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)
Discourse comprises those phenomena that usually do not arise when processing a single sentence . It appears to be the most difficult and probably the least understood aspect of automated message understanding. Five out of fifteen sites on a MUC-3 survey listed discourse as their main weakness and an area in which t o concentrate future research . Virtually(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 multimodal 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)
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 a s part of a DARPA-funded research effort on integrating probabilistic language models with more traditional linguistic techniques . Our research(More)
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 research(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)
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)
In order to meet the information processing demands of the next decade, natural language systems must have the capability of processing very large amounts of text, commonly called "messages", from highly diverse sources written in any of a few dozen languages. One of the key issues in building systems with this scale of competence is handling large numbers(More)