Authors: Walid S. Saba
Addresses: American Institutes for Research, 1000 Thomas Jefferson Street, NW, Washington, DC 20007, USA
Abstract: Over two decades ago, a |quiet revolution| overwhelmingly replaced knowledge-based approaches in natural language processing (NLP) by quantitative (e.g., statistical, corpus-based, machine learning) methods. Although it is our firm belief that purely quantitative approaches cannot be the only paradigm for NLP, dissatisfaction with purely engineering approaches to the construction of large knowledge bases for NLP are somewhat justified. In this paper we hope to demonstrate that both trends are partly misguided and that the time has come to enrich logical semantics with an ontological structure that reflects our commonsense view of the world and the way we talk about in ordinary language. In this paper it will be demonstrated that assuming such an ontological structure a number of challenges in the semantics of natural language (e.g., metonymy, intensionality, copredication, nominal compounds, etc.) can be properly and uniformly addressed.
Keywords: ontology; compositional semantics; commonsense knowledge; reasoning; natural language processing; NLP; metonymy; intensionality; copredication; nominal compounds.
International Journal of Reasoning-based Intelligent Systems, 2010 Vol.2 No.1, pp.36 - 50
Published online: 02 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article