---
dataset_info:
  features:
  - name: question_title
    dtype: string
  - name: answer_text
    dtype: string
  splits:
  - name: full
    num_bytes: 556210684
    num_examples: 1232296
  - name: semhashed_0.7
    num_bytes: 26391945
    num_examples: 71373
  - name: semhashed_0.8
    num_bytes: 65733853
    num_examples: 181242
  - name: semhashed_0.9
    num_bytes: 214865080
    num_examples: 542393
  download_size: 229389702
  dataset_size: 863201562
configs:
- config_name: default
  data_files:
  - split: full
    path: data/full-*
  - split: semhashed_0.7
    path: data/semhashed_0.7-*
  - split: semhashed_0.8
    path: data/semhashed_0.8-*
  - split: semhashed_0.9
    path: data/semhashed_0.9-*
license: cc0-1.0
task_categories:
- question-answering
language:
- pt
---
# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->

Portuguese preprocessed split from [MQA dataset](https://huggingface.co/datasets/clips/mqa) containing only the question_title and answer_text columns of records in the ".pt" domain.

The dataset was derived by filtering the following dataset: [ju-resplande/qa-pt](https://huggingface.co/datasets/ju-resplande/qa-pt)

The rationale is to have a dataset that is closer aligned with the Portuguese (Portugal) language.

Semantic deduplication splits included for thresholds of 0.7, 0.8 and 0.9 with model [sentence-transformers/static-similarity-mrl-multilingual-v1](https://huggingface.co/sentence-transformers/static-similarity-mrl-multilingual-v1) 

The same license as both upstream datasets is used: Creative Commons Zero v1.0 Universal.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

- **Curated by:** @marquesafonso
- **Language(s) (NLP):** Portuguese (Portugal)
- **License:** Creative Commons Zero v1.0 Universal

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repositories:** [MQA dataset](https://huggingface.co/datasets/clips/mqa); [ju-resplande/qa-pt](https://huggingface.co/datasets/ju-resplande/qa-pt)

## Uses

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### Direct Use

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[More Information Needed]

### Out-of-Scope Use

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[More Information Needed]

## Dataset Structure

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[More Information Needed]

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

The rationale is to have a dataset that is closer aligned with the Portuguese (Portugal) language.

Semantic deduplication splits included for thresholds of 0.7, 0.8 and 0.9 with model [sentence-transformers/static-similarity-mrl-multilingual-v1](https://huggingface.co/sentence-transformers/static-similarity-mrl-multilingual-v1) 

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

Portuguese preprocessed split from [MQA dataset](https://huggingface.co/datasets/clips/mqa) containing only the question_title and answer_text columns of records in the ".pt" domain.

The dataset was derived by filtering the following dataset: [ju-resplande/qa-pt](https://huggingface.co/datasets/ju-resplande/qa-pt)

#### Who are the source data producers?

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[More Information Needed]

### Annotations [optional]

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#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

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## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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