mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp.git
synced 2024-12-25 19:44:17 +00:00
packages/stand-off-data-py | ||
wrapper | ||
.gitlab-ci.yml | ||
Dockerfile | ||
nlp | ||
README.md | ||
spacy-nlp | ||
vrt-creator |
NLP - Natural Language Processing
This software implements a heavily parallelized pipeline for Natural Language Processing of text files. It is used for nopaque's NLP service but you can also use it standalone, for that purpose a convenient wrapper script is provided.
Software used in this pipeline implementation
- Official Debian Docker image (buster-slim) and programs from its free repositories: https://hub.docker.com/_/debian
- pyFlow (1.1.20): https://github.com/Illumina/pyflow/releases/tag/v1.1.20
- spaCy (3.0.5): https://github.com/tesseract-ocr/tesseract/releases/tag/4.1.1
- spaCy medium sized models (3.0.0):
- https://github.com/explosion/spacy-models/releases/tag/de_core_news_md-3.0.0
- https://github.com/explosion/spacy-models/releases/tag/en_core_web_md-3.0.0
- https://github.com/explosion/spacy-models/releases/tag/it_core_news_md-3.0.0
- https://github.com/explosion/spacy-models/releases/tag/nl_core_news_md-3.0.0
- https://github.com/explosion/spacy-models/releases/tag/pl_core_news_md-3.0.0
- https://github.com/explosion/spacy-models/releases/tag/zh_core_web_md-3.0.0
Use this image
- Create input and output directories for the pipeline.
mkdir -p /<my_data_location>/input /<my_data_location>/output
-
Place your text files inside
/<my_data_location>/input
. Files should all contain text of the same language. -
Start the pipeline process. Check the pipeline help (
nlp --help
) for more details.
# Option one: Use the wrapper script
## Install the wrapper script (only on first run). Get it from https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp/-/raw/1.0.0/wrapper/nlp, make it executeable and add it to your ${PATH}
cd /<my_data_location>
nlp -i input -l <language_code> -o output <optional_pipeline_arguments>
# Option two: Classic Docker style
docker run \
--rm \
-it \
-u $(id -u $USER):$(id -g $USER) \
-v /<my_data_location>/input:/input \
-v /<my_data_location>/output:/output \
gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/nlp:1.0.0 \
-i /input \
-l <language_code>
-o /output \
<optional_pipeline_arguments>
- Check your results in the
/<my_data_location>/output
directory.