Similarity-Analogy-Relatedness for Tartar Language (SART) Dataset

A Similarity-Analogy-Relatedness for Tartar Language (SART) Dataset is a Benchmark Dataset that can be used in Word Embedding Benchmark and Semantic Word Similarity Benchmark Tasks.

• AKA: SART Dataset.
• Context:
  • Website: https://github.com/tat-nlp/SART
  • It was first introduced by Khusainova et al. (2019).
  • It is based on WordSim-353 Dataset.
• Example(s):
  • Semantic Word Similarity SART Dataset,
  • Word Analogy SART Dataset,
  • Word Relatedness SART Dataset,
  • ...
  • …
• Counter-Example(s):
  • a Semantic Word Similarity Dataset,
  • a Reading Comprehension Dataset,
  • a Question-Answer Dataset,
  • a Word Relatedness Dataset,
  • a Word Analogy Dataset.
• See: Training Dataset, Semantic Word Similarity Measure, Semantic Word Similarity System, SemEval-2017 Task 2, Reading Comprehension Dataset, Question-Answer Dataset.

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References

2019

• (Khusainova et al., 2019) ⇒ Albina Khusainova, Adil Khan, and Adin Ramirez Rivera (2019). "SART - Similarity, Analogies, and Relatedness for Tatar Language: New Benchmark Datasets for Word Embeddings Evaluation". In: arXiv:1904.00365

2002

• (Finkelstein et al., 2002) ⇒ Lev Finkelstein, Evgeniy Gabrilovich, Yossi Matias, Ehud Rivlin, Zach Solan, Gadi Wolfman, and Eytan Ruppin (2002). "Placing Search in Context: The Concept Revisited". In: ACM Transactions on Information Systems (TOIS), Volume 20.

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