Headed Span-Based Projective Dependency Parsing

08/10/2021 ∙ by Songlin Yang, et al. ∙ 0

We propose a headed span-based method for projective dependency parsing. In a projective tree, the subtree rooted at each word occurs in a contiguous sequence (i.e., span) in the surface order, we call the span-headword pair headed span. In this view, a projective tree can be regarded as a collection of headed spans. It is similar to the case in constituency parsing since a constituency tree can be regarded as a collection of constituent spans. Span-based methods decompose the score of a constituency tree sorely into the score of constituent spans and use the CYK algorithm for global training and exact inference, obtaining state-of-the-art results in constituency parsing. Inspired by them, we decompose the score of a dependency tree into the score of headed spans. We use neural networks to score headed spans and design a novel O(n^3) dynamic programming algorithm to enable global training and exact inference. We evaluate our method on PTB, CTB, and UD, achieving state-of-the-art or comparable results.



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Source code of "Headed Span-Based Projective Dependency Parsing" and "Combining (second-order) graph-based and headed span-based projective dependency parsing

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