Papers with Chinese dependency parsing

2 papers
Semi-supervised Domain Adaptation for Dependency Parsing (P19-1)

Copied to clipboard

Challenge: Currently, most studies on cross-domain parsing focus on unsupervised domain adaptation . however, unsupervised approaches make limited progress due to the intrinsic difficulty of both domain adaptation and parse.
Approach: They propose a semi-supervised domain adaptation problem for Chinese dependency parsing by using newly-annotated large-scale domain-aware datasets.
Outcome: The proposed method is more effective than direct corpus concatenation and multi-task learning.
Global Transition-based Non-projective Dependency Parsing (P18-1)

Copied to clipboard

Challenge: Until recently, transition-based dependency parsers were limited to approximate inference due to their incompatibility with rich feature models.
Approach: They propose a transition-based parser with high coverage on non-projective treebanks to support non- projective parsing.
Outcome: The proposed approach is more efficient than its projective counterpart in non-projective languages.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations