The evaluation framework is distributed together with all systems and requirements as a Docker image, which can be pulled like so:
$ docker pull registry.gitlab.com/frankier/stiff:latest
And run like so:
$ docker -v /path/to/working/dir/:/work/ run python eval.py /work/results.json /work/eurosense.eval/
For CUDA accelerated experiments, you can use nvidia-docker. For running in shared computing environments, in which you don't have root access, I recommend udocker.
You can also set up requirements manually. See the Dockerfile for the list of
commands to run.
The one requirement which is not included in the Docker image is the evaluation corpus. Please follow the instructions in the STIFF README.
eval.pyYou can run a subset of experiments by passing filters to eval.py, e.g.
$ python eval.py /work/results.json /work/eurosense.eval/ Knowledge 'Cross-lingual Lesk' mean=pre_sif_mean
table.pyYou can make LaTeX tables with table.py, e.g.
$ python table.py results.json --filter='Knowledge;Cross-lingual Lesk' --table='use_freq;vec:fasttext,numberbatch,double;mean expand;wn_filter'
This project is licensed under the Apache v2 license. The code in ukb-eval is
vendorized from UKB, and therefore licensed under the GPL. The scorer in
support/scorer is under an unknown license, possibly public domain.
BABEL2WN_MAP.Content type
Image
Digest
Size
9.5 GB
Last updated
about 7 years ago
docker pull frankierr/finn-wsd-eval