Word Sense Disambiguation Using English-Spanish Aligned Phrases over Comparable Corpora

TL;DR

This study explores using aligned English-Spanish phrases from comparable corpora for word sense disambiguation, achieving high precision but limited coverage, and discusses its potential and limitations.

Contribution

It introduces a bilingual phrase alignment approach for WSD and evaluates its effectiveness compared to traditional methods.

Findings

Potential precision is high at 74.3%.

Coverage is low at 2.7%.

The method is less effective due to language closeness and domain differences.

Abstract

In this paper we describe a WSD experiment based on bilingual English-Spanish comparable corpora in which individual noun phrases have been identified and aligned with their respective counterparts in the other language. The evaluation of the experiment has been carried out against SemCor. We show that, with the alignment algorithm employed, potential precision is high (74.3%), however the coverage of the method is low (2.7%), due to alignments being far less frequent than we expected. Contrary to our intuition, precision does not rise consistently with the number of alignments. The coverage is low due to several factors; there are important domain differences, and English and Spanish are too close languages for this approach to be able to discriminate efficiently between senses, rendering it unsuitable for WSD, although the method may prove more productive in machine translation.