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Bootstrapping Location Relations from Text

Wu Zheng and Catherine Blake

(Submission #114)


Ontologies play a critical role in information organization and can be used for a range of applications from information retrieval to knowledge discovery. However, manual ontology construction is extremely labor intensive. This paper describes a bootstrapping algorithm that, when provided with a seed term, automatically induces relations from text. We describe a series of experiments that explore the role of sentence syntax during the bootstrapping process and demonstrate the feasibility of this approach by identifying a primitive instance-level relation – the location relation, which is of interest because locations are described in multiple genres, such as in the news, novels and scientific articles. Our results suggest that syntax plays a critical role in identifying location relations.


Program Track:  Track 2 - Knowledge Organization
Submission Type:  Research Paper


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