Currently Quepy provides support for Sparql and MQL query languages. We plan to extended it to other database query languages.

Quepy is a python framework to transform natural language questions to queries in a database query language. It can be easily customized to different kinds of questions in natural language and database queries. So, with little coding you can build your own system for natural language access to your database.

An example¶

To illustrate what can you do with quepy, we included an example application to access DBpedia contents via their sparql endpoint.

You can try the example online here: Online demo

Or, you can try the example yourself by doing:

python examples / dbpedia / main . py "Who is Tom Cruise?"

And it will output something like this:

SELECT DISTINCT ?x1 WHERE { ?x0 rdf:type foaf:Person. ?x0 rdfs:label "Tom Cruise"@en. ?x0 rdfs:comment ?x1. } Thomas Cruise Mapother IV, widely known as Tom Cruise, is an...

The transformation from natural language to sparql is done by first using a special form of regular expressions:

person_name = Group ( Plus ( Pos ( "NNP" )), "person_name" ) regex = Lemma ( "who" ) + Lemma ( "be" ) + person_name + Question ( Pos ( "." ))

And then using and a convenient way to express semantic relations:

person = IsPerson () + HasKeyword ( person_name ) definition = DefinitionOf ( person )

The rest of the transformation is handled automatically by the framework to finally produce this sparql:

SELECT DISTINCT ?x1 WHERE { ?x0 rdf : type foaf : Person . ?x0 rdfs : label "Tom Cruise" @ en . ?x0 rdfs : comment ?x1 . }

Using a very similar procedure you could generate and MQL query for the same question obtaining: