Paper Info
Title
Attentive Semantic Role Labeling with Boundary Indicator.
Abstract
The goal of semantic role labeling (SRL) is to discover the predicate-argument structure of a sentence, which plays a critical role in deep processing of natural language. This paper introduces simple yet effective auxiliary tags for dependency-based SRL to enhance a syntax-agnostic model with multi-hop self-attention. Our syntax-agnostic model achieves competitive performance with state-of-the-art models on the CoNLL-2009 benchmarks both for English and Chinese.
Year
Venue
Field
2018
arXiv: Computation and Language
Computer science,Natural language,Natural language processing,Artificial intelligence,Sentence,Semantic role labeling
DocType
Volume
Citations 
Journal
abs/1809.02796
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Zhuosheng Zhang15714.93
Shexia He2213.99
Zuchao Li33512.61
Hai Zhao4960113.64