Computer Engineering Commons^™

Universal Schema For Knowledge Representation From Text And Structured Data, Limin Yao

Doctoral Dissertations

In data integration we transform information from a source into a target schema. A general problem in this task is loss of fidelity and coverage: the source expresses more knowledge than that can be fit into the target schema, or knowledge that is hard to fit into any schema at all. This problem is taken to an extreme in information extraction (IE) where the source is natural language---one of the most expressive forms of knowledge representation. To address this issue, one can either automatically learn a latent schema emergent in text (a brittle and ill-defined task), or manually define schemas. …