XLING: Matching Query Sentences to a Parallel Corpus using Topic Models for Word Sense Disambiguation
Liling Tan, Francis T. Bond · 2013
This paper describes the XLING system participation in SemEval-2013 Crosslingual Word Sense Disambiguation task. The XLING system introduces a novel approach to skip the sense disambiguation step by matching query sentences to sentences in a parallel corpus using topic models; it returns the word alignments as the translation for the target polysemous words. Although, the topic-model base matching underperformed, the matching approach showed potential in the simple cosine-based surface similarity matching.