Commit 7155c339 authored by Łukasz Kopociński's avatar Łukasz Kopociński

Add repository packages description to README.md

parent 358edeef
# Semrel Extraction
Repository contains a codebase used in research on the extraction of semantic relations (brand-product).
Research description and results are included in the paper:
["Brand-Product Relation Extraction Using Heterogeneous Vector Space Representations"](https://gitlab.clarin-pl.eu/team-semantics/semrel-extraction/-/blob/develop/LREC_BP.pdf).
["Brand-Product Relation Extraction Using Heterogeneous Vector Space Representations"](https://gitlab.clarin-pl.eu/team-semantics/semrel-extraction/-/blob/develop/LREC_BP.pdf)
published in [LREC2020](https://lrec2020.lrec-conf.org/en/) conference.
## Frameworks
......@@ -24,11 +25,20 @@ Download datasets related to actual commit: \
Then enter to docker folder: \
`$ cd docker`
Copy __credentials.template__ into __credentials__ files and fill with correct access keys.\
Copy __credentials.template__ into __credentials__ files and fill with correct access keys. \
`$ cp deps/credentials.template deps/credentials`
Start docker: \
`$ docker-compose up`
`$ docker-compose up`
## Repository packages
Repository also contains code for additional functionalities:
__docker__ - docker configuration and execution environment for semrel package. \
__mlflow__ - configuration and execution environment for mlflow server used for tracking experiments. \
__spert__ - scripts used to prepare dataset in format required to train [SpERT](https://github.com/markus-eberts/spert) model. \
__worker__ - scripts and execution environment to use trained model as a worker. \
## FAQ
......@@ -44,8 +54,8 @@ DVC will download all data related to actual commit.
#### How to train and test a model?
There is a script __semrel/model/train.sh__ which starts training.
Adjust training params in __semrel/model/config.yaml__ and then execute.
`$ ./train.sh`
Adjust training params in __semrel/model/config.yaml__ and then execute:\
`$ ./train.sh`
Training result will be automatically uploaded to mlflow server.
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