A Methodology for Large-Scale, Disambiguated and Unbiased Lexical Knowledge Acquisition Based on Multilingual Word Alignment
Francesca Grasso, Luigi Di · Accademia University Press eBooks · 2022
In order to be concretely effective, many NLP applications require the availability of lexical resources providing varied, broadly shared, and language-unbounded lexical information. However, state-of-the-art knowledge models rarely adopt such a comprehensive and cross-lingual approach to semantics. In this paper, we propose a novel automatable methodology for knowledge modeling based on a multilingual word alignment mechanism that enhances the encoding of unbiased and naturally disambiguated lexical knowledge. Results from a simple implementation of the proposal show relevant outcomes that are not found in other resources.