Abstract
#Turki$hTweets is a benchmark dataset for the task of correcting the user misspellings, with the purpose of introducing the first public Turkish dataset in this area. #Turki$hTweets provides correct/incorrect word annotations with a detailed misspelling category formulation based on the real user data. We evaluated four state-of-the-art approaches on our dataset to present a preliminary analysis for the sake of reproducibility.- Anthology ID:
- 2020.findings-emnlp.374
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4190–4198
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.374
- DOI:
- 10.18653/v1/2020.findings-emnlp.374
- Cite (ACL):
- Asiye Tuba Koksal, Ozge Bozal, Emre Yürekli, and Gizem Gezici. 2020. #Turki$hTweets: A Benchmark Dataset for Turkish Text Correction. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4190–4198, Online. Association for Computational Linguistics.
- Cite (Informal):
- #Turki$hTweets: A Benchmark Dataset for Turkish Text Correction (Koksal et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.findings-emnlp.374.pdf
- Code
- atubakoksal/annotated_tweets