@inproceedings{wang-etal-2019-best,
title = "How to Best Use Syntax in Semantic Role Labelling",
author = "Wang, Yufei and
Johnson, Mark and
Wan, Stephen and
Sun, Yifang and
Wang, Wei",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1529",
doi = "10.18653/v1/P19-1529",
pages = "5338--5343",
abstract = "There are many different ways in which external information might be used in a NLP task. This paper investigates how external syntactic information can be used most effectively in the Semantic Role Labeling (SRL) task. We evaluate three different ways of encoding syntactic parses and three different ways of injecting them into a state-of-the-art neural ELMo-based SRL sequence labelling model. We show that using a constituency representation as input features improves performance the most, achieving a new state-of-the-art for non-ensemble SRL models on the in-domain CoNLL{'}05 and CoNLL{'}12 benchmarks.",
}
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<abstract>There are many different ways in which external information might be used in a NLP task. This paper investigates how external syntactic information can be used most effectively in the Semantic Role Labeling (SRL) task. We evaluate three different ways of encoding syntactic parses and three different ways of injecting them into a state-of-the-art neural ELMo-based SRL sequence labelling model. We show that using a constituency representation as input features improves performance the most, achieving a new state-of-the-art for non-ensemble SRL models on the in-domain CoNLL’05 and CoNLL’12 benchmarks.</abstract>
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%0 Conference Proceedings
%T How to Best Use Syntax in Semantic Role Labelling
%A Wang, Yufei
%A Johnson, Mark
%A Wan, Stephen
%A Sun, Yifang
%A Wang, Wei
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F wang-etal-2019-best
%X There are many different ways in which external information might be used in a NLP task. This paper investigates how external syntactic information can be used most effectively in the Semantic Role Labeling (SRL) task. We evaluate three different ways of encoding syntactic parses and three different ways of injecting them into a state-of-the-art neural ELMo-based SRL sequence labelling model. We show that using a constituency representation as input features improves performance the most, achieving a new state-of-the-art for non-ensemble SRL models on the in-domain CoNLL’05 and CoNLL’12 benchmarks.
%R 10.18653/v1/P19-1529
%U https://aclanthology.org/P19-1529
%U https://doi.org/10.18653/v1/P19-1529
%P 5338-5343
Markdown (Informal)
[How to Best Use Syntax in Semantic Role Labelling](https://aclanthology.org/P19-1529) (Wang et al., ACL 2019)
ACL
- Yufei Wang, Mark Johnson, Stephen Wan, Yifang Sun, and Wei Wang. 2019. How to Best Use Syntax in Semantic Role Labelling. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5338–5343, Florence, Italy. Association for Computational Linguistics.