Story generation is a long standing goal of Artificial Intelligence. At first glance, there is a noticeable lack of homogeneity in the way in which existing story generation systems represent their knowledge, but there is a common need: their basic knowledge must be expressed unambiguously to avoid inconsistencies. A suitable solution could be the use of a controlled natural language (CNL), acting both as an intermediate step between human expertise and system knowledge and as a generic format in which to express knowledge for one system in a way that can be easily mined to obtain knowledge for another system - which might use a different formal language. This paper analyses the suitability of using CNLs for representing knowledge for story generation systems.
CITATION STYLE
Concepción, E., Gervás, P., Méndez, G., & León, C. (2016). Using CNL for knowledge elicitation and exchange across story generation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9767, pp. 81–91). Springer Verlag. https://doi.org/10.1007/978-3-319-41498-0_8
Mendeley helps you to discover research relevant for your work.