Transactions of the Association for Computational Linguistics · 2014 · 747 citations · 65 references
ComputingComputer ScienceLinguisticsComputational LinguisticsNatural Language ProcessingSemanticsLexical RelationsMultilingual Natural Language ProcessingMultilingual ProcessingNamed Entity RecognitionSemantic NetworksWord Sense DisambiguationEntity LinkingGraph-based Word Sense DisambiguationLexical AmbiguityLexical Ambiguity ResolutionNamed Entity LinkingSemantic CoherenceSubgraph IsomorphismSubgraph Mining
Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental respect: in EL the textual mention can be linked to a named entity which may or may not contain the exact mention, while in WSD there is a perfect match between the word form (better, its lemma) and a suitable word sense. In this paper we present Babelfy, a unified graph-based approach to EL and WSD based on a loose identification of candidate meanings coupled with a densest subgraph heuristic which selects high-coherence semantic interpretations. Our experiments show state-of-the-art performances on both tasks on 6 different datasets, including a multilingual setting. Babelfy is online at http://babelfy.org
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Collective dynamics of ‘small-world’ networks
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Automatic sense disambiguation using machine readable dictionaries
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