UniParse: A universal graph-based parsing toolkit

Daniel Varab, Natalie Schluter


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
Venues:
NoDaLiDa | WS
SIG:
Publisher:
Linköping University Electronic Press
Note:
Pages:
406–410
Language:
URL:
https://www.aclweb.org/anthology/W19-6149
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-6149.pdf