Paper: Learning Theories From Text

ACL ID C04-1027
Title Learning Theories From Text
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004

In this paper we describe a method of automati- cally learning domain theories from parsed cor- pora of sentences from the relevant domain and use FSA techniques for the graphical represen- tation of such a theory. By a ‘domain theory’ we mean a collection of facts and generalisations or rules which capture what commonly happens (or does not happen) in some domain of interest. As language users, we implicitly draw on such theories in various disambiguation tasks, such as anaphora resolution and prepositional phrase attachment, and formal encodings of domain theories can be used for this purpose in natural language processing. They may also be objects of interest in their own right, that is, as the out- put of a knowledge discovery process. The ap- proach is generizable to different dom...