Skip Nav Destination
Close Modal
Update search
NARROW
Format
Journal
Date
Availability
1-1 of 1
Robert Rubinoff
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Publisher: Journals Gateway
Computational Linguistics (2000) 26 (2): 107–138.
Published: 01 June 2000
Abstract
View article
PDF
Natural language generation is usually divided into separate text planning and linguistic components. This division, though, assumes that the two components can operate independently, which is not always true. The IGEN generator eliminates the need for this assumption; it handles interactions between the components without sacrificing the advantages of modularity. IGEN accomplishes this by means of annotations that its linguistic component places on the structures it builds; these annotations provide an abstract description of the effects of particular linguistic choices, allowing the planner to evaluate these choices without needing any linguistic knowledge. This approach allows IGEN to vary the work done by each component independently, even in cases where the final output depends on interactions between them. In addition, since IGEN explicitly models the effects of linguistic choices, it can gracefully handle situations where the available time or linguistic resources are limited.