Tracking the Lexical Zeitgeist with WordNet and Wikipedia

Most new words, or neologisms, bubble beneath the surface of widespread usage for some time, perhaps even years, before gaining acceptance in conventional print dictionaries [1]. A shorter, yet still significant, delay is also evident in the life-cycle of NLP-oriented lexical resources like WordNet [2]. A more topical lexical resource is Wikipedia [3], an open-source community-maintained encyclopedia whose headwords reflect the many new words that gain recognition in a particular linguistic sub-culture. In this paper we describe the principles behind Zeitgeist, a system for dynamic lexicon growth that harvests and semantically analyses new lexical forms from Wikipedia, to automatically enrich WordNet as these new word forms are minted. Zeitgeist demonstrates good results for composite words that exhibit a complex morphemic structure, such as portmanteau words and formal blends [4, 5].

• Type: Conference
• Year: 2006
• Where: ECAI
• Authors: Tony Veale
• Keywords: Artificial Intelligence, ECAI 2006, Lexical Resource, NLP-oriented Lexical Resources, Topical Lexical Resource