Cross-Document Event Coreference Resolution Beyond Corpus-Tailored Systems
@article{Bugert2020CrossDocumentEC, title={Cross-Document Event Coreference Resolution Beyond Corpus-Tailored Systems}, author={Michael Bugert and N. Reimers and Iryna Gurevych}, journal={ArXiv}, year={2020}, volume={abs/2011.12249} }
Cross-document event coreference resolution (CDCR) is an NLP task in which mentions of events need to be identified and clustered throughout a collection of documents. CDCR aims to benefit downstream multi-document applications, but despite recent progress on corpora and model development, downstream improvements from applying CDCR have not been shown yet. The reason lies in the fact that every CDCR system released to date was developed, trained, and tested only on a single respective corpus… Expand
References
SHOWING 1-10 OF 48 REFERENCES
New Insights into Cross-Document Event Coreference: Systematic Comparison and a Simplified Approach
- Computer Science
- NUSE@ACL
- 2020
- 3
- PDF
Breaking the Subtopic Barrier in Cross-Document Event Coreference Resolution
- Computer Science
- Text2Story@ECIR
- 2020
- 2
- PDF
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution
- Computer Science
- ACL
- 2019
- 27
- PDF
Revisiting the Evaluation for Cross Document Event Coreference
- Computer Science
- COLING
- 2016
- 8
- Highly Influential
- PDF
Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation
- Computer Science, Medicine
- ACL
- 2014
- 123
- PDF
Using a sledgehammer to crack a nut? Lexical diversity and event coreference resolution
- Computer Science
- LREC
- 2014
- 87
- PDF
Identifying the Most Dominant Event in a News Article by Mining Event Coreference Relations
- Computer Science
- NAACL-HLT
- 2018
- 10
- PDF
Entity-Based Cross-Document Coreferencing Using the Vector Space Model
- Computer Science
- COLING-ACL
- 1998
- 599
- PDF
Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events
- Computer Science
- EMNLP
- 2017
- 21
- PDF