Spanless Event Annotation for Corpus-Wide Complex Event Understanding
Ann Bies, Jennifer Tracey, Ann O’Brien, Song Chen, Stephanie Strassel
Abstract
We present a new approach to event annotation designed to promote whole-corpus understanding of complex events in multilingual, multimedia data as part of the DARPA Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) Program. KAIROS aims to build technology capable of reasoning about complex real-world events like a specific terrorist attack in order to provide actionable insights to end users. KAIROS systems extract events from a corpus, aggregate information into a coherent semantic representation, and instantiate observed events or predict unseen but expected events using a relevant event schema selected from a generalized schema library. To support development and testing for KAIROS Phase 2B we created a complex event annotation corpus that, instead of individual event mentions anchored in document spans with pre-defined event type labels, comprises a series of temporally ordered event frames populated with information aggregated from the whole corpus and labeled with an unconstrained tag set based on Wikidata Qnodes. The corpus makes a unique contribution to the resource landscape for information extraction, addressing gaps in the availability of multilingual, multimedia corpora for schema-based event representation. The corpus will be made available through publication in the Linguistic Data Consortium (LDC) catalog.- Anthology ID:
- 2024.lrec-main.1313
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 15105–15113
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.1313
- DOI:
- Cite (ACL):
- Ann Bies, Jennifer Tracey, Ann O’Brien, Song Chen, and Stephanie Strassel. 2024. Spanless Event Annotation for Corpus-Wide Complex Event Understanding. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 15105–15113, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Spanless Event Annotation for Corpus-Wide Complex Event Understanding (Bies et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.1313.pdf