We present Pro3Gres, a deep-syntactic, fast dependency parser that combines a handwritten competence grammar with probabilistic performance disambiguation and that has been used i...
Gerold Schneider, Kaarel Kaljurand, Fabio Rinaldi,...
We present results that show that incorporating lexical and structural semantic information is effective for word sense disambiguation. We evaluated the method by using precise in...
Takaaki Tanaka, Francis Bond, Timothy Baldwin, San...
It is possible to reduce the bulk of phrasetables for Statistical Machine Translation using a technique based on the significance testing of phrase pair co-occurrence in the para...
Howard Johnson, Joel D. Martin, George F. Foster, ...
We describe our submission to the domain adaptation track of the CoNLL07 shared task in the open class for systems using external resources. Our main finding was that it was very...
We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of p...
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki ...