In spite of decades of research on word sense disambiguation (WSD), all-words general purpose WSD has remained a distant goal. Many supervised WSD systems have been built, but the...
Mitesh M. Khapra, Anup Kulkarni, Saurabh Sohoney, ...
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Knowledge plays a central role in intelligent systems. Manual knowledge acquisition is very inefficient and expensive. In this paper, we present (1) an automatic method to acquire...
Ping Chen, Wei Ding 0003, Chris Bowes, David Brown
This article focuses on Word Sense Disambiguation (WSD), which is a Natural Language Processing task that is thought to be important for many Language Technology applications, suc...