'Healthy' Coreference: Applying Coreference Resolution to the Health Education Domain
David Z. Hirtle · UWSpace (University of Waterloo) · 2008
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii This thesis investigates coreference and its resolution within the domain of health education. Coreference is the relationship between two linguistic expressions that refer to the same real-world entity, and resolution involves identifying this rela-tionship among sets of referring expressions. The coreference resolution task is considered among the most difficult of problems in Artificial Intelligence; in some cases, resolution is impossible even for humans. For example, she in the sentence Lynn called Jennifer while she was on vacation is genuinely ambiguous: the vaca-tioner could be either Lynn or Jennifer. There are three primary motivations for this thesis. The first is that health edu-cation has never before been studied in this context. So far, the vast majority of