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.
@article{arxiv.1809.02796,
title = {Attentive Semantic Role Labeling with Boundary Indicator},
author = {Zhuosheng Zhang and Shexia He and Zuchao Li and Hai Zhao},
journal= {arXiv preprint arXiv:1809.02796},
year = {2018}
}