Make word sense disambiguation in EBMT practical

In an EBMT system, we will meet the word sense disambiguation problem. The disambiguation methods used at present can't be used easily in EBMT. We propose a new method for word sense disambiguation in EBMT: it is based on a language mode of the target language. Its main idea is that a proper word sense can make the whole sentence fluent. We use a language model to measure this fluency, and use dynamic programming method to compute the proper words sense sequence in EBMT. It has the virtues of easily being used. and doesn't need extra lingual knowledge, besides, the general performance of it can be improved by using more target language resource to train. And experiment shows our method works well.