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README.md

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@@ -10,22 +10,14 @@ and extended to support DM, PSD, EDS and AMR.
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### Install
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Create a Python virtual environment. For example, on Linux:
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virtualenv --python=/usr/bin/python3 venv
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. venv/bin/activate # on bash
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source venv/bin/activate.csh # on csh
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Install the latest code from GitHub:
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Install the latest code from GitHub (may be unstable):
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git clone https://github.com/danielhers/tupa --branch=mrp
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cd tupa
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pip install .
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pip install git+https://github.com/danielhers/tupa.git@mrp
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### Train the parser
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Having a directory with MRP graph files
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(for example, [the MRP sample](http://svn.nlpl.eu/mrp/2019/public/sample.tgz)),
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(for example, [the MRP UCCA data](http://svn.nlpl.eu/mrp/2019/public/ucca.tgz)),
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run:
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python -m tupa -t <train_dir> -d <dev_dir> -m <model_filename>
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Citation
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--------
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If you make use of this software, please cite [the following paper](http://aclweb.org/anthology/P18-1035):
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@InProceedings{hershcovich2018multitask,
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author = {Hershcovich, Daniel and Abend, Omri and Rappoport, Ari},
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title = {Multitask Parsing Across Semantic Representations},
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booktitle = {Proc. of ACL},
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year = {2018},
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pages = {373--385},
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url = {http://aclweb.org/anthology/P18-1035}
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If you make use of this software, please cite [the following paper](https://www.aclweb.org/anthology/K19-2002):
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@InProceedings{hershcovich-arviv-2019-tupa,
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author = {Hershcovich, Daniel and Arviv, Ofir},
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title = {{TUPA} at {MRP} 2019: A Multi-Task Baseline Syste},
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booktitle = {Proc. of CoNLL MRP Shared Task},
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year = {2019},
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pages = {28--39},
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url = {https://www.aclweb.org/anthology/K19-2002},
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doi = {10.18653/v1/K19-2002}
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}
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