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
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/D18-1196.pdf