A tractable machine dictionary as a resource for computational semantics
Computational lexicography for natural language processing
Word association norms, mutual information, and lexicography
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Principled disambiguation: discriminating adjective senses with modified nouns
Computational Linguistics
Human memory models and term association
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
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
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
A quantitative evaluation of linguistic tests for the automatic prediction of semantic markedness
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Augmenting lexicons automatically: clustering semantically related adjectives
HLT '93 Proceedings of the workshop on Human Language Technology
Knowledge-free discovery of domain-specific multiword units
Proceedings of the 2008 ACM symposium on Applied computing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SIGNUM: a graph algorithm for terminology extraction
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Corpus-based analysis of the co-occurrence of Chinese antonym pairs
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet
Language Resources and Evaluation
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Charles and Miller propose that lexical associations between antonymous adjectives are formed via their co-occurences within the same sentence (the co-occurrence hypothesis), rather than via their syntatic substitutability (the substitutability hypothesis), and that such co-occurrences must take place more often than expected by chance. This paper provides empirical support for the co-occurrence hypothesis in a corpus analysis of all high-frequency adjectives and their antonyms and of a major group of morphologically derived antonyms (e.g., impossible, un-happy). We show that very high co-occurrence rates do appear to characterize all antonymous adjective pairs, supporting the precondition for the formation of the association; and we find that the syntactic contexts of these co-occurrences raise the intrinsic associability of antonyms when they do co-occur. We show that via one of these patterns, mutual substitution within otherwise repeated phrases in a sentence, the co-occurrences hypothesis captures the generalizations that were the basis for the substitutability hypothesis for the formation of antonymic associations.