This paper presents the SemEval-2013 task on multilingual Word Sense Disambiguation.
We describe our experience in producing a multilingual sense-annotated corpus for the task …

Contributive resources, such as Wikipedia, have proved to be valuable to Natural Language
Processing or multilingual Information Retrieval applications. This work focusses on …

In Word Sense Disambiguation, sense annotated corpora are often essential for evaluating
a system and also valuable in order to reach a good efficiency. Always created for a specific …

Word sense disambiguation (WSD) is a natural language processing problem that occurs at
the semantic level. It consists of determining the sense of a polysemous word that is suitable …

This work focuses on the rapid development of linguistic annotation tools for resource-poor
languages. We experiment several cross-lingual annotation projection methods using …

Word sense disambiguation is an early problem in the field of computational linguistics, and
is defined as identifying the sense (or senses) that most likely represents a word, or a …

This work focuses on the rapid development of linguistic annotation tools for low-resource
languages (languages that have no labeled training data). We experiment with several cross …

ShotgunWSD is a recent unsupervised and knowledge-based algorithm for global word
sense disambiguation (WSD). The algorithm is inspired by the Shotgun sequencing …

Abstract Word Sense Disambiguation (WSD) is a key step for many natural language
processing tasks such as information search, automatic translation, and sentiment analysis …

In this paper, we present a novel unsupervised algorithm for word sense disambiguation
(WSD) at the document level. Our algorithm is inspired by a widely-used approach in the …