During the first period we managed to clarify the needs for knowledge representation infrastructure of the case studies and software tools in MOLTO. We have also circulated a questionaire describing the structured data sets which are expected to be of benefit for the project. Based on this information, we proceeded with deploying the knowledge representation infrastructure, which is now in place and accessible to the partners. It will be further described in D4.1 Knowledge Representation Infrastructure.

The second major direction during this period was the undoubtedly challenging grammar to ontology interoperability. For this we have chosen a quasi-exhaustive knowledge base of important named entities in the world and some relations between them. It is encoded according to PROTON – a basic-upper level ontology with about 300 classes of named entities. The first goal set for this interoperability was a transformation of questions expressed in natural language towards a formal query language – SPARQL. For this purpose, and on the basis of the ontology and the entities in the knowledge base, we have manually created a corpus of 500 sentences. This corpus is being used for development of the GF grammars handling the natural language questions and also for evaluation of the coverage of the grammars over this language space. After an initial grammar handling questions to the knowledge base has been developed for a subset of the English language, we have created a transformation function, rendering GF sentence trees to SPARQL queries. In order to show these initial results, we have developed a natural language based search interface over the knowledge base, with automatic suggestion of possible continuation of the questions, which is featured on the MOLTO website. The results of these questions are one or two dimensional tables of entities, where each row is an individual “answer”.

Effort spent by Ontotext in WP4 – 7.5 PMs; Other participants UGOT: Aarne will talk directly to Olga for this.