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Word sense disambiguation is typically phrased as the task of labeling a word in context with the best-fitting sense from a sense inventory such as WordNet. While questions have o...
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 ...
Word Sense Disambiguation (WSD) is an intermediate task that serves as a means to an end defined by the application in which it is to be used. However, different applications have...
The accuracy of current word sense disambiguation (WSD) systems is affected by the fine-grained sense inventory of WordNet as well as a lack of training examples. Using the WSD ex...
Given the recent trend to evaluate the performance of word sense disambiguation systems in a more application-oriented set-up, we report on the construction of a multilingual benc...