Parsing/stanfordnlp

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(Background)
(Background)
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<pre>
 
<pre>
 
module purge; module load nlpl-stanfordnlp
 
module purge; module load nlpl-stanfordnlp
python3 -c 'import stanfordnlp; foo = stanfordnlp.Pipeline("en")("Kim wanted to be heard."); foo.sentences[0].print_dependencies();'
+
python3 -c 'import stanfordnlp; \
 +
  foo = stanfordnlp.Pipeline("en")("Kim wanted to be heard."); \
 +
  foo.sentences[0].print_dependencies();'
 
</pre>
 
</pre>
  

Revision as of 01:07, 11 February 2019

Background

The StanfordNLP pipeline makes available two multilingual parsing systems with a Python interface, one implemented natively on top of PyTorch, the other a server–client interface to the venerable Stanford CoreNLP software (which runs in Java).

module purge; module load nlpl-stanfordnlp
python3 -c 'import stanfordnlp; \
  foo = stanfordnlp.Pipeline("en")("Kim wanted to be heard."); \
  foo.sentences[0].print_dependencies();'

Installation on Abel

module purge; module load python3/3.70
/projects/nlpl/operation/python/initialize --version 0.1.1 stanfordnlpl

Next, it appears we need to manually patch the default location for model files in .../site-packages/stanfordnlp/utils/resources.py, to point to a shared directory for all users (viz. /projects/nlpl/software/stanfordnlp/0.1.1/resources/). To download all available pre-trained models (for the complete UD 2.x set of treebanks):

module purge; module load nlpl-stanfordnlp
yes | python3 /projects/nlpl/software/stanfordnlp/0.1.1/download.py
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