Summary of the paper
| Title | Detecting Subevent Structure for Event Coreference Resolution |
|---|---|
| Authors | Jun Araki, Zhengzhong Liu, Eduard Hovy and Teruko Mitamura |
| Abstract | In the task of event coreference resolution, recent work has shown the need to perform not only full coreference but also partial coreference of events. We show that subevents can form a particular hierarchical event structure. This paper examines a novel two-stage approach to finding and improving subevent structures. First, we introduce a multiclass logistic regression model that can detect subevent relations in addition to full coreference. Second, we propose a method to improve subevent structure based on subevent clusters detected by the model. Using a corpus in the Intelligence Community domain, we show that the method achieves over 3.2 BLANC F1 gain in detecting subevent relations against the logistic regression model. |
| Topics | Information Extraction, Information Retrieval, Other |
Full paper  |
Detecting Subevent Structure for Event Coreference Resolution |
| Bibtex | @InProceedings{ARAKI14.963, author = {Jun Araki and Zhengzhong Liu and Eduard Hovy and Teruko Mitamura}, title = {Detecting Subevent Structure for Event Coreference Resolution}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |