Section: Application Domains

Information extraction and knowledge acquisition

Participants : Éric Villemonte de La Clergerie, Benoît Sagot.

The first domain of application for Alpage parsing systems is information extraction, and in particular knowledge acquisition, be it linguistic or not, and text mining.

Knowledge acquisition for a given restricted domain is something that has already been studied by some Alpage members for several years. Obviously, the progressive extension of Alpage parsing systems or even shallow processing chains to the semantic level increase the quality of the extracted information, as well as the scope of information that can be extracted. Such knowledge acquisition efforts bring solutions to current problems related to information access and take place into the emerging notion of Semantic Web. The transition from a web based on data (textual documents,...) to a web based on knowledge requires linguistic processing tools which are able to provide fine grained pieces of information, in particular by relying on high-quality deep parsing. For a given domain of knowledge (say, news wires or tourism), the extraction of a domain ontology that represents its key concepts and the relations between them is a crucial task, which has a lot in common with the extraction of linguistic information.

In the last years, such efforts have been targeted towards information extraction from news wires in collaboration with the Agence France-Presse (Rosa Stern was a CIFRE PhD student at Alpage and at AFP, and worked in 2013 within the ANR project EDyLex).

These applications in the domain of information extraction raise exciting challenges that require altogether ideas and tools coming from the domains of computational linguistics, machine learning and knowledge representation.