Multi-layer Biaffine Model for Neural Dependency Parsing
The biaffine model is a strong and efficient model for graph-based dependency parsing. However, previous work only used the biaffine method in single-layer form. In this paper, we propose a multi-layer biaffine model for neural dependency parsing. In this model, we modify the biaffine method so that it can be utilized in multi-layer form. We evaluate our model on PTB and CTB and show our model achieves state-of-the-art results on both datasets. Further experiments show the benefits of introducing multi-layer form into the biaffine method with low efficiency loss.
Code (0)
등록된 구현이 없습니다.
Tasks
Dependency ParsingFormSimilar Papers 제목 키워드 기반
Multi-Layer Pseudo-Siamese Biaffine Model for Dependency Parsing
Biaffine method is a strong and efficient method for graph-based dependency parsing. However, previous work only used the biaffine method at the end of the dependency parser as a scorer, and its application in multi-laye…
ARCDependency ParsingFormEnd-to-End Argument Mining as Biaffine Dependency Parsing
Non-neural approaches to argument mining (AM) are often pipelined and require heavy feature-engineering. In this paper, we propose a neural end-to-end approach to AM which is based on dependency parsing, in contrast to t…
Argument MiningDependency ParsingFeature EngineeringRelation+1Dependency Parsing is More Parameter-Efficient with Normalization
Dependency parsing is the task of inferring natural language structure, often approached by modeling word interactions via attention through biaffine scoring. This mechanism works like self-attention in Transformers, whe…
Dependency ParsingSentenceJBNU at MRP 2019: Multi-level Biaffine Attention for Semantic Dependency Parsing
This paper describes Jeonbuk National University (JBNU){'}s system for the 2019 shared task on Cross-Framework Meaning Representation Parsing (MRP 2019) at the Conference on Computational Natural Language Learning. Of th…
DecoderDependency ParsingSemantic Dependency ParsingSentenceEfficient Second-Order TreeCRF for Neural Dependency Parsing
In the deep learning (DL) era, parsing models are extremely simplified with little hurt on performance, thanks to the remarkable capability of multi-layer BiLSTMs in context representation. As the most popular graph-base…
ARCChinese Dependency ParsingDependency Parsing