LREC 2006 - Proceedings sorted by papers

Title	Reducing the Granularity of a Computational Lexicon via an Automatic Mapping to a Coarse-Grained Sense Inventory
Authors	R. Navigli
Abstract	WordNet is the reference sense inventory of most of the current Word Sense Disambiguation systems. Unfortunately, it encodes too fine-grained distinctions, making it difficult even for humans to solve the ambiguity of words in context. In this paper, we present a method for reducing the granularity of the WordNet sense inventory based on the mapping to a manually crafted dictionary encoding sense groups, namely the Oxford Dictionary of English. We assess the quality of the mapping and discuss the potential of the method.
Keywords	sense clustering, sense mapping, word sense disambiguation
Full paper	Reducing the Granularity of a Computational Lexicon via an Automatic Mapping to a Coarse-Grained Sense Inventory

Title

Reducing the Granularity of a Computational Lexicon via an Automatic Mapping to a Coarse-Grained Sense Inventory

Authors

R. Navigli

Abstract

WordNet is the reference sense inventory of most of the current Word Sense Disambiguation systems. Unfortunately, it encodes too fine-grained distinctions, making it difficult even for humans to solve the ambiguity of words in context. In this paper, we present a method for reducing the granularity of the WordNet sense inventory based on the mapping to a manually crafted dictionary encoding sense groups, namely the Oxford Dictionary of English. We assess the quality of the mapping and discuss the potential of the method.

Keywords

sense clustering, sense mapping, word sense disambiguation

Full paper

Reducing the Granularity of a Computational Lexicon via an Automatic Mapping to a Coarse-Grained Sense Inventory