This paper presents an explanatory overview of a large and complex grammar, DIAGRAM, that is used in a computer system for interpreting English dialogue. DIAGRAM analyzes all of the basic kinds of phrases and sentences and many quite complex ones as well.
This paper discusses two problems central to the interpretation of utterances: determining the relationship between actions described in an utterance and events in the world, and inferring the ``state of the world’’ from utterances.
The importance of spatial and other metaphors is demonstrated. An approach to handling metaphor in a computational framework is described, based on the idea of selective inferencing.
In this paper, a framework for investigating conversation, which for convenience will be called the Planning Approach, is developed from this hypothesis.
Texts are viewed as purposeful transactions whose interpretation requires inferences based on extra-linguistic as well as on linguistic information. Text processors are viewed as systems that model both a theory of text and a theory of information processing.
This paper shows how a simple label propagation technique, in conjunction with some novel ideas about how labels can be applied to an image to express semantic knowledge, lead to the simplification of a number of diverse and difficult image analysis tasks.
We have substantially expanded the capabilities of the data base access component that serves as the interface between the natural-language front end of LADDER and the data base management systems on which the data is actually stored.
This paper describes the basic strategies of automatic problem solving, and then focuses on a variety of tactics for improving their efficiency. An attempt is made to provide some perspective on and structure to the set of tactics.
This paper evaluates the capabilities of natural language processing systems against these requirements and identifies crucial areas for future research in language processing, common-sense reasoning, and their coordination.
