Document Structuring is a subtask of Natural language generation, which involves deciding the order and grouping (for example into paragraphs) of sentences in a generated text. It is closely related to the Content determination NLG task. Example Assume we have four sentences which we want to include in a generated text It will rain on Saturday It will be sunny on Sunday Max temperature will be 10 °C on Saturday Max temperature will be 15 °C on Sunday There are 24 (4!) orderings of these messages, including (1234) It will rain on Saturday. It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. (2341) It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. It will rain on Saturday. (4321) Max temperature will be 15 °C on Sunday. Max temperature will be 10 °C on Saturday. It will be sunny on Sunday. It will rain on Saturday. Some of these orderings are better than others. For example, of the texts shown above, human readers prefer (1234) over (2314) and (4321). For any ordering, there are also many ways in which sentences can be grouped into paragraphs and higher-level structures such as sections. For example, there are 8 (2**3) ways in which the sentences in (1234) can be grouped into paragraphs, including (12)(34) It will rain on Saturday. It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. (1)(23)(4) It will rain on Saturday. It will be sunny on Sunday. Max temperature will be 10 °C on Saturday. Max temperature will be 15 °C on Sunday. As with ordering, human readers prefer some groupings over others; for example, (12)(34) is preferred over (1)(23)(4). The document structuring task is to choose an ordering and grouping of sentences which results in a coherent and well-organised text from the reader's perspective. Algorithms and models There are three basic approaches to document structuring: schemas, corpus-based, and heuristic. Schemas are templates which explicitly specify sentence ordering and grouping for a document (as well as Content determination information). Typically they are constructed by manually analysing a corpus of human-written texts in the target genre, and extracting a document template from these texts. Schemas work well in practice for texts which are