Assessment of Pre-Trained Models Across Languages and Grammars
Alberto Muñoz-Ortiz,
David Vilares,
Carlos Gómez-Rodríguez
Abstract:We present an approach for assessing how multilingual large language models (LLMs) learn syntax in terms of multi-formalism syntactic structures. We aim to recover constituent and dependency structures by casting parsing as sequence labeling. To do so, we select a few LLMs and study them on 13 diverse UD treebanks for dependency parsing and 10 treebanks for constituent parsing. Our results show that: (i) the framework is consistent across encodings, (ii) pre-trained word vectors do not favor constituency repre… Show more
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