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.- Anthology ID:
- W18-6904
- Volume:
- Proceedings of the Workshop on NLG for Human–Robot Interaction
- Month:
- November
- Year:
- 2018
- Address:
- Tilburg, The Netherlands
- Editors:
- Mary Ellen Foster, Hendrik Buschmeier, Dimitra Gkatzia
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 17–21
- Language:
- URL:
- https://aclanthology.org/W18-6904
- DOI:
- 10.18653/v1/W18-6904
- Cite (ACL):
- Mihai Pomarlan, Robert Porzel, John Bateman, and Rainer Malaka. 2018. From sensors to sense: Integrated heterogeneous ontologies for Natural Language Generation. In Proceedings of the Workshop on NLG for Human–Robot Interaction, pages 17–21, Tilburg, The Netherlands. Association for Computational Linguistics.
- Cite (Informal):
- From sensors to sense: Integrated heterogeneous ontologies for Natural Language Generation (Pomarlan et al., INLG 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-6904.pdf