Papers › Left-to-Right Dependency Parsing with Pointer Networks
Left-to-Right Dependency Parsing with Pointer Networks
Daniel Fern{\'a}ndez-Gonz{\'a}lez, Carlos G{\'o}mez-Rodr{\'\i}guez
We propose a novel transition-based algorithm that straightforwardly parses sentences from left to right by building n attachments, with n being the length of the input sentence. Similarly to the recent stack-pointer parser by Ma et al. (2018), we use the pointer network framework that, given a word, can directly point to a position from the sentence. However, our left-to-right approach is simpler than the original top-down stack-pointer parser (not requiring a stack) and reduces transition sequence length in half, from 2n-1 actions to n. This results in a quadratic non-projective parser that runs twice as fast as the original while achieving the best accuracy to date on the English PTB dataset (96.04{\%} UAS, 94.43{\%} LAS) among fully-supervised single-model dependency parsers, and improves over the former top-down transition system in the majority of languages tested.
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