2011 · 286 citations · 15 references
ComputingComputer ScienceComputational LinguisticsNatural Language ProcessingSemanticsAnnotationLanguage ModelingLanguage ModelsLexical RelationsLexical SemanticsNamed Entity RecognitionDistributional FeaturesSemantic DependenciesSemantic ModelsSemantic Relation ExtractionSemantic Relations ExtractionSemantic Word RelationsSynonymy ExtractionWord Representation Learning
We introduce BLESS, a data set specifically designed for the evaluation of distributional semantic models. BLESS contains a set of tuples instantiating different, explicitly typed semantic relations, plus a number of controlled random tuples. It is thus possible to assess the ability of a model to detect truly related word pairs, as well as to perform in-depth analyses of the types of semantic relations that a model favors. We discuss the motivations for BLESS, describe its construction and structure, and present examples of its usage in the evaluation of distributional semantic models. 1
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