Camille Pradel

A semantic web interface using patterns: the SWIP system

Our purpose is to hide the complexity of formulating a query expressed in a graph query language such as SPARQL. We propose a mechanism allowing queries to be expressed in a very simple pivot language, mainly composed of keywords and relations between keywords. Our system associates the keywords with the corresponding elements of the ontology (classes, relations, instances). Then it selects pre-written query patterns, and instanciates them with regard to the keywords of the initial query. Several possible queries are generated, ranked and then shown to the user. These queries are presented by means of natural language sentences. The user then selects the query he/she is interested in and the SPARQL query is built.

Expressing conceptual graph queries from patterns: how to take into account the relations

Our goal is to hide the complexity of formulating a query expressed in a graph query language such as conceptual graphs. We propose a mechanism allowing one to express queries in a very simple pivot language, mainly composed of keywords and relations between keywords. Our system associates the keywords with the corresponding elements of the support (concept types, relation types, individual markers). Then it selects pre-written query patterns, and instanciates them with regard to the keywords of the initial query. Several possible queries are shown to the user. These queries are presented by means of natural language sentences. The user then selects the query he/she is interested in. The query conceptual graph is then built.

Swip: A Natural Language to SPARQL Interface Implemented with SPARQL

The Swip approach aims at translating into SPARQL queries expressed in natural language exploiting query patterns. In this article, we present the main module of the prototype implementing this approach which entirely relies on SPARQL. All steps of the interpretation process which are carried out in this module are indeed completely performed on RDF triple stores through SPARQL updates. Thus, the implementation gets benefit from SPARQL engine capabilities, which prevent us from worrying about graph manipulation and matching.

Taking SPARQL 1.1 Extensions into Account in the SWIP System

The SWIP system aims at hiding the complexity of expressing a query in a graph query language such as SPARQL. We propose a mechanism by which a query expressed in natural language is translated into a SPARQL query. Our system analyses the sentence in order to exhibit concepts, instances and relations. Then it generates a query in an internal format called the pivot language. Finally, it selects pre-written query patterns and instantiates them with regard to the keywords of the initial query. These queries are presented by means of explicative natural language sentences among which the user can select the query he/she is actually interested in. We are currently focusing on new kinds of queries which are handled by the new version of our system, which is now based on the 1.1 version of SPARQL.

Allowing end users to query graph-based knowledge bases

Our purpose is to provide end users a means to query knowledge bases using natural language queries and thus hide the complexity of formulating a query expressed in a graph query language such as SPARQL. The main originality of our approach lies in the use of query patterns. Our contribution is materialized in a system named SWIP, standing for Semantic Web Interface Using Patterns, which is situated in the Semantic Web framework. This paper presents the main issues addressed by our work and establishes the list of the important steps (to be) carried out in order to make SWIP a fully functional system.