Inferring Temporally-Anchored Spatial Knowledge from Semantic Roles
نویسندگان
چکیده
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.
منابع مشابه
Complementing Semantic Roles with Temporally Anchored Spatial Knowledge: Crowdsourced Annotations and Experiments
This paper presents a framework to infer spatial knowledge from semantic role representations. We infer whether entities are or are not located somewhere, and temporally anchor this spatial information. A large crowdsourcing effort on top of OntoNotes shows that these temporally-anchored spatial inferences are ubiquitous and intuitive to humans. Experimental results show that inferences can be ...
متن کاملAnnotating Temporally-Anchored Spatial Knowledge on Top of OntoNotes Semantic Roles
This paper presents a two-step methodology to annotate spatial knowledge on top of OntoNotes semantic roles. First, we manipulate semantic roles to automatically generate potential additional spatial knowledge. Second, we crowdsource annotations with Amazon Mechanical Turk to either validate or discard the potential additional spatial knowledge. The resulting annotations indicate whether entiti...
متن کاملNarrative reasoning for cognitive ubiquitous robots
The symbolic spatio-temporal reasoning is one of the major research challenges aiming to increase the autonomy and cognitive capabilities of ubiquitous robots in ambient intelligent systems. In these environments, there are several situations that are governed by complex processes and where multiple events must be correlated with respect to their spatial and temporal ordering to infer the right...
متن کاملExtracting Wikipedia Historical Attributes Data
In this paper, we describe the collection of a large structured dataset of temporally anchored relational data, obtained from the full revision history of the English Wikipedia. By mining (attribute, value) pairs from this revision history, we are able to collect a comprehensive, temporally-aware knowledge base that contains data on how attributes change over time. We discuss different characte...
متن کاملOntological Description of Image Content Using Regions Relationships
Rapid growth in the volume of multimedia information creates new challenges for information retrieval and sharing, and thus anticipates the emergence of the Semantic Web [2, 3]. The principal component in most of multimedia applications is the use of visual information and new approaches are essential to improve the inferring of semantic relationships from low-level features for semantic image ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015