| ## Overview | |
| Original dataset available [here](https://wellecks.github.io/dialogue_nli/). | |
| ## Dataset curation | |
| Original `label` column is renamed `original_label`. The original classes are renamed as follows | |
| ``` | |
| {"positive": "entailment", "negative": "contradiction", "neutral": "neutral"}) | |
| ``` | |
| and encoded with the following mapping | |
| ``` | |
| {"entailment": 0, "neutral": 1, "contradiction": 2} | |
| ``` | |
| and stored in the newly created column `label`. | |
| The following splits and the corresponding columns are present in the original files | |
| ``` | |
| train {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| dev {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| test {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| verified_test {'dtype', 'annotation3', 'sentence1', 'sentence2', 'annotation1', 'annotation2', 'original_label', 'label', 'triple2', 'triple1'} | |
| extra_test {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| extra_dev {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| extra_train {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| valid_havenot {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| valid_attributes {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| valid_likedislike {'dtype', 'id', 'sentence1', 'sentence2', 'original_label', 'label', 'triple2', 'triple1'} | |
| ``` | |
| Note that I only keep the common columns, which means that I drop "annotation{1, 2, 3}" from `verified_test`. | |
| Note that there are some splits with the same instances, as found by matching on "original_label", "sentence1", "sentence2". | |
| ## Code to create dataset | |
| ```python | |
| import pandas as pd | |
| from pathlib import Path | |
| import json | |
| from datasets import Features, Value, ClassLabel, Dataset, DatasetDict, Sequence | |
| # load data | |
| ds = {} | |
| for path in Path(".").rglob("<path to folder>/*.jsonl"): | |
| print(path, flush=True) | |
| with path.open("r") as fl: | |
| data = fl.read() | |
| try: | |
| d = json.loads(data, encoding="utf-8") | |
| except json.JSONDecodeError as error: | |
| print(error) | |
| df = pd.DataFrame(d) | |
| # encode labels | |
| df["original_label"] = df["label"] | |
| df["label"] = df["label"].map({"positive": "entailment", "negative": "contradiction", "neutral": "neutral"}) | |
| df["label"] = df["label"].map({"entailment": 0, "neutral": 1, "contradiction": 2}) | |
| ds[path.name.split(".")[0]] = df | |
| # prettify names of data splits | |
| datasets = { | |
| k.replace("dialogue_nli_", "").replace("uu_", "").lower(): v | |
| for k, v in ds.items() | |
| } | |
| datasets.keys() | |
| #> dict_keys(['train', 'dev', 'test', 'verified_test', 'extra_test', 'extra_dev', 'extra_train', 'valid_havenot', 'valid_attributes', 'valid_likedislike']) | |
| # cast to datasets using only common columns | |
| features = Features({ | |
| "label": ClassLabel(num_classes=3, names=["entailment", "neutral", "contradiction"]), | |
| "sentence1": Value(dtype="string", id=None), | |
| "sentence2": Value(dtype="string", id=None), | |
| "triple1": Sequence(feature=Value(dtype="string", id=None), length=3), | |
| "triple2": Sequence(feature=Value(dtype="string", id=None), length=3), | |
| "dtype": Value(dtype="string", id=None), | |
| "id": Value(dtype="string", id=None), | |
| "original_label": Value(dtype="string", id=None), | |
| }) | |
| ds = {} | |
| for name, df in datasets.items(): | |
| if "id" not in df.columns: | |
| df["id"] = "" | |
| ds[name] = Dataset.from_pandas(df.loc[:, list(features.keys())], features=features) | |
| ds = DatasetDict(ds) | |
| ds.push_to_hub("dialogue_nli", token="<token>") | |
| # check overlap between splits | |
| from itertools import combinations | |
| for i, j in combinations(ds.keys(), 2): | |
| print( | |
| f"{i} - {j}: ", | |
| pd.merge( | |
| ds[i].to_pandas(), | |
| ds[j].to_pandas(), | |
| on=["original_label", "sentence1", "sentence2"], | |
| how="inner", | |
| ).shape[0], | |
| ) | |
| #> train - dev: 58 | |
| #> train - test: 98 | |
| #> train - verified_test: 90 | |
| #> train - extra_test: 0 | |
| #> train - extra_dev: 0 | |
| #> train - extra_train: 0 | |
| #> train - valid_havenot: 0 | |
| #> train - valid_attributes: 0 | |
| #> train - valid_likedislike: 0 | |
| #> dev - test: 19 | |
| #> dev - verified_test: 19 | |
| #> dev - extra_test: 0 | |
| #> dev - extra_dev: 75 | |
| #> dev - extra_train: 75 | |
| #> dev - valid_havenot: 75 | |
| #> dev - valid_attributes: 75 | |
| #> dev - valid_likedislike: 75 | |
| #> test - verified_test: 12524 | |
| #> test - extra_test: 34 | |
| #> test - extra_dev: 0 | |
| #> test - extra_train: 0 | |
| #> test - valid_havenot: 0 | |
| #> test - valid_attributes: 0 | |
| #> test - valid_likedislike: 0 | |
| #> verified_test - extra_test: 29 | |
| #> verified_test - extra_dev: 0 | |
| #> verified_test - extra_train: 0 | |
| #> verified_test - valid_havenot: 0 | |
| #> verified_test - valid_attributes: 0 | |
| #> verified_test - valid_likedislike: 0 | |
| #> extra_test - extra_dev: 0 | |
| #> extra_test - extra_train: 0 | |
| #> extra_test - valid_havenot: 0 | |
| #> extra_test - valid_attributes: 0 | |
| #> extra_test - valid_likedislike: 0 | |
| #> extra_dev - extra_train: 250946 | |
| #> extra_dev - valid_havenot: 250946 | |
| #> extra_dev - valid_attributes: 250946 | |
| #> extra_dev - valid_likedislike: 250946 | |
| #> extra_train - valid_havenot: 250946 | |
| #> extra_train - valid_attributes: 250946 | |
| #> extra_train - valid_likedislike: 250946 | |
| #> valid_havenot - valid_attributes: 250946 | |
| #> valid_havenot - valid_likedislike: 250946 | |
| #> valid_attributes - valid_likedislike: 250946 | |
| ``` |