Generating context-sensitive responses to object-related misconceptions
Artificial Intelligence
Semantic-head-driven generation
Computational Linguistics
An integrated approach to generation using systemic grammars and tree adjoining grammars
An integrated approach to generation using systemic grammars and tree adjoining grammars
Systemic Text Generation as Problem Solving
Systemic Text Generation as Problem Solving
TAGs as a grammatical formalism for generation
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Salience: the key to the selection problem in natural language generation
ACL '82 Proceedings of the 20th annual meeting on Association for Computational Linguistics
Parsing strategies with 'lexicalized' grammars: application to tree adjoining grammars
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 2
A uniform method of grammar extraction and its applications
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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It has been hypothesized that Tree Adjoining Grammar (TAG) is particularly well suited for sentence generation. It is unclear, however, how a sentence generation system based on TAG should choose among the syntactic possibilities made available in the grammar. In this paper we consider the question of what needs to be done to generate with TAGs and explain a generation system that provides the necessary features. This approach is compared with other TAG-based generation systems. Particular attention is given to Mumble-86 which, like our system, makes syntactic choice on sophisticated functional grounds.