Understanding computers and cognition
Understanding computers and cognition
Implementing a semantic interpreter using conceptual graphs
IBM Journal of Research and Development
Natural Language Information Processing: A Computer Grammmar of English and Its Applications
Natural Language Information Processing: A Computer Grammmar of English and Its Applications
Augmented phrase structure grammars
TINLAP '75 Proceedings of the 1975 workshop on Theoretical issues in natural language processing
Semantically significant patterns in dictionary definitions
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
Conceptual graphs for the analysis and generation of sentences
IBM Journal of Research and Development
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A system has been developed to find the most likely attachment for prepositional phrases in English sentences in a fairly unrestricted way. The system receives as input a syntactic sentence parse provided by a general-purpose computational grammar called PEG (PLNLP English Grammar) The semantic decision that is necessary to make the right attachments is made (a) by parsing (also with PEG) the natural language definitions of an online standard dictionary, in this case Webster's Seventh New Collegiate Dictionary; (b) by relating words to other words in the dictionary; and (c) by reasoning heuristically about the comparative likelihood of different possible attachments. The basic assumption of this research is that natural language itself is a knowledge representation language that can be conveniently accessed and richly exploited. Techniques such as those presented here offer hope for eliminating the time-consuming and often incomplete hand coding of semantic information that has been conventional in natural language understanding systems.