Abstract
Our approach is constructed to improve on a couple of aspects; preprocessing with an emphasis on humor sense detection, using embeddings from state-of-the-art language model(Elmo), and ensembling the results came up with using machine learning model Na ̈ıve Bayes(NB) with a deep learning pre-trained models. Elmo-NB participation has scored (0.5642) on the competition leader board, where results were measured by Root Mean Squared Error (RMSE).- Anthology ID:
- 2020.semeval-1.130
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1001–1007
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.130
- DOI:
- 10.18653/v1/2020.semeval-1.130
- Cite (ACL):
- Enas Khwaileh and Muntaha A. Al-As’ad. 2020. ELMo-NB at SemEval-2020 Task 7: Assessing Sense of Humor in EditedNews Headlines Using ELMo and NB. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1001–1007, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- ELMo-NB at SemEval-2020 Task 7: Assessing Sense of Humor in EditedNews Headlines Using ELMo and NB (Khwaileh & Al-As’ad, SemEval 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.semeval-1.130.pdf