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## Overview
Original dataset available [here](https://gluebenchmark.com/diagnostics).
## Dataset curation
Filled in the empty rows of columns "lexical semantics", "predicate-argument structure",
"logic", "knowledge" with empty string `""`.
Labels are encoded as follows
```
{"entailment": 0, "neutral": 1, "contradiction": 2}
```
## Code to create dataset
```python
import pandas as pd
from datasets import Features, Value, ClassLabel, Dataset
df = pd.read_csv("<path to file>/diagnostic-full.tsv", sep="\t")
# column names to lower
df.columns = df.columns.str.lower()
# fill na
assert df["label"].isna().sum() == 0
df = df.fillna("")
# encode labels
df["label"] = df["label"].map({"entailment": 0, "neutral": 1, "contradiction": 2})
# cast to dataset
features = Features({
"lexical semantics": Value(dtype="string", id=None),
"predicate-argument structure": Value(dtype="string", id=None),
"logic": Value(dtype="string", id=None),
"knowledge": Value(dtype="string", id=None),
"domain": Value(dtype="string", id=None),
"premise": Value(dtype="string", id=None),
"hypothesis": Value(dtype="string", id=None),
"label": ClassLabel(num_classes=3, names=["entailment", "neutral", "contradiction"]),
})
dataset = Dataset.from_pandas(df, features=features)
dataset.push_to_hub("glue_diagnostics", token="<token>", split="test")
```
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