Abstract
This paper describes the design and use of the graph-based parsing framework and toolkit UniParse, released as an open-source python software package. UniParse as a framework novelly streamlines research prototyping, development and evaluation of graph-based dependency parsing architectures. UniParse does this by enabling highly efficient, sufficiently independent, easily readable, and easily extensible implementations for all dependency parser components. We distribute the toolkit with ready-made configurations as re-implementations of all current state-of-the-art first-order graph-based parsers, including even more efficient Cython implementations of both encoders and decoders, as well as the required specialised loss functions.- Anthology ID:
- W19-6149
- Volume:
- Proceedings of the 22nd Nordic Conference on Computational Linguistics
- Month:
- September–October
- Year:
- 2019
- Address:
- Turku, Finland
- Editors:
- Mareike Hartmann, Barbara Plank
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- Linköping University Electronic Press
- Note:
- Pages:
- 406–410
- Language:
- URL:
- https://aclanthology.org/W19-6149
- DOI:
- Cite (ACL):
- Daniel Varab and Natalie Schluter. 2019. UniParse: A universal graph-based parsing toolkit. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 406–410, Turku, Finland. Linköping University Electronic Press.
- Cite (Informal):
- UniParse: A universal graph-based parsing toolkit (Varab & Schluter, NoDaLiDa 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W19-6149.pdf
- Code
- ITUnlp/UniParse