Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
natural-language-inference
Languages:
Polish
Size:
10K - 100K
License:
Commit
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Parent(s):
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Update README.md (#2)
Browse files- Update README.md (30ef48bbe1c91c457efb1d212e7b1e6fbd7e5868)
Co-authored-by: Albert Sawczyn <asawczyn@users.noreply.huggingface.co>
README.md
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@@ -33,18 +33,23 @@ Although the SICK corpus inspires the main design of the dataset, it differs in
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The entailment relation between two sentences is labeled with *entailment*, *contradiction*, or *neutral*. The task is to predict if the premise entails the hypothesis (entailment), negates the hypothesis (contradiction), or is unrelated (neutral).
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**Input**: ('sentence_A', 'sentence_B'): sentence pair
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**Output** ('entailment_judgment' column): one of the possible entailment relations (*entailment*, *contradiction*, *neutral*)
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**Domain:** image captions
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Żaden mężczyzna nie stoi na przystanku autobusowym. (Eng. No man standing at the bus stop.) vs. Mężczyzna z żółtą i białą reklamówką w ręce stoi na przystanku obok autobusu. (Eng. A man with a yellow and white commercial in his hand stands at a bus stop next to a bus.) → **entailment**
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## Data splits
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The entailment relation between two sentences is labeled with *entailment*, *contradiction*, or *neutral*. The task is to predict if the premise entails the hypothesis (entailment), negates the hypothesis (contradiction), or is unrelated (neutral).
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b **entails** a (a **wynika z** b) – if a situation or an event described by sentence b occurs, it is recognized that a situation or an event described by a occurs as well, i.e., a and b refer to the same event or the same situation;
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**Input**: ('sentence_A', 'sentence_B'): sentence pair
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**Output** ('entailment_judgment' column): one of the possible entailment relations (*entailment*, *contradiction*, *neutral*)
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**Domain:** image captions
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**Measurements**: Accuracy
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**Example:**
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Input: `Żaden mężczyzna nie stoi na przystanku autobusowym.` ; `Mężczyzna z żółtą i białą reklamówką w ręce stoi na przystanku obok autobusu.`
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Input (translated by DeepL): `No man standing at the bus stop.` ; `A man with a yellow and white bag in his hand stands at a bus stop next to a bus.`
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Output: `entailment`
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## Data splits
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