Learning Subjective Adjectives from Corpora
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
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
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
Semi-supervised modeling for prenominal modifier ordering
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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The preferred order of pre-nominal adjectives in English is determined primarily by semantics. Nevertheless, Adjective Ordering (AO) systems do not generally exploit semantic features. This paper describes a system that orders adjectives with significantly above-chance accuracy (73.0%) solely on the basis of semantic features pertaining to the cognitive-semantic dimension of subjectivity. The results indicate that combining such semantic approaches with current methods could result in more accurate and robust AO systems.