Text Generation and Systemic-Functional Linguistics: Experiences from English and Japanese (Communication in Artificial Intelligence) by Bateman, John A., Matthiessen, Christian M. I. M.: Acceptable hardcover (1991)

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Bibliographic Details

Title: Text Generation and Systemic-Functional Linguistics: Experiences from English and Japanese (Communication in Artificial Intelligence)
Publisher: UNKNO
Publication Date: 1991
Language: English
ISBN 10: 086187711X
ISBN 13: 9780861877119
Binding: hardcover
Condition: Acceptable
Book Type: book

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Synopsis

Text generation is the processing of information that is stored at a higher level than grammatical structures and lexical items (such as sentences and words), organizing and re-expressing it so that it can appear as a worded text. Of course it interests those working on artificial intelligence, but it should also interest linguists as a linguistic research task. The image of linguistics in computational areas is often derived from Chomsky's work, but this is limited because there are many areas crucial to computational linguistics - discourse, context and register, for instance - which fall outside Chomskyan theorizing. For this reason Matthiessen and Bateman prefer to use systemic linguistics, which interprets and represents language not as a rule-system for generating structures but as a resource for expressing and making meanings. There is a similarity between problem-solving in artificial intelligence and the systemic-functional approach to language developed by Hallida and adopted by Matthiessen and Bateman. Both involve the use of a network of inter-related choice points (a system network) making explicit what resources are available. Using examples from English and Japanese the authors explain what systemic-functional linguistics is, and how it can be useful in the task of text generation.

Synopsis

Text generation is the processing of information that is stored at a higher level than grammatical structures and lexical items (such as sentences and words), organizing and re-expressing it so that it can appear as a worded text. Of course it interests those working on artificial intelligence, but it should also interest linguists as a linguistic research task. The image of linguistics in computational areas is often derived from Chomsky's work, but this is limited because there are many areas crucial to computational linguistics - discourse, context and register, for instance - which fall outside Chomskyan theorizing. For this reason Matthiessen and Bateman prefer to use systemic linguistics, which interprets and represents language not as a rule-system for generating structures but as a resource for expressing and making meanings. There is a similarity between problem-solving in artificial intelligence and the systemic-functional approach to language developed by Hallida and adopted by Matthiessen and Bateman. Both involve the use of a network of inter-related choice points (a system network) making explicit what resources are available.

Using examples from English and Japanese the authors explain what systemic-functional linguistics is, and how it can be useful in the task of text generation.

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