Sequential Graph Dependency Parser
This addresses parsing challenges in NLP for languages with complex syntactic structures, but it is incremental as it blends existing parsing approaches.
The paper tackles non-projective dependency parsing by predicting edges incrementally without a pre-specified order, achieving near state-of-the-art results on both projective and non-projective languages.
We propose a method for non-projective dependency parsing by incrementally predicting a set of edges. Since the edges do not have a pre-specified order, we propose a set-based learning method. Our method blends graph, transition, and easy-first parsing, including a prior state of the parser as a special case. The proposed transition-based method successfully parses near the state of the art on both projective and non-projective languages, without assuming a certain parsing order.