论文标题
关系/以实体为中心的阅读理解
Relation/Entity-Centric Reading Comprehension
论文作者
论文摘要
构建理解人类语言的机器是人工智能中最难以捉摸，最长期的挑战之一。本论文通过阅读理解的研究解决了这一挑战，重点是理解实体及其关系。更具体地说，我们专注于回答旨在衡量阅读理解的任务。我们专注于实体和关系，因为它们通常用于代表自然语言的语义。
Constructing a machine that understands human language is one of the most elusive and long-standing challenges in artificial intelligence. This thesis addresses this challenge through studies of reading comprehension with a focus on understanding entities and their relationships. More specifically, we focus on question answering tasks designed to measure reading comprehension. We focus on entities and relations because they are typically used to represent the semantics of natural language.
