Abstract
This paper presents a framework to infer spatial knowledge from verbal semantic role representations. First, we generate potential spatial knowledge deterministically. Second, we determine whether it can be inferred and a degree of certainty. Inferences capture that something is located or is not located somewhere, and temporally anchor this information. An annotation effort shows that inferences are ubiquitous and intuitive to humans.
Cite
CITATION STYLE
Blanco, E., & Vempala, A. (2015). Inferring temporally-anchored spatial knowledge from semantic roles. In NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 452–461). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-1048
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