SimLex-999 Dataset
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A SimLex-999 Dataset is a Semantic Word Similarity Dataset that can be used in a Semantic Word Similarity Benchmark Task.
- Context:
- It was first introduced by Hill et al. (2015).
- Example(s):
- Counter-Example(s):
- See: Training Dataset, Semantic Word Similarity Measure, Semantic Word Similarity System, SemEval-2017 Task 2, Reading Comprehension Dataset, Question-Answer Dataset.
References
2021
- (Simlex-Github, 2021) ⇒ https://fh295.github.io//simlex.html Retrieved:2021-07-18.
- QUOTE: SimLex-999 is a gold standard resource for the evaluation of models that learn the meaning of words and concepts.
SimLex-999 provides a way of measuring how well models capture similarity, rather than relatedness or association. The scores in SimLex-999 therefore differ from other well-known evaluation datasets such as WordSim-353 (...).
- QUOTE: SimLex-999 is a gold standard resource for the evaluation of models that learn the meaning of words and concepts.
2019
- (ACL, 2020) ⇒ https://aclweb.org/aclwiki/SimLex-999_(State_of_the_art) Last updated: 15 September 2019.
- QUOTE: SimLex-999 aims at a cleaner benchmark of similarity (but not relatedness). Pairs of words were chosen to represent different ranges of similarity and with either high or low association. Subjects were instructed to differentiate between similarity and relatedness and rate regarding the former only.
2017
- (Camacho-Collados et al., 2017) ⇒ Jose Camacho-Collados, aMohammad Taher Pilehvar, Nigel Collier, and Roberto Navigli. (2017). “SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity.” In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval@ACL 2017).
2015
- (Hill et al., 2015) ⇒ Felix Hill, Roi Reichart, and Anna Korhonen. (2015). “SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation.” In: Computational Linguistics, 41(4).