Damaris M. Ayuso

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This paper reports a handful of experiments designed to test the feasibility of applying well-known partial parsing techniques to the problem of automatic data base update from an open-ended source of messages, and the feasiblity of automatically learning semantic knowledge from annotated examples. The challenges arise from the incompleteness of any(More)
APPROACH Traditional approaches to the problem of extracting data from texts have emphasized hand-crafted linguisti c knowledge. In contrast, BBN's PLUM system (Probabilistic Language Understanding Model) was developed as par t of an ARPA-funded research effort on integrating probabilistic language models with more traditional linguisti c techniques. Our(More)
An improved version of IRACQ (for Interpretation Rule ACQuisition) is presented. I Our approach to semantic knowledge acquisition: 1) is in the context of a general purpose NL interface rather than one that accesses only databases, 2) employs a knowledge representation formalism with limited inferencing capabilities, 3) assumes a trained person but not an(More)
This paper addresses issues that arose in applying the model for discourse entity (DE) generation in B. Webber's work (1978, 1983) to an interactive multi-modal interface. Her treatment was extended in 4 areas: (1)the notion of context dependence of DEs was formalized in an intensional logic, (2)the treatment of DEs for indefinite NPs was modified to use(More)
Although natural language technology has achieved a high degree of domain independence through separating domain-independent modules from domain-dependent knowledge bases, portability, as measured by effort to move from one application to another, is still a problem. Here we describe a knowledge acquisition tool (KNACQ) that has sharply decreased our effort(More)