---
license: apache-2.0
task_categories:
- translation
language:
- kk
- ru
- en
tags:
- code
pretty_name: Multilingual Literature Parallel Corpus
size_categories:
- 10K<n<100K
---

# Dataset Card for Multilingual Literature Parallel Corpus

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

The Multilingual Literature Parallel Corpus is designed for translation tasks, containing parallel text pairs from literature in three languages: Kazakh (kaz_Cyrl), Russian (rus_Cyrl), and English (eng_Latn).

## Dataset Details

### Dataset Description

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

The Multilingual Literature Parallel Corpus provides parallel text pairs for translation tasks across Kazakh, Russian, and English. The dataset is curated to support the development of machine translation models by offering high-quality parallel sentences from literature.

- **Language(s) (NLP):** Kazakh, Russian, English
- **License:** Apache-2.0

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

The dataset is suitable for developing and benchmarking translation models, cross-linguistic analysis, and linguistic research in the context of Kazakh, Russian, and English literature.

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

The dataset is not suitable for non-literary text translation tasks, real-time translation applications, or any use cases requiring domain-specific jargon outside literature.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

- **Language_pair**: The language pair in the format source_to_target (e.g., kaz_to_eng).
- **X**: The source text.
- **y**: The translated text.
- **X_lang**: The language of the source text.
- **y_lang**: The language of the translated text.
- **Similarity**: The similarity score between the source and target texts.

### Language Pairs and Example Counts

- **rus_to_eng**: 23,856 examples
- **rus_to_kaz**: 19,832 examples
- **eng_to_rus**: 15,690 examples
- **eng_to_kaz**: 5,534 examples
- **kaz_to_eng**: 3,884 examples
- **kaz_to_rus**: 2,300 examples

## Dataset Creation

### Curation Rationale

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

The dataset was created to enhance the quality and accessibility of machine translation models for Kazakh, Russian, and English, specifically within the literary domain.

### Source Data

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

The source data consists of original literary texts in Kazakh, Russian, and English.

### Target Data

The source data consists of translated literary texts in Kazakh, Russian, and English.

#### 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. -->

The data was collected from publicly available literary sources, preprocessed to align translations accurately, and normalized to maintain consistency in formatting and structure.


<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if