Abstract
This submission describes the development of a fine-grained, text-chunking algorithm for the task of comprehensive MWE segmentation. This task notably focuses on the identification of colloquial and idiomatic language. The submission also includes a thorough model evaluation in the context of two recent shared tasks, spanning 19 different languages and many text domains, including noisy, user-generated text. Evaluations exhibit the presented model as the best overall for purposes of MWE segmentation, and open-source software is released with the submission (although links are withheld for purposes of anonymity). Additionally, the authors acknowledge the existence of a pre-print document on arxiv.org, which should be avoided to maintain anonymity in review.- Anthology ID:
- W17-4401
- Volume:
- Proceedings of the 3rd Workshop on Noisy User-generated Text
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Venue:
- WNUT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–10
- Language:
- URL:
- https://aclanthology.org/W17-4401
- DOI:
- 10.18653/v1/W17-4401
- Cite (ACL):
- Jake Williams. 2017. Boundary-based MWE segmentation with text partitioning. In Proceedings of the 3rd Workshop on Noisy User-generated Text, pages 1–10, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Boundary-based MWE segmentation with text partitioning (Williams, WNUT 2017)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W17-4401.pdf