Abstract
This work explores different approaches of using normalization for parser adaptation. Traditionally, normalization is used as separate pre-processing step. We show that integrating the normalization model into the parsing algorithm is more beneficial. This way, multiple normalization candidates can be leveraged, which improves parsing performance on social media. We test this hypothesis by modifying the Berkeley parser; out-of-the-box it achieves an F1 score of 66.52. Our integrated approach reaches a significant improvement with an F1 score of 67.36, while using the best normalization sequence results in an F1 score of only 66.94.- Anthology ID:
- P17-2078
- 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:
- 491–497
- Language:
- URL:
- https://aclanthology.org/P17-2078
- DOI:
- 10.18653/v1/P17-2078
- Cite (ACL):
- Rob van der Goot and Gertjan van Noord. 2017. Parser Adaptation for Social Media by Integrating Normalization. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 491–497, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Parser Adaptation for Social Media by Integrating Normalization (van der Goot & van Noord, ACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/P17-2078.pdf