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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Section: Application Domains

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  • Mining Referring Expressions in Knowledge Bases. A referring expression (RE) is a description that identifies a concept unambiguously in a domain of knowledge. For example, the expression “X is the capital of France” is an RE for Paris, because no other city holds this title. Mining REs from data is a central task in natural language generation, and is also applicable to automatic journalism and query generation (e.g., for benchmarking purposes). A common requirement for REs is to be “intuitive”, that is, to resort to concepts that are easily understandable by users. For this reason, existing methods required users to provide a lexical ranking of concepts that conveys their preferences for certain predicates and entities in descriptions. In addition, state-of-the-art methods are not tailored for large current knowledge bases and, due to data incompleteness, are often unable to provide an answer. The internship of Julien Delaunay was conceived to tackle these issues by designing a parallel method to mine intuitive REs on large knowledge bases. The system extends the state-of-the-art language bias for REs to deal with incompleteness and proposes a notion of intuitiveness based on information theory that does not require a lexical ranking from the user. The description of the system, named REMI, is under review at the Extended Semantic Web Conference (ESWC) 2019.