├── .gitignore
└── README.md


/.gitignore:
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 1 | # Byte-compiled / optimized / DLL files
 2 | __pycache__/
 3 | *.py[cod]
 4 | 
 5 | # C and C++ extensions
 6 | *.so
 7 | *.c
 8 | *.cpp
 9 | *.html
10 | 
11 | # Distribution / packaging
12 | bin/
13 | build/
14 | develop-eggs/
15 | dist/
16 | eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | *.egg-info/
23 | .installed.cfg
24 | *.egg
25 | 
26 | # Installer logs
27 | pip-log.txt
28 | pip-delete-this-directory.txt
29 | 
30 | # Unit test / coverage reports
31 | .tox/
32 | .coverage
33 | .cache
34 | nosetests.xml
35 | coverage.xml
36 | 
37 | # Translations
38 | *.mo
39 | 
40 | .vscode
41 | 


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/README.md:
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 1 | # UniParse
 2 | UniParse: A universal graph-based modular parsing framework, for quick prototyping and comparison of parser components.  
 3 | 
 4 | **This code base has been moved to [github.com/danielvarab/uniparse](https://github.com/danielvarab/uniparse) as of October 1. 2019. All future development will happend in this repository.**
 5 | 
 6 | **To continue to use this version of UniParse, checkout the branch labeled `archived` which contains a frozen/archived state of UniParse.**
 7 | 
 8 | ## Citation
 9 | If you are using UniParse, please cite our [paper](https://www.aclweb.org/anthology/W19-6149/).
10 | 
11 | ```
12 | @inproceedings{varab-schluter-2019-uniparse,
13 |     title = "{U}ni{P}arse: A universal graph-based parsing toolkit",
14 |     author = "Varab, Daniel  and Schluter, Natalie",
15 |     booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
16 |     month = "30 " # sep # " {--} 2 " # oct,
17 |     year = "2019",
18 |     address = "Turku, Finland",
19 |     publisher = {Link{\"o}ping University Electronic Press},
20 |     url = "https://www.aclweb.org/anthology/W19-6149",
21 |     pages = "406--410",
22 |     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.",
23 | }
24 | ```


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