DFKI-LT - rocessing Document Collections to Automatically Extract Linked Data: Semantic Storytelling Technologies for Smart Curation Workflows
rocessing Document Collections to Automatically Extract Linked Data: Semantic Storytelling Technologies for Smart Curation Workflows
4 Proceedings of the 2nd International Workshop on Natural Language Generation and the Semantic Web (WebNLG 2016),
We develop a system that operates on a document collection and represents the contained information to enable the intuitive and efficient exploration of the collection. Using various NLP, IE and Semantic Web methods, we generate a semantic layer on top of the collection, from which we take the key concepts. We define templates for structured reorganization and rearrange the information related to the key concepts to fit the respective template. The use case of the system is to support knowledge workers (journalists, editors, curators, etc.) in their task of processing large amounts of documents by summarizing the information contained in these documents and suggesting potential story paths that the knowledge worker can then process further.