Abstract
In order to demonstrate its understanding of an editorial, OpEd must be able to answer questions about the issues addressed in that editorial. Chapter 1 established that question answering in OpEd is characterized in terms of three processes: (1) understanding questions from the perspective of the editorial’s memory representation, or argument graph; (2) retrieving conceptual answers from the argument graph; and (3) generating conceptual answers in natural language. Furthermore, Chapter 1 indicated that question comprehension is performed by the same conceptual parser used for editorial comprehension, and answer generation is performed by a recursive-descent, English generator. This chapter examines the techniques used in the process of retrieving information from conceptual representations of editorials.KeywordsSteel IndustryMemory SearchNormal ProfitCausal BeliefREAGAN AdministrationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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