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Conference Papers Year : 2016

Neural Greedy Constituent Parsing with Dynamic Oracles


Dynamic oracle training has shown substantial improvements for dependency parsing in various settings, but has not been explored for constituent parsing. The present article introduces a dynamic oracle for transition-based constituent parsing. Experiments on the 9 languages of the SPMRL dataset show that a neural greedy parser with morphological features , trained with a dynamic oracle, leads to accuracies comparable with the best non-reranking and non-ensemble parsers.


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hal-01353734 , version 1 (17-08-2016)


  • HAL Id : hal-01353734 , version 1


Maximin Coavoux, Benoît Crabbé. Neural Greedy Constituent Parsing with Dynamic Oracles. Association for Computational Linguistics (ACL), 2016, Berlin, Germany. ⟨hal-01353734⟩
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