Universal knowledge engines for lexical semantic creativity in humans and machines

点击翻译按钮获取中文摘要

This proposed research investigates knowledge structures that are shared in the lexicons across the world's languages and thereby aims to develop universal knowledge engines that will enhance machine interpretation of human languages.A key aspect that distinguishes human language users from artificial natural language systems is our ability to interpret and create novel word usages, and this creative character is reflected in the lexical semantic structures of the world's languages. This phenomenon, known as word meaning extension, poses significant challenges for machine understanding of the most fundamental units of natural languages: words. This collaborative research program will launch a new effort in bridging the gap between humans and machines in lexical semantic creativity, by taking two main steps. 1) We will characterize at a large scale knowledge representations in word meaning extension that are shared across the world's languages and through child language acquisition, drawing data and resources from a variety of publicly accessible venues including cross-linguistic databases, psychological experiments, and deep learning models. 2) We will develop new methodologies that harness and integrate different knowledge modalities toward constructing universal knowledge engines to support the flexible and adaptive interpretation and inference of novel word meanings across languages.