Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
The syntactic process
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
The kappa statistic: a second look
Computational Linguistics
Generative models for statistical parsing with Combinatory Categorial Grammar
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Parsing the WSJ using CCG and log-linear models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Wide-coverage semantic representations from a CCG parser
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Investigating the effects of selective sampling on the annotation task
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Entity discovery and assignment for opinion mining applications
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Towards a computational treatment of superlatives
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
Mining opinions in comparative sentences
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Computing genitive superlatives
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
Sentiment analysis of conditional sentences
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
TextWiki: a superlative resource
Language Resources and Evaluation
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In this paper we introduce an empirical approach to the semantic interpretation of superlative adjectives. We present a corpus annotated for superlatives and propose an interpretation algorithm that uses a wide-coverage parser and produces semantic representations. We achieve F-scores between 0.84 and 0.91 for detecting attributive superlatives and an accuracy in the range of 0.69--0.84 for determining the correct comparison set. As far as we are aware, this is the first automated approach to superlatives for open-domain texts and questions.