Dockerizing Alvis and its components
Find the OpenMinteD compatible components here.
The components are wrapped following the OpenMinTeD guidelines.
A docker image for the alvisnlp engine in command line is available into Docker Hub
/!\ Prerequisites are docker installed (>= 1.13.1) and 4Go of free disk space
docker run mandiayba/alvisengine:1.0.0 \
alvisnlp -help
docker run mandiayba/alvisengine:1.0.0 \
alvisnlp -supportedModules
SimpleProjector
docker run mandiayba/alvisengine:1.0.0 \
alvisnlp -moduleDoc GeniaTagger
docker run -i --rm -v $PWD/workdir:/opt/alvisnlp/data \
-a stderr mandiayba/alvisengine:1.0.0 \
alvisnlp /opt/alvisnlp/data/plans/train.plan
docker run -i --rm -v $PWD/workdir:/opt/alvisnlp/data \
-a stderr mandiayba/alvisengine:1.0.0 \
alvisnlp /opt/alvisnlp/data/plans/predict.plan
docker run -i --rm -v $PWD/workdir:/opt/alvisnlp/data -a stderr mandiayba/alvisengine:1.0.0 \
alvisnlp \
-param train textDir /opt/alvisnlp/data/corpus/train \
-param dev textDir /opt/alvisnlp/data/corpus/dev \
-param test textDir /opt/alvisnlp/data/corpus/test \
-param TEESTrain model /opt/alvisnlp/data/models \
/opt/alvisnlp/data/plans/train.plan
The train and classify workflows (called plans into alvis) are based on GeniaTagger and TEES tools integrated to AlvisNLP. The corpus used is Bacteria Biotope 2016. The binary relation here is named "Lives_in" ant it expresses the fact that some bacteries live in some habitats.
automatically clone and install alvisnlp with Dockerfile by addding the following external programs:
* Not the latest version, we might want to test with the latest version.