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.
REF propose a method to infer temporally-anchored spatial knowledge from semantic roles.
Inferring Temporally-Anchored Spatial Knowledge from Semantic Roles
HLT-NAACL
Computer Science