The upv-unige-CIAOSENSO WSD system

The upv-unige-CIAOSENSO WSD System Davide Buscaldi �� � , Paolo Rosso � , Francesco Masulli � � DISI, Universit`a di Genova, Italy � DSIC, Universidad Polit´ecnica de Valencia, Spain � INFM-Genova and Dip. di Informatica, Universit`a di Pisa, Italy �� dbuscaldi, prosso � @dsic.upv.es � masulli@disi.unige.it Abstract The CIAOSENSO WSD system is based on Con- ceptual Density, WordNet Domains and frequences of WordNet senses. This paper describes the upv- unige-CIAOSENSO WSD system, we participated in the english all-word task with, and its versions used for the english lexical sample and the Word- Net gloss disambiguation tasks. In the last an ad- ditional goal was to check if the disambiguation of glosses, that has been performed during our tests on the SemCor corpus, was done properly or not. Introduction The CIAOSENSO WSD system is an unsupervised system based on Conceptual Density (Agirre and Rigau, 1995), frequencies of WordNet senses, and WordNet Domains (Magnini and Cavagli`a, 2000). Conceptual Density (CD) is a measure of the cor- relation among the sense of a given word and its context. The foundation of this measure is the Con- ceptual Distance, defined as the length of the short- est path which connects two concepts in a hierar- chical semantic net. The starting point for our work was the CD formula of Agirre and Rigau (Agirre and Rigau, 1995), which compares areas of sub- hierarchies. The noun sense disambiguation in the CIAOSENSO WSD system is performed by means of a formula combining Conceptual Density with WordNet sense frequency (Rosso et al., 2003). WordNet Domains is an extension of WordNet 1.6, developed at ITC-irst1, where each synset has been annotated with at least one domain label, selected from a set of about two hundred labels hierarchically organized (Magnini and Cavagli`a, 2000). Since the lexical resource used by the upv- unige-CIAOSENSO WSD system is WordNet 2.0 (WN2.0), it has been necessary to map the synsets of WordNet Domains from version 1.6 to the ver- sion 2.0. This has been done in a fully automated way, by using the WordNet mappings for nouns and 1Istituto per la Ricerca Scientifica e Tecnologica, Trento, Italy verbs, and by checking the similarity of synset terms and glosses for adjectives and adverbs. Some do- mains have also been assigned by hand in some cases, when necessary. 1 Noun Sense Disambiguation In our upv-unige-CIAOSENSO WSD system the noun sense disambiguation is carried out by means of the formula presented in (Rosso et al., 2003), which gave good results for the disambiguation of nouns over the SemCor corpus (precision 0.815). This formula has been derived from the original Conceptual Density formula described in (Agirre and Rigau, 1995): � �  �� �  ! #"%$'&  () �  * #"%$'&  (1) where is the synset at the top of subhierarchy,  the number of word senses falling within a subhier- archy, " the height of the subhierarchy, and #"+$,& the averaged number of hyponyms for each node (synset) in the subhierarchy. The numerator ex- …

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