Towards Discourse Parsing-inspired Semantic Storytelling

• URL: http://arxiv.org/abs/2004.12190v1
• Date: Sat, 25 Apr 2020 17:09:56 GMT
• Title: Towards Discourse Parsing-inspired Semantic Storytelling
• Authors: Georg Rehm and Karolina Zaczynska and Juli\'an Moreno-Schneider and Malte Ostendorff and Peter Bourgonje and Maria Berger and Jens Rauenbusch and Andr\'e Schmidt and Mikka Wild
• Abstract summary: We outline our longer-term vision on Semantic Storytelling and describe the current conceptual and technical approach. One long-term goal is the development of an approach for Semantic Storytelling that has broad coverage and that is, furthermore, robust.
• Score: 0.8974184539413771
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Previous work of ours on Semantic Storytelling uses text analytics procedures including Named Entity Recognition and Event Detection. In this paper, we outline our longer-term vision on Semantic Storytelling and describe the current conceptual and technical approach. In the project that drives our research we develop AI-based technologies that are verified by partners from industry. One long-term goal is the development of an approach for Semantic Storytelling that has broad coverage and that is, furthermore, robust. We provide first results on experiments that involve discourse parsing, applied to a concrete use case, "Explore the Neighbourhood!", which is based on a semi-automatically collected data set with documents about noteworthy people in one of Berlin's districts. Though automatically obtaining annotations for coherence relations from plain text is a non-trivial challenge, our preliminary results are promising. We envision our approach to be combined with additional features (NER, coreference resolution, knowledge graphs

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