__ _ _ _ ___ _ __ _ _ / _` | | | |/ _ \ '_ \| | | | | (_| | |_| | __/ |_) | |_| | \__, |\__,_|\___| .__/ \__, | |_| |_| |___/
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.
Currently Quepy provides support for Sparql and MQL query languages. We plan to extended it to other database query languages.
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:
[{
"/common/topic/description": [{}],
"/type/object/name": "Tom Cruise",
"/type/object/type": "/people/person"
}]
You need to have installed docopt and numpy. Other than that, you can just type:
pip install quepy
You can get more details on the installation here:
http://quepy.readthedocs.org/en/latest/installation.html
You can find a tutorial here:
http://quepy.readthedocs.org/en/latest/tutorial.html
And the full documentation here:
Join our mailing list
Want to help develop quepy? Welcome aboard! Find us in http://groups.google.com/group/quepy