具有比较词和广义量词的逻辑推理
Logical Inferences with Comparatives and Generalized Quantifiers
摘要：
比较构式是自然语言推理中的一个难题，它的任务是确定文本是否包含假设。比较级在结构上是复杂的，因为它们与其他语言现象，如量词，数词和词汇反义词相互作用。在形式语义学中，有大量关于比较级和等级表达式的工作使用了度的概念。然而，一个逻辑推理系统的比较还没有得到充分的发展，用于在NLI任务。在本文中，我们提出了一个组合语义，映射各种比较结构在英语中的语义表示，通过组合范畴语法（CCG）解析器，并结合它与推理系统的基础上自动定理证明。我们评估我们的系统在三个NLI数据集，包含复杂的逻辑推理比较，广义量词和数字。我们表明，该系统优于以前的基于逻辑的系统以及最近的基于深度学习的模型。
英文摘要：
Comparative constructions pose a challenge in Natural Language Inference (NLI), which is the task of determining whether a text entails a hypothesis. Comparatives are structurally complex in that they interact with other linguistic phenomena such as quantifiers, numerals, and lexical antonyms. In formal semantics, there is a rich body of work on comparatives and gradable expressions using the notion of degree. However, a logical inference system for comparatives has not been sufficiently developed for use in the NLI task. In this paper, we present a compositional semantics that maps various comparative constructions in English to semantic representations via Combinatory Categorial Grammar (CCG) parsers and combine it with an inference system based on automated theorem proving. We evaluate our system on three NLI datasets that contain complex logical inferences with comparatives, generalized quantifiers, and numerals. We show that the system outperforms previous logic-based systems as well as recent deep learning-based models.
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。
