The natural language queries are processed and transformed into SPARQL queries, which is used to lookup DBpedia to find a solution.

Install requirements using:
pip3 install -r req.txt

Create a folder data/ and place datasets there.
Run the standalone implementation using python3 Sparql.py "u<query>".
Otherwise, run the flask app using python3 app.py and answer interact from the frontend.

Sample dataset used can be found at https://github.com/ag-sc/QALD/blob/master/7/data/qald-7-train-largescale.json .

To open the front end, simply open index.html when inside the folder qald-interface from a browser.

A partial implementation which uses Blazegraph hosted over a local network is available under kmst.py.