Interpreting Natural Language Database Updates.
STANFORD UNIV CA DEPT OF COMPUTER SCIENCE
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Although the problems of querying databases in natural language are well understood, the performance of database updates via natural language introduces additional difficulties. This thesis examines the problems encountered in interpreting natural language updates, and describes an implemented system that performs simple updates. The difficulties associated with natural language updates result from the fact that the user will naturally phrase requests with respect to his conception of the domain, which may be a considerable simplification of the actual underlying database structure. Updates that are meaningful and unambiguous from the users standpoint may not translate into reasonable changes to the underlying database. The PIQUE system Program for Interpretation of Queries and Updates in English operates by maintaining a simple model of the user and interpreting update requests with respect to that model. For a given request, a limited set of candidate updates alternative ways of fulfilling the request are considered, and ranked according to a set of domain-independent heuristics that reflect general properties of reasonable update. The leading candidate may be performed, or the highest ranking alternatives presented to the user for selection. The resultant action may also include a warning to the user about unanticipated side effects, or an explanation for the failure to fulfill a request. This thesis describes the PIQUE system in detail, presents examples of its operation, and discusses the effectiveness of the system with respect to coverage, accuracy, efficiency, and portability. The range of behaviors required for natural language update systems in general is discussed, and implications of updates on the design of data models are briefly considered.
- Computer Programming and Software