Attentive Semantic Role Labeling with Boundary Indicator

2018/09/08 by Zhuosheng Zhang, Shexia He, Zhang, Zhuosheng +5
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling

paper · pdf · doi:10.48550/arxiv.1809.02796

openalex publication_date 2018/09/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Long Short-Term Memory
• A Structured Self-attentive Sentence Embedding

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