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Disambiguating Nouns, Verbs, and Adjectives Using Automatically Acquired Selectional Preferences
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Knowledge-rich Word Sense Disambiguation rivaling supervised systems
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Automatic selectional preference acquisition for Latin verbs
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Semi-supervised WSD in selectional preferences with semantic redundancy
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Co-related verb argument selectional preferences
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TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
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SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
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Selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This papers extends previous statistical models to class-to-class preferences, and presents a model that learns selectional preferences for classes of verbs. The motivation is twofold: different senses of a verb may have different preferences, and some classes of verbs can share preferences. The model is tested on a word sense disambiguation task which uses subject-verb and object-verb relationships extracted from a small sense-disambiguated corpus.