Improving Tagging Performance by Using Voting Taggers

TL;DR

This paper introduces a bootstrapping approach that leverages the agreement of two POS taggers to improve tagging accuracy and develop annotated corpora for resource-scarce languages, demonstrated on Spanish.

Contribution

It proposes a novel collaborative voting method for POS tagging that enhances accuracy and aids corpus creation in low-resource language settings.

Findings

Higher accuracy in agreed-upon tags

Effective corpus development for Spanish

Improved tagging performance through voting

Abstract

We present a bootstrapping method to develop an annotated corpus, which is specially useful for languages with few available resources. The method is being applied to develop a corpus of Spanish of over 5Mw. The method consists on taking advantage of the collaboration of two different POS taggers. The cases in which both taggers agree present a higher accuracy and are used to retrain the taggers.