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---
task_categories:
- translation
- question-answering
- conversational
language:
- en
- sq
pretty_name: Lilium Albanicum Eng-Alb
size_categories:
- 100K<n<1M
---
# Lilium Albanicum Eng-Alb
**Task Categories**:
- Translation
- Question-Answering
- Conversational
**Languages**: English (en), Albanian (sq)
**Size Categories**: 100K < n < 1M
---
# Dataset Card for "Lilium Albanicum"
## Dataset Summary
The Lilium Albanicum dataset is a comprehensive English-Albanian and Albanian-English parallel corpus. The dataset includes original translations and extended synthetic Q&A pairs, which are designed to support and optimize LLM translation tasks. The synthetic pairs are generated to mimic realistic conversational scenarios, aiding in the development of more effective translation models.
## Dataset Attribution
### Translation Process:
The dataset comprises expert-generated translations, ensuring high-quality language pairs. The Q&A pairs are machine-generated, followed by rigorous human review and refinement to guarantee natural and coherent translations.
## Supported Tasks and Leaderboards
This dataset is primarily tailored for translation, question-answering, and conversational tasks, aiming to improve bilingual models' performance with a focus on contextual understanding.
## Languages
The dataset includes bilingual data in English (en) and Albanian (sq).
## Dataset Structure
### Data Instances
A typical data instance includes a text pair in English and Albanian, reflecting a conversational exchange or a Q&A format suited for translation tasks.
### Data Fields
- albanian: The corresponding Albanian translation of the text.
- english: The English version of the text.
- question: The question part of the conversational or Q&A context.
- response: The response part of the conversational or Q&A context.
- swapped: An integer (int64) indicating whether the roles in the conversation have been swapped.
- system_prompt: A string containing system prompts or instructions related to the text entry.
### Data Splits
The dataset is structured into appropriate splits for training, validation, and testing to facilitate effective machine learning practices.
## Dataset Creation
### Curation Rationale
The creation of Lilium Albanicum aims to fill the gap in high-quality, conversational-context-focused datasets for English-Albanian translation tasks, thereby enhancing the capabilities of translation models.
### Source Data
The source data originates from a well-established Albanian-English parallel corpus, enriched with synthetic yet realistic Q&A scenarios.
## Dataset Use
### Use Cases
The dataset can be employed for various NLP tasks such as bilingual translation, conversational understanding, and question-answering systems development, both in academic research and practical applications.
### Usage Caveats
The synthetic nature of some parts of the dataset may not encompass all nuances of natural language. Users should consider complementing it with naturally occurring text data for tasks requiring high levels of linguistic subtlety.
### Getting Started
The dataset is accessible through the Hugging Face datasets library, with support for streaming to handle large datasets efficiently.
________________________________________
**Dataset contributors**:
- Marlind Maksuti (contact: marlind.maksuti@gmail.com)
- StochastX team
**Acknowledgments**:
Special thanks to the creators of the original Albanian-English parallel corpus MaCoCu-sq-en 1.0 and to all contributors who participated in the generation and refinement of the Q&A pairs.
**License**:
This work is licensed under the MIT license.
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