Joseph Z. Chang

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In recent years, state-of-the-art cross-linguistic systems have been based on parallel corpora. Nevertheless, it is difficult at times to find translations of a certain technical term or named entity even with a very large parallel corpora. In this paper, we present a new method for learning to find translations on the Web for a given term. In our approach,(More)
In this report paper, we investigate two issues facing phrase-based machine translation (MT) systems such as Moses (Koehn et al., 2007): out-of-vocabulary (OOV) words and singletons. MT systems typically ignore and directly output unknown or OOV source words into the target translation. On the other hand, for words which do not couple with their preceding(More)
In this paper, we introduce a minimally supervised method for learning to classify named-entity titles in a given encyclopedia into broad semantic categories in an existing ontology. Our main idea involves using overlapping entries in the encyclopedia and ontology and a small set of 30 handed tagged parenthetic explanations to automatically generate the(More)
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