git clone https://github.com/dice-group/favel.git
conda create -n "favel" python=3.7
conda activate favel
cd favel
pip install -r requirements.txt
cd favel

or

git clone https://github.com/dice-group/favel.git
virtualenv -p python3.7 favel
source favel/bin/activate
pip install -r requirements.txt
cd favel

• To conduct an experiment with the software execute the following steps:
  1. Create a directory inside the Evaluation directory.
     The name of the directory is the name of the experiment
     Example: favel/Evaluation/experiment42
  2. Create a configuration file favel.conf inside the experiment directory.
     The configuration file defines the set of fact validation approaches and the machine learning algorithm.
     A basic configuration file is can be found here.
     For more advanced configuration options look here.
     Example: favel/Evaluation/experiment42/favel.conf
  3. Execute the software.
     For the software to be able to use fact validation approaches, these approaches might have to be started manually.
     An exaustive description how to run the software can be found in the following section.
     Results will be saved to the favel/Evaluation/ directory.
     Example: python3 favel/Software/Favel.py -d favel/FinalDataset_Hard -e experiment42

• -e EXPERIMENT, --experiment EXPERIMENT name of the experiment, corresponds with the name of the experiment folder in the Evaluation directory
• -b EXPERIMENT, --batch EXPERIMENT name of the experiment, corresponds with the name of the experiment folder in the Evaluation directory. Experiment will be run in batch mode, meaning that an experiment will be executed with every subset of the specified set of fact validation approaches.
• -d DATA, --data DATA path to the dataset to validate
• -w, --write write everything to disk. If this flag is set, all possible outputs are written to disk. This includes models, normalizers, predicate encoders, and dataframes. If the flag is not set, only the overview is written to disk.
• -c, --containersAutomatically Start/Stop containers that encapsulate the fact validation approaches.
• -a, --automl To use the autoML system instead of the manual algorithm selection.

• First activate the environment using the command specified above.
• FAVEL_ALL_RESULTS.zip file contains the precomputed veracity scores from individual approaches.
• Unzip this file and run the following command to execute experiments.
• You can change the input config file in the Evaluations/eval001 folder.

unzip FAVEL_ALL_RESULTS.zip
python3 Software/Favel.py -e eval001 -d FAVEL_ALL_RESULTS/FaVEL/input/ -w -a

Each experiment can take up to 3 hours depending upon no. of iterations in the input config file.