| ## Overview | |
| Original dataset available [here](https://github.com/sheng-z/JOCI/tree/master/data). | |
| This dataset is the "full" JOCI dataset, which is the file named `joci.csv.zip`. | |
| # Dataset curation | |
| The following processing is applied, | |
| - `label` column renamed to `original_label` | |
| - creation of the `label` column using the following mapping, using common practices ([1](https://github.com/rabeehk/robust-nli/blob/c32ff958d4df68ac2fad9bf990f70d30eab9f297/data/scripts/joci.py#L22-L27), [2](https://github.com/azpoliak/hypothesis-only-NLI/blob/b045230437b5ba74b9928ca2bac5e21ae57876b9/data/convert_joci.py#L7-L12)) | |
| ``` | |
| { | |
| 0: "contradiction", | |
| 1: "contradiction", | |
| 2: "neutral", | |
| 3: "neutral", | |
| 4: "neutral", | |
| 5: "entailment", | |
| } | |
| ``` | |
| - finally, converting this to the usual NLI classes, that is `{"entailment": 0, "neutral": 1, "contradiction": 2}` | |
| ## Code to create dataset | |
| ```python | |
| import pandas as pd | |
| from datasets import Features, Value, ClassLabel, Dataset | |
| # read data | |
| df = pd.read_csv("<path to folder>/joci.csv") | |
| # column name to lower | |
| df.columns = df.columns.str.lower() | |
| # rename label column | |
| df = df.rename(columns={"label": "original_label"}) | |
| # encode labels | |
| df["label"] = df["original_label"].map({ | |
| 0: "contradiction", | |
| 1: "contradiction", | |
| 2: "neutral", | |
| 3: "neutral", | |
| 4: "neutral", | |
| 5: "entailment", | |
| }) | |
| # encode labels | |
| df["label"] = df["label"].map({"entailment": 0, "neutral": 1, "contradiction": 2}) | |
| # cast to dataset | |
| features = Features({ | |
| "context": Value(dtype="string"), | |
| "hypothesis": Value(dtype="string"), | |
| "label": ClassLabel(num_classes=3, names=["entailment", "neutral", "contradiction"]), | |
| "original_label": Value(dtype="int32"), | |
| "context_from": Value(dtype="string"), | |
| "hypothesis_from": Value(dtype="string"), | |
| "subset": Value(dtype="string"), | |
| }) | |
| ds = Dataset.from_pandas(df, features=features) | |
| ds.push_to_hub("joci", token="<token>") | |
| ``` | |