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The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations

机译:Cogalex-V分享任务是基于语料库的语义关系的识别

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The shared task of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex-V) aims at providing a common benchmark for testing current corpus-based methods for the identification of lexical semantic relations (synonymy, antonymy, hypemymy, part-whole meronymy) and at gaining a better understanding of their respective strengths and weaknesses. The shared task uses a challenging dataset extracted from EVALution 1.0 (Santus et al., 2015b), which contains word pairs holding the above-mentioned relations as well as semantically unrelated control items (random). The task is split into two subtasks: (i) identification of related word pairs vs. unrelated ones; (ii) classification of the word pairs according to their semantic relation. This paper describes the subtasks, the dataset, the evaluation metrics, the seven participating systems and their results. The best performing system in subtask 1 is GHHH (F_1 = 0.790), while the best system in subtask 2 is LexNet (F_1 = 0.445).'
机译:第5次研讨会的共同任务局部关于莱克西森的认知方面(Cogalex-V)的旨在为测试基于语料库的方法进行识别的识别词汇语义关系,提供共同的基准(同义词,对抗洋,半孟喻)并且在更好地了解他们各自的优势和劣势。共享任务使用从评估1.0中提取的具有挑战性的数据集(Santus等,2015b),其中包含持有上述关系的字对对以及语义无关控制项(随机)。该任务分为两个子任务:(i)识别相关词对与不相关的字段; (ii)根据他们的语义关系进行单词对的分类。本文介绍了子任务,数据集,评估度量,七个参与系统及其结果。子任务1中的最佳执行系统是GHHH(F_1 = 0.790),而子任务2中的最佳系统是LexNet(F_1 = 0.445)。

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