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https://doi.org/10.3115/991250...
Article . 1994 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 1995
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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NL understanding with a grammar of constructions

Authors: David E. Johnson; Wlodek Zadrozny; Leora Morgenstern; Stanislaw Jarecki; Marcin Szummer;

NL understanding with a grammar of constructions

Abstract

We present an approach to natural language understanding based on a computable grammar of constructions. A "construction" consists of a set of features of form and a description of meaning in a context. A grammar is a set of constructions. This kind of grammar is the key element of Mincal, an implemented natural language, speech-enabled interface to an on-line calendar system. The system consists of a NL grammar, a parser, an on-line calendar, a domain knowledge base (about dates, times and meetings), an application knowledge base (about the calendar), a speech recognizer, a speech generator, and the interfaces between those modules. We claim that this architecture should work in general for spoken interfaces in small domains. In this paper we present two novel aspects of the architecture: (a) the use of constructions, integrating descriptions of form, meaning and context into one whole; and (b) the separation of domain knowledge from application knowledge. We describe the data structures for encoding constructions, the structure of the knowledge bases, and the interactions of the key modules of the system.

appeared in Proc. Coling'94, Kyoto, Japan, 1994; 5 postscript pages; email to wlodz@watson.ibm.com

Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
bronze