Generalized augmented transition network grammars for generation from semantic networks
The augmented transition network (ATN) is a formalism for writing parsing grammars which has been much used in artificial intelligence and computational linguistics. A few researchers have also used ATNs for writing grammars for generating sentences. Previously, however, either generation ATNs did not have the same semantics as parsing ATNs, or they required an auxiliary mechanism to determine the syntactic structure of the sentence to be generated. This paper reports a generalization of the ATN formalism which allows ATN grammars to be written to parse labelled directed graphs. Specifically, an ATN grammar can be written to parse a semantic network and generate a surface string as its analysis. An example is given of a combined parsing-generating grammar which parses surface sentences, builds and queries a semantic network knowledge representation, and generates surface sentences in response. 8 references.
- Research Organization:
- State Univ. of New York, Amherst
- OSTI ID:
- 6412706
- Journal Information:
- Am. J. Comput. Ling.; (United States), Journal Name: Am. J. Comput. Ling.; (United States) Vol. 1; ISSN AJCLD
- Country of Publication:
- United States
- Language:
- English
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