Textual Entailment Recognition for Russian
Textual Entailment Recognition has been proposed recently as a generic task that captures major semantic inference needs across many NLP applications, such as Question Answering, Information Retrieval, Information Extraction, and Text Summarization. This task requires to recognize, given two text fragments, whether the meaning of one text is entailed (can be inferred) from the other text.
RTE (Recognizing Textual Entailment) Sentence Pair Classification - Entailment - Not Entailment
{
"premise": "Автор поста написал в комментарии, что прорвалась канализация.",
"hypothesis": "Автор поста написал про канализацию.",
"label": "entailment",
"idx": "6062"
}
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: TERRa
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Natural Language Inference | heuristic majority | Unreasonable Effectiveness of Rule-Based Heuristics … | 2021-05-03 |
Natural Language Inference | majority_class | Unreasonable Effectiveness of Rule-Based Heuristics … | 2021-05-03 |
Natural Language Inference | Random weighted | Unreasonable Effectiveness of Rule-Based Heuristics … | 2021-05-03 |
Natural Language Inference | Human Benchmark | RussianSuperGLUE: A Russian Language Understanding … | 2020-10-29 |
Natural Language Inference | Baseline TF-IDF1.1 | RussianSuperGLUE: A Russian Language Understanding … | 2020-10-29 |
Natural Language Inference | MT5 Large | mT5: A massively multilingual pre-trained … | 2020-10-22 |
Recent papers with results on this dataset: