short (5 sentences or less) and/or have a standardised structure, but have problems in generating texts which are longer and do not have a fixed structure. Corpus-based structuring techniques use statistical corpus analysis techniques to automatically build ordering and/or grouping models. Such techniques are common in Automatic summarisation, where a computer program automatically generates a summary of a textual document. In principle they could be applied to text generated from non-linguistic data, but this work is in its infancy; part of the challenge is that texts generated by Natural Language Generation systems are generally expected to be of fairly high quality, which is not always the case for texts generated by automatic summarisation systems. The final approach is heuristic-based structuring. Such algorithms perform the structuring task based on heuristic rules, which can come from theories of rhetoric, psycholinguistic models, and/or a combination of intuition and feedback from pilot experiments with potential users. Heuristic-based structuring is appealing intellectually, but it can be difficult to get it to work well in practice, in part because heuristics often depend on semantic information (how sentences relate to each other) which is not always available. On the other hand, heuristic rules can focus on what is best for text readers, whereas the other approaches focus on imitating authors (and many human-authored texts are not well structured). Narrative Perhaps the ultimate document structuring challenge is to generate a good narrative—in other words, a text which starts by setting the scene and giving an introduction/overview; then describes a set of events in a clear fashion so readers can easily see how the individual events are related and link together; and concludes with a summary/ending. Note that narrative in this sense applies to factual texts as well as stories. Current NLG systems do not do a good job of generating narratives, and this is a major source of user criticism. Generating good narratives is a challenge for all aspects of NLG, but the most fundamental challenge is probably in document structuring. References Computational linguistics Natural language processing Natural language generation