Abstract
This paper describes the approach developed by the LT3 team in the Intended Sarcasm Detection task at SemEval-2022 Task 6. We considered the binary classification subtask A for English data. The presented system is based on the fuzzy-rough nearest neighbor classification method using various text embedding techniques. Our solution reached 9th place in the official leader-board for English subtask A.- Anthology ID:
- 2022.semeval-1.138
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 987–992
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.138
- DOI:
- 10.18653/v1/2022.semeval-1.138
- Cite (ACL):
- Olha Kaminska, Chris Cornelis, and Veronique Hoste. 2022. LT3 at SemEval-2022 Task 6: Fuzzy-Rough Nearest Neighbor Classification for Sarcasm Detection. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 987–992, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- LT3 at SemEval-2022 Task 6: Fuzzy-Rough Nearest Neighbor Classification for Sarcasm Detection (Kaminska et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2022.semeval-1.138.pdf
- Code
- olha-kaminska/frnn_emotion_detection
- Data
- TweetEval