You Shall Know the Most Frequent Sense by the Company it Keeps
This work addresses a semantic task for natural language processing, but it appears incremental as it builds on existing concepts to improve detection.
The paper tackled the problem of identifying the most frequent sense of polysemous words by introducing companions and most frequent translations, and showed that these methods advance the state of the art on MFS detection.
Identification of the most frequent sense of a polysemous word is an important semantic task. We introduce two concepts that can benefit MFS detection: companions, which are the most frequently co-occurring words, and the most frequent translation in a bitext. We present two novel methods that incorporate these new concepts, and show that they advance the state of the art on MFS detection.