Dense Event Ordering with a Multi-Pass Architecture
Nathanael Chambers, Taylor Cassidy, Bill McDowell, Steven Bethard
Abstract
The past 10 years of event ordering research has focused on learning partial orderings over document events and time expressions. The most popular corpus, the TimeBank, contains a small subset of the possible ordering graph. Many evaluations follow suit by only testing certain pairs of events (e.g., only main verbs of neighboring sentences). This has led most research to focus on specific learners for partial labelings. This paper attempts to nudge the discussion from identifying some relations to all relations. We present new experiments on strongly connected event graphs that contain ∼10 times more relations per document than the TimeBank. We also describe a shift away from the single learner to a sieve-based architecture that naturally blends multiple learners into a precision-ranked cascade of sieves. Each sieve adds labels to the event graph one at a time, and earlier sieves inform later ones through transitive closure. This paper thus describes innovations in both approach and task. We experiment on the densest event graphs to date and show a 14% gain over state-of-the-art.- Anthology ID:
- Q14-1022
- Volume:
- Transactions of the Association for Computational Linguistics, Volume 2
- Month:
- Year:
- 2014
- Address:
- Cambridge, MA
- Editors:
- Dekang Lin, Michael Collins, Lillian Lee
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 273–284
- Language:
- URL:
- https://aclanthology.org/Q14-1022
- DOI:
- 10.1162/tacl_a_00182
- Cite (ACL):
- Nathanael Chambers, Taylor Cassidy, Bill McDowell, and Steven Bethard. 2014. Dense Event Ordering with a Multi-Pass Architecture. Transactions of the Association for Computational Linguistics, 2:273–284.
- Cite (Informal):
- Dense Event Ordering with a Multi-Pass Architecture (Chambers et al., TACL 2014)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/Q14-1022.pdf
- Data
- TimeBank