Machine Reading as a Process of Partial Question-Answering

This paper explores the close relationship between question answering and machine reading, and how the active use of reasoning to answer (and in the process, disambiguate) questions can also be applied to reading declarative texts, where a substantial proportion of the text’s contents is already known to (represented in) the system. In question answering, a question may be ambiguous, and it may only be in the process of trying to answer it that the "right" way to disambiguate it becomes apparent. Similarly in machine reading, a text may be ambiguous, and may require some process to relate it to what is already known. Our conjecture in this paper is that these two processes are similar, and that we can modify a question answering tool to help "read" new text that augments existing system knowledge. Specifically, interpreting a new text T can be recast as trying to answer, or partially answer, the question "Is it true that T?", resulting in both appropriate disambiguation and connection of T to existing knowledge. Some preliminary investigation suggests this might be useful for proposing knowledge base extensions, extracted from text, to a knowledge engineer.