Towards Discourse Parsing-inspired Semantic Storytelling

Georg Rehm, Karolina Zaczynska, Julián Moreno Schneider, Malte Ostendorff, Peter Bourgonje, Maria Berger, Jens Rauenbusch, André Schmidt, Mikka Wild

In: Adrian Paschke, Clemens Neudecker, Georg Rehm, Jamal Al Qundus, Lydia Pintscher (Hrsg.). Proceedings of QURATOR 2020 -- The conference for intelligent content solutions. Conference on Digital Curation Technologies (QURATOR-2020) Berlin, Germany Proceedings of QURATOR 2020 -- The conference for intelligent content solutions 2/2020.


Previous work of ours on Semantic Storytelling uses text an-alytics procedures including Named Entity Recognition and Event De-tection. In this paper, we outline our longer-term vision on SemanticStorytelling and describe the current conceptual and technical approach.In the project that drives our research we develop AI-based technologiesthat are verified by partners from industry. One long-term goal is thedevelopment of an approach for Semantic Storytelling that has broadcoverage and that is, furthermore, robust. We provide first results on ex-periments that involve discourse parsing, applied to a concrete use case,“Explore the Neighbourhood!”, which is based on a semi-automaticallycollected data set with documents about noteworthy people in one ofBerlin’s districts. Though automatically obtaining annotations for coher-ence relations from plain text is a non-trivial challenge, our preliminaryresults are promising. We envision our approach to be combined withadditional features (NER, coreference resolution, knowledge graphs).


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Georg_Rehm,_Karolina_Zaczynska,_Julián_Moreno_Schneider,_Malte_Ostendorff,_Peter_Bourgonje,_Maria_Berger,_Jens_Rauenbusch,_André_Schmidt,_and_Mikka_Wild._Towards_Discourse_Parsing-inspired_Semantic_Storytelling..pdf (pdf, 1 MB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence