA_DESCRIPTION = """
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NarrativeQA (Kočiský et al.,
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Annotators were given summaries of the books and scripts obtained from Wikipedia, and asked to generate question-answer pairs,
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resulting in about 30 questions and answers for each of the 1,567 books and scripts.
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They were encouraged to use their own words rather then copying, and avoid asking yes/no questions or ones about the cast.
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@@ -96,7 +96,7 @@ Given 50 hotel reviews (without their ratings) from the Space dataset (Angelidis
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"""
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_BOOK_SUM_DESCRIPTION = """
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BookSumSort is a new task based on the BookSum dataset (Kry ́sci ́nski et al.,
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Given a shuffled list of chapter summaries, the task is to reorder them according to the original order of summaries in BookSum.
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"""
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"""
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_SUMM_SCREEN_DESCRIPTION = """
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SummScreenFD (Chen et al., 2022) is a summarization dataset in the domain of TV shows (e.g. Friends, Game of Thrones).
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Given a transcript of a specific episode, the goal is to produce the episode's recap.
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The original dataset is divided into two complementary subsets, based on the source of its community contributed transcripts.
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For SCROLLS, we use the ForeverDreaming (FD) subset, as it incorporates 88 different shows,
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while ensuring that the relevant text for answering each query spans at least 200 words or 10 turns."""
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_NARRATIVE_QA_DESCRIPTION = """
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NarrativeQA (Kočiský et al., 2018) is an established question answering dataset over entire books from Project Gutenberg and movie scripts from different websites.
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Annotators were given summaries of the books and scripts obtained from Wikipedia, and asked to generate question-answer pairs,
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resulting in about 30 questions and answers for each of the 1,567 books and scripts.
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They were encouraged to use their own words rather then copying, and avoid asking yes/no questions or ones about the cast.
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"""
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_BOOK_SUM_DESCRIPTION = """
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BookSumSort is a new task based on the BookSum dataset (Kry ́sci ́nski et al., 2022), which contains summaries of chapters (or parts) of novels, plays, and long poems from various sources.
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Given a shuffled list of chapter summaries, the task is to reorder them according to the original order of summaries in BookSum.
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"""
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