Assembling Narratives with Associative Threads

Abstract

A model is proposed showing how automatically extracted and manually written association rules can be used to build the structure of a narrative from real-life temporal data. The generated text’s communicative goal is to help the reader construct a causal representation of the events. A connecting associative thread allows the reader to follow associations from the beginning to the end of the text. It is created using a spanning tree over a selected associative sub-network. The results of a text quality evaluation show that the texts were understandable, but that flow between sentences, although not bad, could still be improved.