Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Trainable methods for surface natural language generation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Exploiting a probabilistic hierarchical model for generation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Evaluating coverage for large symbolic NLG grammars
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Stochastic realisation ranking for a free word order language
ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation
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Recent evaluation techniques applied to corpus-based systems have been introduced that can predict quantitatively how well surface realizers will generate unseen sentences in isolation. We introduce a similar method for determining the coverage on the Fuf/Surge symbolic surface realizer, report that its coverage and accuracy on the Penn TreeBank is higher than that of a similar statistics-based generator, describe several benefits that can be used in other areas of computational linguistics, and present an updated version of Surge for use in the NLG community.