1. Hidden-Variable Models for Discriminative Reranking.

    Hidden–Variable Models for Discriminative Reranking Terry Koo MIT CSAIL maestro@mit.edu Michael Collins MIT CSAIL mcollins@csail.mit.edu Abstract We describe a new method for the representation of NLP structures within reranking approaches. We make use of a conditional log–linear model, with hidden variables representing the assignment of lexical items to word clusters or word senses. The model learns to automatically make these assignments based on a discriminative training criterion. Trainin
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
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