Abstract
This paper studies a new cognitively motivated semantic typing task,multi-axis event process typing, that, given anevent process, attempts to infer free-form typelabels describing (i) the type of action made bythe process and (ii) the type of object the pro-cess seeks to affect. This task is inspired bycomputational and cognitive studies of eventunderstanding, which suggest that understand-ing processes of events is often directed by rec-ognizing the goals, plans or intentions of theprotagonist(s). We develop a large dataset con-taining over 60k event processes, featuring ul-tra fine-grained typing on both the action andobject type axes with very large (10ˆ3∼10ˆ4)label vocabularies. We then propose a hybridlearning framework,P2GT, which addressesthe challenging typing problem with indirectsupervision from glosses1and a joint learning-to-rank framework. As our experiments indi-cate,P2GTsupports identifying the intent ofprocesses, as well as the fine semantic type ofthe affected object. It also demonstrates the ca-pability of handling few-shot cases, and stronggeneralizability on out-of-domain processes.- Anthology ID:
- 2020.conll-1.43
- Volume:
- Proceedings of the 24th Conference on Computational Natural Language Learning
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Raquel Fernández, Tal Linzen
- Venue:
- CoNLL
- SIG:
- SIGNLL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 531–542
- Language:
- URL:
- https://aclanthology.org/2020.conll-1.43
- DOI:
- 10.18653/v1/2020.conll-1.43
- Cite (ACL):
- Muhao Chen, Hongming Zhang, Haoyu Wang, and Dan Roth. 2020. What Are You Trying to Do? Semantic Typing of Event Processes. In Proceedings of the 24th Conference on Computational Natural Language Learning, pages 531–542, Online. Association for Computational Linguistics.
- Cite (Informal):
- What Are You Trying to Do? Semantic Typing of Event Processes (Chen et al., CoNLL 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.conll-1.43.pdf