How to best use syntax in semantic role labelling

Yufei Wang; Mark Johnson; Stephen Wan; Yifang Sun; Wei Wang

doi:10.18653/v1/P19-1529

How to best use syntax in semantic role labelling

Yufei Wang, Mark Johnson, Stephen Wan, Yifang Sun, Wei Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

20 Citations (Scopus)

72 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Editors	Anna Korhonen, David Traum, Lluís Màrquez
Place of Publication	Florence, Italy
Publisher	Association for Computational Linguistics
Pages	5338-5343
Number of pages	6
ISBN (Electronic)	9781950737482
DOIs	https://doi.org/10.18653/v1/P19-1529
Publication status	Published - Jul 2019
Event	Annual Meeting of the Association for Computational Linguistics (57th : 2019) - Florence, Italy Duration: 28 Jul 2019 → 2 Aug 2019

Publication series

Name	ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference

Conference

Conference	Annual Meeting of the Association for Computational Linguistics (57th : 2019)
Country/Territory	Italy
City	Florence
Period	28/07/19 → 2/08/19

Bibliographical note

Copyright the Publisher 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Access to Document

10.18653/v1/P19-1529

Publisher version (open access)Final published version, 323 KBLicence: CC BY

Cite this

Wang, Y., Johnson, M., Wan, S., Sun, Y., & Wang, W. (2019). How to best use syntax in semantic role labelling. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 5338-5343). (ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference). Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1529

Wang, Yufei ; Johnson, Mark ; Wan, Stephen et al. / How to best use syntax in semantic role labelling. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. editor / Anna Korhonen ; David Traum ; Lluís Màrquez. Florence, Italy : Association for Computational Linguistics, 2019. pp. 5338-5343 (ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference).

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title = "How to best use syntax in semantic role labelling",

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{\textquoteright}05 and CoNLL{\textquoteright}12 benchmarks.",

author = "Yufei Wang and Mark Johnson and Stephen Wan and Yifang Sun and Wei Wang",

note = "Copyright the Publisher 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher. ; Annual Meeting of the Association for Computational Linguistics (57th : 2019) ; Conference date: 28-07-2019 Through 02-08-2019",

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language = "English",

series = "ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference",

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Wang, Y, Johnson, M, Wan, S, Sun, Y & Wang, W 2019, How to best use syntax in semantic role labelling. in A Korhonen, D Traum & L Màrquez (eds), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, Association for Computational Linguistics, Florence, Italy, pp. 5338-5343, Annual Meeting of the Association for Computational Linguistics (57th : 2019), Florence, Italy, 28/07/19. https://doi.org/10.18653/v1/P19-1529

How to best use syntax in semantic role labelling. / Wang, Yufei; Johnson, Mark; Wan, Stephen et al.
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. ed. / Anna Korhonen; David Traum; Lluís Màrquez. Florence, Italy: Association for Computational Linguistics, 2019. p. 5338-5343 (ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Wan, Stephen

AU - Sun, Yifang

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N2 - 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.

AB - 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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Wang Y, Johnson M, Wan S, Sun Y, Wang W. How to best use syntax in semantic role labelling. In Korhonen A, Traum D, Màrquez L, editors, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy: Association for Computational Linguistics. 2019. p. 5338-5343. (ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference). doi: 10.18653/v1/P19-1529

How to best use syntax in semantic role labelling

Abstract

Publication series

Conference

Bibliographical note

Access to Document

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Fingerprint

Improved syntactic and semantic analysis for natural language processing

Cite this

How to best use syntax in semantic role labelling

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Projects

Improved syntactic and semantic analysis for natural language processing

Cite this