Abstract

We present a simple and accurate span-based model for semantic role labeling (SRL). Our model directly takes into account all possible argument spans and scores them for each label. At decoding time, we greedily select higher scoring labeled spans. One advantage of our model is to allow us to design and use span-level features, that are difficult to use in token-based BIO tagging approaches. Experimental results demonstrate that our ensemble model achieves the state-of-the-art results, 87.4 F1 and 87.0 F1 on the CoNLL-2005 and 2012 datasets, respectively.

Highlights

  • Semantic Role Labeling (SRL) is a shallow semantic parsing task whose goal is to recognize the predicate-argument structure of each predicate

  • We provide a detailed description of the stacked bidirectional LSTMs (BiLSTMs) in Appendix B

  • To take advantage of it, we introduce a variant of a mixture of experts (MoE) (Shazeer et al, 2017), 3

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Summary

Introduction

Semantic Role Labeling (SRL) is a shallow semantic parsing task whose goal is to recognize the predicate-argument structure of each predicate. By using contextualized word representations, ELMo (Peters et al, 2018), our ensemble model achieves the state-of-the-art results, 87.4 F1 and 87.0 F1 on the CoNLL-2005 and 2012 datasets, respectively. Empirical analysis on these results shows that the label prediction ability of our span-based model is better than that of the CRF-based model. Another finding is that ELMo improves the model performance for span boundary identification. This section formalizes the problem and provides our span selection model

Span Selection Problem
Scoring Function
Function Fθ
Inference
Network Architecture
BiLSTM-Span Model
Ensembling
Baseline Model
Model Setup
Results
Findings
Performance for Span Boundary Identification
Performance for Label Prediction
Qualitative Analysis on Our Model
Semantic Role Labeling Tasks
BIO-based SRL Models
Span-based SRL Models
Span-based Models in Other NLP Tasks
Conclusion and Future Work
A Span-Consistent Greedy Search
B BiLSTMs
C Hyperparameters
Ensemble Model
Span-based Model

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