SOTAVerified

Dependency or Span, End-to-End Uniform Semantic Role Labeling

2019-01-16Code Available0· sign in to hype

Zuchao Li, Shexia He, Hai Zhao, Yiqing Zhang, Zhuosheng Zhang, Xi Zhou, Xiang Zhou

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Semantic role labeling (SRL) aims to discover the predicateargument structure of a sentence. End-to-end SRL without syntactic input has received great attention. However, most of them focus on either span-based or dependency-based semantic representation form and only show specific model optimization respectively. Meanwhile, handling these two SRL tasks uniformly was less successful. This paper presents an end-to-end model for both dependency and span SRL with a unified argument representation to deal with two different types of argument annotations in a uniform fashion. Furthermore, we jointly predict all predicates and arguments, especially including long-term ignored predicate identification subtask. Our single model achieves new state-of-the-art results on both span (CoNLL 2005, 2012) and dependency (CoNLL 2008, 2009) SRL benchmarks.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
CoNLL 2005Li et al. (2019) (Ensemble)F187.7Unverified
CoNLL 2005Li et al. (2019) + ELMoF186.3Unverified
CoNLL 2005Li et al. (2019)F183Unverified
OntoNotesLi et al.F186Unverified

Reproductions