Abstract
In this paper, we describe our participation in SemEval-2019 Task 3: EmoContext - A Shared Task on Contextual Emotion Detection in Text. We propose a three layer model with a generic, multi-purpose approach that without any task specific optimizations achieve competitive results (f1 score of 0.7096) in the EmoContext task. We describe our development strategy in detail along with an exposition of our results.- Anthology ID:
- S19-2037
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 225–229
- Language:
- URL:
- https://aclanthology.org/S19-2037
- DOI:
- 10.18653/v1/S19-2037
- Cite (ACL):
- Dumitru Bogdan. 2019. GenSMT at SemEval-2019 Task 3: Contextual Emotion Detection in tweets using multi task generic approach. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 225–229, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- GenSMT at SemEval-2019 Task 3: Contextual Emotion Detection in tweets using multi task generic approach (Bogdan, SemEval 2019)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/S19-2037.pdf
- Data
- EmoContext