%0 Conference Paper %1 rink2012determining %A Rink, Bryan %A Harabagiu, Sanda %B 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 %C Stroudsburg, PA, USA %D 2012 %I Association for Computational Linguistics %K relational semeval2012 similarity utd %P 413--418 %T UTD: Determining Relational Similarity Using Lexical Patterns %U http://dl.acm.org/citation.cfm?id=2387636.2387702 %X In this paper we present our approach for assigning degrees of relational similarity to pairs of words in the SemEval-2012 Task 2. To measure relational similarity we employed lexical patterns that can match against word pairs within a large corpus of 12 million documents. Patterns are weighted by obtaining statistically estimated lower bounds on their precision for extracting word pairs from a given relation. Finally, word pairs are ranked based on a model predicting the probability that they belong to the relation of interest. This approach achieved the best results on the SemEval 2012 Task 2, obtaining a Spearman correlation of 0.229 and an accuracy on reproducing human answers to MaxDiff questions of 39.4%.

@inproceedings{rink2012determining, abstract = {In this paper we present our approach for assigning degrees of relational similarity to pairs of words in the SemEval-2012 Task 2. To measure relational similarity we employed lexical patterns that can match against word pairs within a large corpus of 12 million documents. Patterns are weighted by obtaining statistically estimated lower bounds on their precision for extracting word pairs from a given relation. Finally, word pairs are ranked based on a model predicting the probability that they belong to the relation of interest. This approach achieved the best results on the SemEval 2012 Task 2, obtaining a Spearman correlation of 0.229 and an accuracy on reproducing human answers to MaxDiff questions of 39.4%.}, acmid = {2387702}, added-at = {2016-06-30T15:07:08.000+0200}, address = {Stroudsburg, PA, USA}, author = {Rink, Bryan and Harabagiu, Sanda}, biburl = {https://www.bibsonomy.org/bibtex/2f45a3fd9b34d25b0bebb80ba6824ca1e/thoni}, booktitle = {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}, interhash = {de03faa3f5e6d942dc5ae78d0650b306}, intrahash = {f45a3fd9b34d25b0bebb80ba6824ca1e}, keywords = {relational semeval2012 similarity utd}, location = {Montr\éal, Canada}, numpages = {6}, pages = {413--418}, publisher = {Association for Computational Linguistics}, series = {SemEval '12}, timestamp = {2016-09-06T08:23:07.000+0200}, title = {UTD: Determining Relational Similarity Using Lexical Patterns}, url = {http://dl.acm.org/citation.cfm?id=2387636.2387702}, year = 2012 }