Distributional Lesk: Effective Knowledge-Based Word Sense Disambiguation
Dieke Oele, Gertjan van Noord · University of Groningen research database (University of Groningen / Centre for Information Technology) · 2017
We propose a simple, yet effective, Word Sense Disambiguation method that uses a combination of a lexical knowledge-base and embeddings. Similar to the classic Lesk algorithm, it exploits the idea that overlap between the context of a word and the definition of its senses provides information on its meaning. Instead of counting the number of words that overlap, we use embeddings to compute the similarity between the gloss of a sense and the context. Evaluation on both Dutch and English datasets shows that our method outperforms other Lesk methods and improves upon a state-of-theart knowledge-based system. Additional experiments confirm the effect of the use of glosses and indicate that our approach works well in different domains.