Extracting fine-grained economic events from business news
- Publication type
- C1
- Publication status
- Published
- Authors
- Jacobs, G.M., & Hoste, V.
- Editor
- Mahmoud El-Haj, Vasiliki Athanasakou, Sira Ferradans, Catherine Salzedo, Ans Elhag, Houda Bouamor, Marina Litvak, Paul Rayson, George Giannakopoulos and Nikiforos Pittaras
- Series
- Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation
- Pagination
- 235-245
- Publisher
- COLING
- Conference
- COLING 2020 (Online (Barcelona, Spain))
- Download
- (.pdf)
- View in Biblio
- (externe link)
Abstract
Based on a recently developed fine-grained event extraction dataset for the economic domain, we present in a pilot study for supervised economic event extraction. We investigate how a state-of-the-art model for event extraction performs on the trigger and argument identification and classification. While F1-scores of above 50{%} are obtained on the task of trigger identification, we observe a large gap in performance compared to results on the benchmark ACE05 dataset. We show that single-token triggers do not provide sufficient discriminative information for a fine-grained event detection setup in a closed domain such as economics, since many classes have a large degree of lexico-semantic and contextual overlap.