mlsanityData to 7 Oct 2026

A Span Selection Model for Semantic Role Labeling

arXiv 1810.02245 ↗First posted 4 Oct 2018cs.CLcited by 15

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Oct 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 10; 2022: 3; 2023: 1; 2024: 1.

15 papers.

Sort: