AI Magazine
WordNet: a lexical database for English
Communications of the ACM
Enriching the WordNet taxonomy with contextual knowledge acquired from text
Natural language processing and knowledge representation
Towards a standard upper ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The algebra of lexical semantics
MOL'07/09 Proceedings of the 10th and 11th Biennial conference on The mathematics of language
Elaborating a knowledge base for deep lexical semantics
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Computational Linguistics
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In the project we describe, we have taken a basic core of about 5000 synsets in WordNet that are the most frequently used, and we have categorized these into sixteen broad categories, including, for example, time, space, scalar notions, composite entities, and event structure. We have sketched out the structure of some of the underlying abstract core theories of commonsense knowledge, including those for the mentioned areas. These theories explicate the basic predicates in terms of which the most common word senses need to be defined or characterized. We are now encoding axioms that link the word senses to the core theories. This may be thought of as a kind of "advanced lexical decomposition", where the "primitives" into which words are "decomposed" are elements in coherently worked-out theories. In this paper we focus on our work on the 450 of these synsets that are concerned with events and their structure.