PARus

Choice of Plausible Alternatives for Russian language

Dataset Information
Modalities
Texts
Languages
Russian
Introduced
2020
License
Homepage

Overview

Choice of Plausible Alternatives for Russian language (PARus) evaluation provides researchers with a tool for assessing progress in open-domain commonsense causal reasoning. Each question in PARus is composed of a premise and two alternatives, where the task is to select the alternative that more plausibly has a causal relation with the premise. The correct alternative is randomized so that the expected performance of randomly guessing is 50%.

Task Type

Evaluation of commonsense causal reasoning

Sentence Pair Classification: suitable - not suitable

Example

{
  "premise": "Гости вечеринки прятались за диваном.",
  "choice1": "Это была вечеринка-сюрприз.",
  "choice2":"Это был день рождения.",
  "question": "cause",
  "label": 0,
  "idx": 4
}

How did we collect data?

All text examples were collected from open news sources and literary magazines, then manually reviewed and supplemented by a human assessment on Yandex.Toloka

Variants: PARus

Associated Benchmarks

This dataset is used in 1 benchmark:

Recent Benchmark Submissions

Task Model Paper Date
Common Sense Reasoning majority_class Unreasonable Effectiveness of Rule-Based Heuristics … 2021-05-03
Common Sense Reasoning Random weighted Unreasonable Effectiveness of Rule-Based Heuristics … 2021-05-03
Common Sense Reasoning heuristic majority Unreasonable Effectiveness of Rule-Based Heuristics … 2021-05-03
Common Sense Reasoning Human Benchmark RussianSuperGLUE: A Russian Language Understanding … 2020-10-29
Common Sense Reasoning Baseline TF-IDF1.1 RussianSuperGLUE: A Russian Language Understanding … 2020-10-29
Common Sense Reasoning MT5 Large mT5: A massively multilingual pre-trained … 2020-10-22

Research Papers

Recent papers with results on this dataset: