English speech verbs' meaning potential for natural language processing

Abstract

Word sense ambiguity and meaning potential can be quite challenging for Natural Language Processing (NLP) tasks. The complex relationship between vocabulary and meanings makes natural language processing difficult to achieve accuracy in machine translation or text generation. This research focuses on speech verbs’ forms and meanings in terms of a semantic network for natural language processing. We find that sense distinctions can be conducted systemically and accurately through semantic network analyses. It will help automated word sense disambiguity and provide an effective method for NLP applications.