Abstract
In this paper we present work-in-progress where we investigate the usefulness of previously created word lists to the task of single-word lexical complexity analysis and prediction of the complexity level for learners of Swedish as a second language. The word lists used map each word to a single CEFR level, and the task consists of predicting CEFR levels for unseen words. In contrast to previous work on word-level lexical complexity, we experiment with topics as additional features and show that linking words to topics significantly increases accuracy of classification.- Anthology ID:
- W18-0508
- Volume:
- Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 79–88
- Language:
- URL:
- https://aclanthology.org/W18-0508
- DOI:
- 10.18653/v1/W18-0508
- Cite (ACL):
- David Alfter and Elena Volodina. 2018. Towards Single Word Lexical Complexity Prediction. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 79–88, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Towards Single Word Lexical Complexity Prediction (Alfter & Volodina, BEA 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W18-0508.pdf