Contextual correlates of synonymy
Communications of the ACM
Placing search in context: the concept revisited
ACM Transactions on Information Systems (TOIS)
Evaluating Natural Language Processing Systems: An Analysis and Review
Evaluating Natural Language Processing Systems: An Analysis and Review
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Similarity of Semantic Relations
Computational Linguistics
A study on similarity and relatedness using distributional and WordNet-based approaches
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
Distributional memory: A general framework for corpus-based semantics
Computational Linguistics
Entailment above the word level in distributional semantics
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Identifying hypernyms in distributional semantic spaces
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
A study of hybrid similarity measures for semantic relation extraction
HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
Looking at word meaning: an interactive visualization of semantic vector spaces for Dutch synsets
EACL 2012 Proceedings of the EACL 2012 Joint Workshop of LINGVIS & UNCLH
Proceedings of the 20th ACM international conference on Multimedia
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We introduce BLESS, a data set specifically designed for the evaluation of distributional semantic models. BLESS contains a set of tuples instantiating different, explicitly typed semantic relations, plus a number of controlled random tuples. It is thus possible to assess the ability of a model to detect truly related word pairs, as well as to perform in-depth analyses of the types of semantic relations that a model favors. We discuss the motivations for BLESS, describe its construction and structure, and present examples of its usage in the evaluation of distributional semantic models.