Paper: Unsupervised Translation Sense Clustering

ACL ID N12-1095
Title Unsupervised Translation Sense Clustering
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

We propose an unsupervised method for clus- tering the translations of a word, such that the translations in each cluster share a com- mon semantic sense. Words are assigned to clusters based on their usage distribution in large monolingual and parallel corpora using the softK-Means algorithm. In addition to de- scribing our approach, we formalize the task of translation sense clustering and describe a procedure that leverages WordNet for evalu- ation. By comparing our induced clusters to reference clusters generated from WordNet, we demonstrate that our method effectively identifies sense-based translation clusters and benefits from both monolingual and parallel corpora. Finally, we describe a method for an- notating clusters with usage examples.