Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Conditional Random Fields (CRFs) have proven to perform well on natural language processing tasks like name transliteration, concept tagging or grapheme-to-phoneme (g2p) conversio...
In this paper we present the use of a "general purpose" textual entaiment recognizer in the Answer Validation Exercise (AVE) task. Our system has been developed to learn...
Hierarchical phrase-based (HPB) translation provides a powerful mechanism to capture both short and long distance phrase reorderings. However, the phrase reorderings lack of conte...