Collocational knowledge is necessary for language generation. The problem is that collocations come in a large variety of forms. They can involve two, three or more words, these w...
We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab ...
Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...
We evaluate the accuracy of an unlexicalized statistical parser, trained on 4K treebanked sentences from balanced data and tested on the PARC DepBank. We demonstrate that a parser...
Deterministic parsing guided by treebankinduced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systemat...