CLJan 28, 2021

Syntactic Nuclei in Dependency Parsing -- A Multilingual Exploration

arXiv:2101.11959v2800 citations
Originality Incremental advance
AI Analysis

This work addresses a niche problem in computational linguistics by incrementally enhancing parsing accuracy for multilingual dependency parsing.

The paper investigated whether enriching dependency parsing models with the abstract notion of syntactic nuclei, as defined in Universal Dependencies, improves parsing accuracy. Experiments on 12 languages showed that nucleus composition yields small but significant improvements, particularly for specific dependency relations like nominal modifiers and coordination.

Standard models for syntactic dependency parsing take words to be the elementary units that enter into dependency relations. In this paper, we investigate whether there are any benefits from enriching these models with the more abstract notion of nucleus proposed by Tesnière. We do this by showing how the concept of nucleus can be defined in the framework of Universal Dependencies and how we can use composition functions to make a transition-based dependency parser aware of this concept. Experiments on 12 languages show that nucleus composition gives small but significant improvements in parsing accuracy. Further analysis reveals that the improvement mainly concerns a small number of dependency relations, including nominal modifiers, relations of coordination, main predicates, and direct objects.

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