DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers

Jesse Dunietz, Jaime Carbonell, Lori Levin


Abstract
This paper introduces the surface construction labeling (SCL) task, which expands the coverage of Shallow Semantic Parsing (SSP) to include frames triggered by complex constructions. We present DeepCx, a neural, transition-based system for SCL. As a test case for the approach, we apply DeepCx to the task of tagging causal language in English, which relies on a wider variety of constructions than are typically addressed in SSP. We report substantial improvements over previous tagging efforts on a causal language dataset. We also propose ways DeepCx could be extended to still more difficult constructions and to other semantic domains once appropriate datasets become available.
Anthology ID:
D18-1196
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1691–1701
Language:
URL:
https://aclanthology.org/D18-1196
DOI:
10.18653/v1/D18-1196
Bibkey:
Cite (ACL):
Jesse Dunietz, Jaime Carbonell, and Lori Levin. 2018. DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1691–1701, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers (Dunietz et al., EMNLP 2018)
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PDF:
https://aclanthology.org/D18-1196.pdf
Attachment:
 D18-1196.Attachment.zip