Content Selection Challenge - University of Aberdeen Entry

Bouayad-Agha et al. (2012) issued a content determination challenge in which researchers were asked to create systems that can automatically select content suitable for a first paragraph in a Wikipedia article from an RDF knowledge base of information about people. This article is a description of the system built at the University of Aberdeen. Our working assumption is that the target text should contain information that is commonly known about the target person. The Wikipedia’s manual of style mentions that “The lead [section] serves as an introduction to the article and a summary of its most important aspects1.” What is most important about a person is likely to be often mentioned in biographies and hence it is more likely to be commonly known. Our system was motivated by the notion of common ground, especially the way it was accounted for by (Clark and Marshall, 1981). Clark and Marshall (1981) introduce two categories of common ground: personal common ground shared by a small group of individuals and communal common ground shared by a community of people. We are most interested in the concept of communal common ground, which arises from the exposure to the same information within a community. For example, if there is a statue in front of your work place, you expect your colleagues to also know about this statue and so the information that there is a statue in front of you workplace becomes a part of the community knowledge (where the community are people who work at the same place). Our hypothesis is that if we take a corpus of documents produced by some large community (e.g., English speakers), we should be able to ap-