Toward a Better Localization of Princeton WordNet

TL;DR

This paper introduces a structured framework for localizing Princeton WordNet, emphasizing quality and cultural authenticity, demonstrated through the successful localization of 10,000 synsets.

Contribution

It presents a comprehensive framework for WordNet localization, addressing quality and cultural alignment, and reports practical application results.

Findings

Successful localization of 10,000 synsets

Framework improves localization quality

Addresses cultural authenticity in NLP resources

Abstract

As Princeton WordNet continues to gain significance as a semantic lexicon in Natural Language Processing, the need for its localization and for ensuring the quality of this process has become increasingly critical. Existing efforts remain limited in both scale and rigor, and there is a notable absence of studies addressing the accuracy of localization or its alignment with the cultural context of Arabic. This paper proposes a structured framework for the localization of Princeton WordNet, detailing the stages and procedures required to achieve high-quality results without compromising cultural authenticity. We further present our experience in applying this framework, reporting outcomes from the localization of 10,000 synsets.