SubjQA：一个用于主观性和复习理解的数据集
SubjQA: A Dataset for Subjectivity and Review Comprehension
摘要：
主观性是无法客观观察或验证的内部意见或信念的表达，并且已被证明对于情感分析和词义消歧很重要。此外，主观性是用户生成数据的一个重要方面。尽管如此，主观性还没有被调查的情况下，这样的数据是广泛的，如在问答（QA）。因此，我们调查主观性和QA之间的关系，同时开发一个新的数据集。我们比较和对比与以前的工作的分析，并验证有关主观性的发现仍然适用于使用最近开发的NLP架构。我们发现，主观性也是一个重要的功能，在QA的情况下，虽然主观性和QA性能之间的相互作用更复杂。例如，主观问题可以或可以不与主观答案相关联。我们发布了一个基于客户评论的英语QA数据集（SubjQA），其中包含6个不同领域的问题和答案的主观性注释。
英文摘要：
Subjectivity is the expression of internal opinions or beliefs which cannot be objectively observed or verified, and has been shown to be important for sentiment analysis and word-sense disambiguation. Furthermore, subjectivity is an important aspect of user-generated data. In spite of this, subjectivity has not been investigated in contexts where such data is widespread, such as in question answering (QA). We therefore investigate the relationship between subjectivity and QA, while developing a new dataset. We compare and contrast with analyses from previous work, and verify that findings regarding subjectivity still hold when using recently developed NLP architectures. We find that subjectivity is also an important feature in the case of QA, albeit with more intricate interactions between subjectivity and QA performance. For instance, a subjective question may or may not be associated with a subjective answer. We release an English QA dataset (SubjQA) based on customer reviews, containing subjectivity annotations for questions and answer spans across 6 distinct domains.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
