README.md

---
license: apache-2.0
dataset_info:
  features:
  - name: pattern_id
    dtype: int64
  - name: pattern
    dtype: string
  - name: test_id
    dtype: int64
  - name: negation_type
    dtype: string
  - name: semantic_type
    dtype: string
  - name: syntactic_scope
    dtype: string
  - name: isDistractor
    dtype: bool
  - name: label
    dtype: bool
  - name: sentence
    dtype: string
  splits:
  - name: train
    num_bytes: 41264658
    num_examples: 268505
  - name: validation
    num_bytes: 3056321
    num_examples: 22514
  - name: test
    num_bytes: 12684749
    num_examples: 90281
  download_size: 6311034
  dataset_size: 57005728
task_categories:
- text-classification
language:
- en
tags:
- commonsense
- negation
- LLMs
- LLM
pretty_name: This is NOT a Dataset
size_categories:
- 100K<n<1M
---


<p align="center">
    <img src="https://github.com/hitz-zentroa/This-is-not-a-Dataset/raw/main/assets/tittle.png" style="height: 250px;">
</p>

<h3 align="center">"A Large Negation Benchmark to Challenge Large Language Models"</h3>

<p align="justify">
We introduce a large semi-automatically generated dataset of ~400,000 descriptive sentences about commonsense knowledge that can be true or false in which negation is present in about 2/3 of the corpus in different forms that we use to evaluate LLMs.
</p>

- 📖 Paper: [This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models (EMNLP'23)]()
- 💻 Baseline Code and the Official Scorer: [https://github.com/hitz-zentroa/This-is-not-a-Dataset](https://github.com/hitz-zentroa/This-is-not-a-Dataset)

# Data explanation

- **pattern_id** (int): The ID of the pattern,in range [1,11]
- **pattern** (str): The name of the pattern
- **test_id** (int): For each pattern we use a set of templates to instanciate the triples. Examples are grouped in triples by test id
- **negation_type** (str): Affirmation, verbal, non-verbal
- **semantic_type** (str): None (for affirmative sentences), analytic, synthetic
- **syntactic_scope** (str): None (for affirmative sentences), clausal, subclausal
- **isDistractor** (bool): We use distractors (randonly selectec synsets) to generate false kwoledge.
- **<span style="color:green">sentence</span>**  (str): The sentence. <ins>This is the input of the model</ins>
- **<span style="color:green">label</span>** (bool): The label of the example, True if the statement is true, False otherwise. <ins>This is the target of the model</ins>

If you want to run experiments with this dataset, please, use the [Official Scorer](https://github.com/hitz-zentroa/This-is-not-a-Dataset#scorer) to ensure reproducibility and fairness. 

# Citation
The paper will be presented at EMNLP 2023, the citation will be available soon. For now, you can use the following bibtex:

```bibtex
@inproceedings{this-is-not-a-dataset,
    title = "This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models",
    author = "Iker García-Ferrero, Begoña Altuna, Javier Alvez, Itziar Gonzalez-Dios, German Rigau",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    year = "2023",
    publisher = "Association for Computational Linguistics",
}
```