A Methodology for Large-Scale, Disambiguated and Unbiased Lexical Knowledge Acquisition Based on Multilingual Word Alignment

Francesca Grasso, Luigi Di Caro
2021 Italian Conference on Computational Linguistics  
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-ofthe-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
more » ... ical knowledge. Results from a simple implementation of the proposal show relevant outcomes that are not found in other resources.
dblp:conf/clic-it/GrassoC21 fatcat:pyisgjjg5bfcng267wkuqdij3q