ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
The order of prenominal adjectives in natural language generation
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Discriminative Reranking for Natural Language Parsing
Computational Linguistics
Class-based ordering of prenominal modifiers
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Prenominal modifier ordering via multiple sequence alignment
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
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In this work, we present a novel approach to the generation task of ordering prenominal modifiers. We take a maximum entropy reranking approach to the problem which admits arbitrary features on a permutation of modifiers, exploiting hundreds of thousands of features in total. We compare our error rates to the state-of-the-art and to a strong Google n-gram count baseline. We attain a maximum error reduction of 69.8% and average error reduction across all test sets of 59.1% compared to the state-of-the-art and a maximum error reduction of 68.4% and average error reduction across all test sets of 41.8% compared to our Google n-gram count baseline.