metadata

configs:
  - config_name: all
    data_files: All.csv.gz
    default: true
  - config_name: quality
    data_files: Quality.csv.gz
  - config_name: readability
    data_files: Readability.csv.gz
  - config_name: sentiment
    data_files: Sentiment.csv.gz
license: cc-by-sa-4.0
task_categories:
  - text-classification
  - feature-extraction
  - translation
language:
  - en
tags:
  - tatoeba
  - multilingual

Tatoeba English Translation Dataset

Dataset Summary

This dataset is derived from the Tatoeba database, focusing on English sentences and their translations. It includes assessments of English sentences using text quality, sentiment, and readability models. The dataset is designed for tasks related to multilingual text quality, readability, and sentiment analysis.

Supported Tasks and Leaderboards

Quality Assessment
Readability Prediction
Sentiment Analysis

Dataset Structure

Data Fields

ID: Unique identifier for the English sentence
English: The English sentence
TranslationID: Unique identifier for the translation
Language: ISO code of the translation language
Translation: The translated sentence
Quality: Text quality score of the English sentence
Readability: Readability score of the English sentence
Sentiment: Sentiment score of the English sentence

Data Splits

The dataset is divided into the following CSV files:

All.csv: Focused on the English and translated text
Quality.csv: Focused on text quality scores
Readability.csv: Focused on readability scores
Sentiment.csv: Focused on sentiment scores

Each of the quality, readability, sentiment files contains a maximum of 50 000 rows.

Those rows were from 25 000 pairs (2 500 from each of 10 bins) split into English and non-English entries.

Dataset Creation

Source Data

The source data is the Tatoeba database, which contains user-contributed translations.

Annotations

English sentences were assessed using:

Personal and Sensitive Information

The dataset may contain personal names and locations as part of the sentences.

Considerations for Using the Data

Social Impact of Dataset

This dataset can be used to improve machine translation systems and text analysis tools, potentially bridging language barriers and enhancing cross-cultural communication.

Discussion of Biases

The dataset may reflect biases present in the original Tatoeba database and in the assessment models used.

Other Known Limitations

The quality, readability, and sentiment scores are model-generated and may not always accurately reflect human judgments.

Contributions

Thanks to the Tatoeba Project contributors for the original sentence pairs.
The rest of the analyses are mine.