Differentiating Homonymy and Polysemy in Information Retrieval

Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 403–410, Vancouver, October 2005. c⃝2005 Association for Computational Linguistics Differentiating Homonymy and Polysemy in Information Retrieval Christopher Stokoe School of Computing and Technology University of Sunderland UK christopher.stokoe@sunderland.ac.uk Abstract Recent studies into Web retrieval have shown that word sense disambiguation can increase retrieval effectiveness. How- ever, it remains unclear as to the mini- mum disambiguation accuracy required and the granularity with which one must define word sense in order to maximize these benefits. This study answers these questions using a simulation of the effects of ambiguity on information retrieval. It goes beyond previous studies by differen- tiating between homonymy and polysemy. Results show that retrieval is more sensitive to polysemy than ho- monymy and that, when resolving polysemy, accuracy as low as 55% can potentially lead to increased performance. 1 Introduction Lexical ambiguity refers to words that share the same orthography but have different meanings (word senses). It can be sub-divided into two dis- tinct types, homonymy and polysemy. Homonymy describes when two senses of a given word (or derivation) are distinct. Typically, they are sepa- rated by etymology and are therefore entirely unre- lated in meaning. One classic example (Kilgarriff, 1992) is ‘bat’ as in an airborne mammal (from the Middle English word ‘bakke’ meaning flying ro- dent) vs. ‘bat’ as in an instrument used in the game of cricket (from the Celtic for stick or cudgel). There is no underlying relationship between these two meanings which have come about independ- ently from differing root languages. Alternatively, polysemy describes where two senses of a word are related in that they share membership of a sub- suming semantic classification. Consider the word ‘mouth’ as in a part of the body vs. ‘mouth’ as in the outlet of a river. Both meanings are subsumed by a higher concept (in this case they both describe an opening). Homonymy and polysemy are differ- entiated in most dictionaries by the major (homo- nyms) and minor (polysemes) entries for a given word. Where a lexical resource is described in terms of granularity a coarse-grained approach only differentiates between homonymy whereas a fine-grained approach also considers polysemy. The use of word sense disambiguation in In- formation Retrieval (IR) has been an active field of study for the past 30 years. Despite several failures (described in Sanderson, 2000) recent studies have begun to show increased retrieval effectiveness, particularly in Web retrieval. However, two key questions remain: (1) to what accuracy must dis- ambiguation be performed in order to show in- creased retrieval effectiveness and (2) to what level of granularity should disambiguation be performed in order to maximize these gains? This study an- swers these questions by simulating the impact of ambiguity and its subsequent resolution on re- trieval effectiveness. 2 Related Work The motivation for this research is taken from re- cent studies (section 2.1) which have demonstrated increased retrieval effectiveness by accounting for word sense. The methodology is …

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