Plan recognition and discourse analysis: an integrated approach for understanding dialogues
Plan recognition and discourse analysis: an integrated approach for understanding dialogues
Introduction to artificial intelligence
Introduction to artificial intelligence
Motivation analysis, abductive unification, and nonmonotonic equality
Artificial Intelligence
A formalization of parsimonious covering and probabilistic reasoning in abductive diagnostic inference (expert systems, set, bayesian classification)
Word sense disambiguation in descriptive text interpretation: a dual-route parsimonious covering model
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
| Hi-index | 0.00 |
Many researchers believe that certain aspects of natural language processing, such as word sense disambiguation and plan recognition in stories, constitute abductive inferences. We have been working with a specific model of abduction, called parsimonious covering, applied in diagnostic problem solving, word sense disambiguation and logical form generation in some restricted settings. Diagnostic parsimonious covering has been extended into a dual-route model to account for syntactic and semantic aspects of natural language. The two routes of covering are integrated by defining "open class" linguistic concepts, aiding each other. The diagnostic model has dealt with sets, while the extended version, where syntactic considerations dictate word order, deals with sequences of linguistic concepts. Here we briefly describe the original model and the extended version, and briefly characterize the notions of covering and different criteria of parsimony. Finally we examine the question of whether parsimonious covering can serve as a general framework for parsing.