Word Disambiguation

Semantic disambiguation depends on a process of defining the appropriate knowledge context. Recent research directions suggest a eonnectionist approach which use dictionaries, but there remain problems of scale, analysis, and …...

This paper presents a method to combine a set of unsupervised algorithms that can accurately disambiguate word senses in a large, completely untagged corpus. Al- though most of the techniques …...

We have participated in the Multilingual Chinese-English Lexical Sample Task of SemEval-2007. Our system disambiguates senses of Chinese words and finds the correct translation in English by using the web …...

This paper is an outcome of ongoing re- search and presents an unsupervised method for automatic word sense induction (WSI) and disambiguation (WSD). The induction algorithm is based on modeling …...

Modelling compositional meaning for sen- tences using empirical distributional methods has been a challenge for computational lin- guists. We implement the abstract categorical model of Coecke et al. (2010) using …...

In this paper, we present a unified model for the automatic induction of word senses from text, and the subsequent disambiguation of particular word instances using the automati- cally extracted …...

This article presents a word-sense annotation for the Balanced Corpus of Contemporary Written Japanese: a mashed-up Japanese lexi- con based on the ‘Word List by Semantic Prin- ciples’ (WLSP). The …...

Negation is an important contextual phenomenon that needs to be addressed in sentiment analysis. Next to common negation function words, such as not or none, there is also a considerably …...