| ## Overview | |
| Proposed by | |
| ```latex | |
| @InProceedings{glockner_acl18, | |
| author = {Glockner, Max and Shwartz, Vered and Goldberg, Yoav}, | |
| title = {Breaking NLI Systems with Sentences that Require Simple Lexical Inferences}, | |
| booktitle = {The 56th Annual Meeting of the Association for Computational Linguistics (ACL)}, | |
| month = {July}, | |
| year = {2018}, | |
| address = {Melbourne, Australia} | |
| } | |
| ``` | |
| Original dataset available [here](https://github.com/BIU-NLP/Breaking_NLI). | |
| ## Dataset curation | |
| Labels encoded with the following mapping `{"entailment": 0, "neutral": 1, "contradiction": 2}` | |
| and made available in the `label` column. | |
| ## Code to create the dataset | |
| ```python | |
| import pandas as pd | |
| from datasets import Features, Value, ClassLabel, Dataset, Sequence | |
| # load data | |
| with open("<path to folder>/dataset.jsonl", "r") as fl: | |
| data = fl.read().split("\n") | |
| df = pd.DataFrame([eval(i) for i in data if len(i) > 0]) | |
| # encode labels | |
| df["label"] = df["gold_label"].map({"entailment": 0, "neutral": 1, "contradiction": 2}) | |
| # cast to dataset | |
| features = Features({ | |
| "sentence1": Value(dtype="string", id=None), | |
| "category": Value(dtype="string", id=None), | |
| "gold_label": Value(dtype="string", id=None), | |
| "annotator_labels": Sequence(feature=Value(dtype="string", id=None), length=3), | |
| "pairID": Value(dtype="int32", id=None), | |
| "sentence2": Value(dtype="string", id=None), | |
| "label": ClassLabel(num_classes=3, names=["entailment", "neutral", "contradiction"]), | |
| }) | |
| ds = Dataset.from_pandas(df, features=features) | |
| ds.push_to_hub("breaking_nli", token="<token>", split="all") | |
| ``` |