A Computational Analysis of Information Structure Using Parallel Expository Texts in English and Japanese

This thesis concerns the notion of 'information structure': informally, organization of information in an utterance with respect to the context. Information structure has been recognized as a critical element in a number of computer applications: e.g., selection of contextually appropriate forms in machine translation and speech generation, and analysis of text readability in computer-assisted writing systems. One of the problems involved in these applications is how to identify information structure in extended texts. This problem is often ignored, assumed to be trivial, or reduced to a sub-problem that does not correspond to the complexity of realistic texts. A handful of computational proposals face the problem directly, but they are generally limited in coverage and all suffer from lack of evaluation. To fully demonstrate the usefulness of information structure, it is essential to apply a theory of information structure to the identification problem and to provide an evaluation method. This thesis adopts a classic theory of information structure as binomial partition between theme and rheme, and captures the property of theme as a requirement of the contextual-link status. The notion of 'contextual link ' is further specified in terms of discourse status, domain-specific knowledge, and linguistic marking. The relation between theme and rheme is identified as the semantic composition of the two, and linked to surfac