From sensors to sense: Integrated heterogeneous ontologies for natural language generation

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Abstract

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.

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APA

Pomarlan, M., Porzel, R., Bateman, J., & Malaka, R. (2018). From sensors to sense: Integrated heterogeneous ontologies for natural language generation. In INLG 2018 - Workshop on NLG for Human-Robot Interaction, Proceedings of the Workshop (pp. 17–21). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-6904

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