论文标题
“那是什么意思？”一种与解析器无关的交互式方法，用于增强文本到SQL
"What Do You Mean by That?" A Parser-Independent Interactive Approach for Enhancing Text-to-SQL
论文作者
论文摘要
在与数据库系统的自然语言接口中，文本到SQL技术允许用户通过使用自然语言问题查询数据库。尽管最近在这一领域取得了重大进展，但大多数解析器被部署在实际系统中时可能会缺乏。主要原因是很难完全理解用户的自然语言问题。在本文中，我们将人类包括在循环中，并提出一种新颖的解析器独立的交互式方法（PIIA），该方法使用多选择问题与用户互动，并且可以轻松与任意解析器一起使用。实验是在两个跨域数据集（Wikisql和更复杂的蜘蛛）上进行的，并具有五个最先进的解析器。这些表明，PIIA能够通过使用模拟和人类评估来通过有限的相互作用转弯来增强文本到SQL的性能。
In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions. Though significant progress in this area has been made recently, most parsers may fall short when they are deployed in real systems. One main reason stems from the difficulty of fully understanding the users' natural language questions. In this paper, we include human in the loop and present a novel parser-independent interactive approach (PIIA) that interacts with users using multi-choice questions and can easily work with arbitrary parsers. Experiments were conducted on two cross-domain datasets, the WikiSQL and the more complex Spider, with five state-of-the-art parsers. These demonstrated that PIIA is capable of enhancing the text-to-SQL performance with limited interaction turns by using both simulation and human evaluation.
