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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.

Abstract

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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