We propose the combination of a robotics ontology (KnowRob) with a linguistically motivated one (GUM) under the upper ontology DUL. We use the DUL Event, Situation, Description pattern to formalize reasoning techniques to convert between a robot’s beliefstate and its linguistic utterances. We plan to employ these techniques to equip robots with a reason-aloud ability, through which they can explain their actions as they perform them, in natural language, at a level of granularity appropriate to the user, their query and the context at hand.

This paper presents a multilingual Natural Language Generation system that produces technical instruction texts in Bulgarian, Czech and Russian. It generates several types of texts, common for software manuals, in two styles. We illustrate the system’s functionality with examples of its input and output behaviour. We discuss the criteria and procedures adopted for evaluating the system and summarise their results. The system embodies novel approaches to providing multilingual documentation, ranging from the re-use of a large-scale, broad coverage grammar of English in order to develop the lexico-grammatical resources necessary for the generation in the three target languages, through to the adoption of a ‘knowledge editing’ approach to specifying the desired content of the texts to be generated independently of the target languages in which those texts finally appear.