ITR: Semantically Tractable Questions: Theory and Implementation

理解任意的自然语言句子被广泛认为是非常具有挑战性的。但是理解诸如“意大利的首都是什么？”或者“西雅图哪些中餐馆周日营业？”即使对于一台机器来说，这似乎也很简单。虽然自然语言句子可能是微妙的、复杂的、充满歧义的，但它们也可以是简单的、直接的和清晰的。本项目通过识别在定义良好的意义上“容易理解”的问题类别，将这种直觉形式化。人们不愿意用可靠和可预测的用户界面来换取智能但不可靠的用户界面。为了满足用户，自然语言接口（nli）不应该经常误解他们的问题，如果有的话。因此，这个研究项目有三个组成部分。首先，它引入了一个理论框架，通过正式定义健全和完备的属性，并确定了一类语义上可处理的自然语言问题，从而可以构建健全和完整的NLI，从而分析NLI的可靠性。其次，通过测量语义可处理问题的普遍性和测量一个健全和完整的NLI在实践中的表现，表明该理论具有实际意义。最后，该项目将框架扩展到对话系统和越来越广泛的自然语言句子类别。这项研究有可能重振nli的基础研究，并产生更广泛的社会影响，使强大的信息资源更容易为普通人提供，而不管他们的计算机科学知识如何。

Understanding arbitrary natural language sentences is widely regarded as very challenging. Yet understanding questions such as ``What is the capital of Italy?'' or ``What Chinese restaurants are open on Sunday in Seattle?'' seems straightforward even for a machine. While natural language sentences have the potential to be subtle, complex, and rife with ambiguity, they can also be simple, straight forward, and clear. This project formalizes this intuition by identifying classes of questions that are ``easy to understand'' in a well defined sense. People are unwilling to trade reliable and predictable user interfaces for intelligent but unreliable ones. To satisfy users, Natural Language Interfaces (NLIs) should not be allowed to misinterpret their questions often, if at all. Consequently, this research project has three components. First, it introduces a theoretical framework for analyzing the reliability of an NLI by formally defining the properties of soundness and completeness and identifying a class of semantically tractable natural language questions for which sound and complete NLIs can be built. Second, it is shown that the theory has practical import by measuring the prevalence of semantically tractable questions and by measuring the performance of a sound and complete NLI in practice. Finally, the project extends the framework to dialog systems and to increasingly broad classes of natural language sentences.The research has the potential to reinvigorate basic research on NLIs, and to have the broader societal impact of making powerful information resources more readily available to ordinary people regardless of their knowledge of Computer Science.