QCRI/LlamaLens-English

LlamaLens: Specialized Multilingual LLM Dataset

This dataset supports the research presented in the paper LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content.

Overview

LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 18 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi. This repository contains the English-language portion of the data.

Dataset Details

This dataset comprises various sub-datasets focusing on different text classification tasks related to news and social media analysis. A detailed breakdown of the datasets and their statistics is provided in the metadata section above.

File Format

Each JSONL file in the dataset follows a structured format with the following fields:

• id: Unique identifier for each data entry.
• original_id: Identifier from the original dataset, if available.
• input: The original text that needs to be analyzed.
• output: The label assigned to the text after analysis.
• dataset: Name of the dataset the entry belongs.
• task: The specific task type.
• lang: The language of the input text.
• instructions: A brief set of instructions describing how the text should be labeled.

Example entry in JSONL file:

{
    "id": "fb6dd1bb-2ab4-4402-adaa-9be9eea6ca18",
    "original_id": null,
    "input": "I feel that worldviews that lack the divine tend toward the solipsistic.",
    "output": "joy",
    "dataset": "Emotion",
    "task": "Emotion",
    "lang": "en",
    "instructions": "Identify if the given text expresses an emotion and specify whether it is joy, love, fear, anger, sadness, or surprise. Return only the label without any explanation, justification, or additional text."
}

Model & Code

• LlamaLens Model on Hugging Face: https://huggingface.co/QCRI/LlamaLens
• LlamaLens GitHub Repository: https://github.com/firojalam/LlamaLens

📢 Citation

If you use this dataset, please cite our paper:

@article{kmainasi2024llamalensspecializedmultilingualllm,
  title={LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content},
  author={Mohamed Bayan Kmainasi and Ali Ezzat Shahroor and Maram Hasanain and Sahinur Rahman Laskar and Naeemul Hassan and Firoj Alam},
  year={2024},
  journal={arXiv preprint arXiv:2410.15308},
  volume={},
  number={},
  pages={},
  url={https://arxiv.org/abs/2410.15308},
  eprint={2410.15308},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}