metadata
annotations_creators:
- crowdsourced
- machine-generated
language:
- en
language_creators:
- found
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
pretty_name: Adversarial NLI
size_categories:
- 100K<n<1M
source_datasets:
- original
- extended|hotpot_qa
task_categories:
- text-classification
task_ids:
- natural-language-inference
- multi-input-text-classification
paperswithcode_id: anli
dataset_info:
features:
- name: uid
dtype: string
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype:
class_label:
names:
'0': entailment
'1': neutral
'2': contradiction
- name: reason
dtype: string
config_name: plain_text
splits:
- name: train_r1
num_bytes: 8006920
num_examples: 16946
- name: dev_r1
num_bytes: 573444
num_examples: 1000
- name: test_r1
num_bytes: 574933
num_examples: 1000
- name: train_r2
num_bytes: 20801661
num_examples: 45460
- name: dev_r2
num_bytes: 556082
num_examples: 1000
- name: test_r2
num_bytes: 572655
num_examples: 1000
- name: train_r3
num_bytes: 44720895
num_examples: 100459
- name: dev_r3
num_bytes: 663164
num_examples: 1200
- name: test_r3
num_bytes: 657602
num_examples: 1200
download_size: 18621352
dataset_size: 77127356
Dataset Card for "anli"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository: https://github.com/facebookresearch/anli/
- Paper: Adversarial NLI: A New Benchmark for Natural Language Understanding
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 17.76 MB
- Size of the generated dataset: 73.55 MB
- Total amount of disk used: 91.31 MB
Dataset Summary
The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset, The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure. ANLI is much more difficult than its predecessors including SNLI and MNLI. It contains three rounds. Each round has train/dev/test splits.
Supported Tasks and Leaderboards
Languages
English
Dataset Structure
Data Instances
plain_text
- Size of downloaded dataset files: 17.76 MB
- Size of the generated dataset: 73.55 MB
- Total amount of disk used: 91.31 MB
An example of 'train_r2' looks as follows.
This example was too long and was cropped:
{
"hypothesis": "Idris Sultan was born in the first month of the year preceding 1994.",
"label": 0,
"premise": "\"Idris Sultan (born January 1993) is a Tanzanian Actor and comedian, actor and radio host who won the Big Brother Africa-Hotshot...",
"reason": "",
"uid": "ed5c37ab-77c5-4dbc-ba75-8fd617b19712"
}
Data Fields
The data fields are the same among all splits.
plain_text
uid
: astring
feature.premise
: astring
feature.hypothesis
: astring
feature.label
: a classification label, with possible values includingentailment
(0),neutral
(1),contradiction
(2).reason
: astring
feature.
Data Splits
name | train_r1 | dev_r1 | train_r2 | dev_r2 | train_r3 | dev_r3 | test_r1 | test_r2 | test_r3 |
---|---|---|---|---|---|---|---|---|---|
plain_text | 16946 | 1000 | 45460 | 1000 | 100459 | 1200 | 1000 | 1000 | 1200 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
cc-4 Attribution-NonCommercial
Citation Information
@InProceedings{nie2019adversarial,
title={Adversarial NLI: A New Benchmark for Natural Language Understanding},
author={Nie, Yixin
and Williams, Adina
and Dinan, Emily
and Bansal, Mohit
and Weston, Jason
and Kiela, Douwe},
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
year = "2020",
publisher = "Association for Computational Linguistics",
}
Contributions
Thanks to @thomwolf, @easonnie, @lhoestq, @patrickvonplaten for adding this dataset.