task_categories:text-classification task_ids:text-scoring task_ids:natural-language-inference task_ids:semantic-similarity-scoring annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:pt license:unknown region:us
The ASSIN 2 corpus is composed of rather simple sentences. Following the procedures of SemEval 2014 Task 1.
The training and validation data are composed, respectively, of 6,500 and 500 sentence pairs in Brazilian Portuguese,
annotated for entailment and semantic similarity. Semantic similarity values range from 1 to 5, and text entailment
classes are either entailment or none. The test data are composed of approximately 3,000 sentence pairs with the same
annotation. All data were manually annotated.
@inproceedings{real2020assin,
  title={The assin 2 shared task: a quick overview},
  author={Real, Livy and Fonseca, Erick and Oliveira, Hugo Goncalo},
  booktitle={International Conference on Computational Processing of the Portuguese Language},
  pages={406--412},
  year={2020},
  organization={Springer}
}
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
- natural-language-inference
- semantic-similarity-scoring
paperswithcode_id: assin2
pretty_name: ASSIN 2
dataset_info:
  features:
  - name: sentence_pair_id
    dtype: int64
  - name: premise
    dtype: string
  - name: hypothesis
    dtype: string
  - name: relatedness_score
    dtype: float32
  - name: entailment_judgment
    dtype:
      class_label:
        names:
          '0': NONE
          '1': ENTAILMENT
  splits:
  - name: train
    num_bytes: 864816
    num_examples: 6500
  - name: test
    num_bytes: 339580
    num_examples: 2448
  - name: validation
    num_bytes: 66895
    num_examples: 500
  download_size: 2113646
  dataset_size: 1271291
---

# Dataset Card for ASSIN 2

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [ASSIN 2 homepage](https://sites.google.com/view/assin2)
- **Repository:** [ASSIN 2 repository](https://sites.google.com/view/assin2)
- **Paper:** [The ASSIN 2 shared task: a quick overview](https://drive.google.com/file/d/1ft1VU6xiVm-N58dfAp6FHWjQ4IvcXgqp/view)
- **Point of Contact:** [Livy Real](mailto:livyreal@gmail.com)

### Dataset Summary

The ASSIN 2 corpus is composed of rather simple sentences. Following the procedures of SemEval 2014 Task 1.
The training and validation data are composed, respectively, of 6,500 and 500 sentence pairs in Brazilian Portuguese, 
annotated for entailment and semantic similarity. Semantic similarity values range from 1 to 5, and text entailment 
classes are either entailment or none. The test data are composed of approximately 3,000 sentence pairs with the same 
annotation. All data were manually annotated.

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

The language supported is Portuguese.

## Dataset Structure

### Data Instances

An example from the ASSIN 2 dataset looks as follows:

```
{
  "entailment_judgment": 1,
  "hypothesis": "Uma criança está segurando uma pistola de água",
  "premise": "Uma criança risonha está segurando uma pistola de água e sendo espirrada com água",
  "relatedness_score": 4.5,
  "sentence_pair_id": 1
}
```

### Data Fields

- `sentence_pair_id`: a `int64` feature.
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `relatedness_score`: a `float32` feature.
- `entailment_judgment`: a classification label, with possible values including `NONE`, `ENTAILMENT`.

### Data Splits

The data is split into train, validation and test set. The split sizes are as follow:

| Train  | Val   | Test |
| ------ | ----- | ---- |
| 6500   | 500   | 2448 |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

```
@inproceedings{real2020assin,
  title={The assin 2 shared task: a quick overview},
  author={Real, Livy and Fonseca, Erick and Oliveira, Hugo Goncalo},
  booktitle={International Conference on Computational Processing of the Portuguese Language},
  pages={406--412},
  year={2020},
  organization={Springer}
}
```

### Contributions

Thanks to [@jonatasgrosman](https://github.com/jonatasgrosman) for adding this dataset.