Abstract
In this paper we show several experiments motivated by the hypothesis that counting the number of relationships each synset has in WordNet 2.0 is related to the senses that are the most frequent (MFS), because MFS usually has a longer gloss, more examples of usage, more relationships with other words (synonyms, hyponyms), etc. We present a comparison of finding the MFS through the relationships in a semantic network (WordNet) versus measuring only the number of characters, words and other features in the gloss of each sense. We found that counting only inbound relationships is different to counting both inbound and outbound relationships, and that second order relationships are not so helpful, despite restricting them to be of the same kind. We analyze the contribution of each different kind of relationship in a synset; and finally, we present an analysis of the different cases where our algorithm is able to find the correct sense in SemCor, being different from the MFS listed in WordNet.
We thank the support of Instituto Politécnico Nacional, and the Mexican Government (CONACyT-SNI, SIP-IPN, COFAA-IPN, and BEIFI-IPN).
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Notes
- 1.
Bidirectional count of hyponyms yields 43.20 %, being lower as the unidirectional count shown in Table 4.
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Calvo, H., Gelbukh, A. (2015). Is the Most Frequent Sense of a Word Better Connected in a Semantic Network?. In: Huang, DS., Han, K. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2015. Lecture Notes in Computer Science(), vol 9227. Springer, Cham. https://doi.org/10.1007/978-3-319-22053-6_52
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