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# How to reproduce the experiment?
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First you need a database that supports SPARQL queries.
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Once you have that, you can generate the database using the ``fill_knowledge_graph.sparql``.
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Then you need to execute ``convert_kg_json_tasks.py`` to convert ``constants.json`` to ``constants.pickle`` (supported by AutoSynth).
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Then you need to preprocess the tasks with ``preprocess_tasks.py`` which will guess the constants.
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Then you can use the ``constants.pickle`` file in ``evaluate.py`` with your model.
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In our paper the model was the one obtained through the scrip ``test_performance.sh`` in experiments.

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