Abstract
We propose novel radical features from automatic translation for event extraction. Event detection is a complex language processing task for which it is expensive to collect training data, making generalisation challenging. We derive meaningful subword features from automatic translations into target language. Results suggest this method is particularly useful when using languages with writing systems that facilitate easy decomposition into subword features, e.g., logograms and Cangjie. The best result combines logogram features from Chinese and Japanese with syllable features from Korean, providing an additional 3.0 points f-score when added to state-of-the-art generalisation features on the TAC KBP 2015 Event Nugget task.- Anthology ID:
- P17-2046
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Regina Barzilay, Min-Yen Kan
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 293–298
- Language:
- URL:
- https://aclanthology.org/P17-2046
- DOI:
- 10.18653/v1/P17-2046
- Cite (ACL):
- Sam Wei, Igor Korostil, Joel Nothman, and Ben Hachey. 2017. English Event Detection With Translated Language Features. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 293–298, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- English Event Detection With Translated Language Features (Wei et al., ACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/P17-2046.pdf