Structural Ambiguity and its Disambiguation in Language Model Based
Parsers: the Case of Dutch Clause Relativization
Conference on Computational Natural Language Learning (CoNLL), 2023
Abstract
This paper addresses structural ambiguity in Dutch relative clauses. By investigating the task of disambiguation by grounding, we study how the presence of a prior sentence can resolve relative clause ambiguities. We apply this method to two parsing architectures in an attempt to demystify the parsing and language model components of two present-day neural parsers. Results show that a neurosymbolic parser, based on proof nets, is more open to data bias correction than an approach based on universal dependencies, although both setups suffer from a comparable initial data bias.
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