Toward a Better Localization of Princeton WordNet
This addresses the need for high-quality, culturally aligned semantic lexicons in NLP for Arabic speakers, but it is incremental as it builds on existing localization efforts.
The paper tackles the problem of localizing Princeton WordNet for Arabic by proposing a structured framework to ensure cultural authenticity, reporting results from localizing 10,000 synsets.
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.