license: cc-by-nc-nd-4.0
language:
- fa
tags:
- nlg
- summarization
- machine-translation
- question-generation
- persian
- multilingual
pretty_name: Persian NLG Benchmark
task_categories:
- text-generation
- summarization
- translation
Persian NLG
Dataset Summary
The Persian NLG Benchmark is a curated collection of Persian datasets designed to evaluate natural language generation (NLG) capabilities in a variety of tasks, including:
- Summarization: Using datasets like SamSUM-fa and PnSummary
- Machine Translation: With parallel corpora such as TEP, MIZAN, and EPOQUE
- Question Generation: Using the PersianQA dataset
This benchmark provides a comprehensive view of how Persian-capable models perform on generative tasks that are linguistically and semantically complex.
Supported Tasks and Leaderboards
Summarization
The summarization track tests how well models can generate concise and accurate summaries from Persian conversational or formal texts. Relevant columns include input text and human-written summaries.
Machine Translation
The translation task evaluates models' performance in translating between Persian, English, and Arabic. The datasets cover multiple domains and include source-target sentence pairs. Evaluation can be done in both directions (e.g., fa→en, en→fa).
Question Generation
The question generation task assesses the ability of models to generate meaningful questions based on a given passage and answer. This tests the contextual and semantic understanding of the models in Persian.
Languages
The primary language is Persian (fa), but the machine translation section includes English (en) and Arabic (ar) as well.
License
This dataset is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
You must give appropriate credit, may not use it for commercial purposes, and may not distribute modified versions of the dataset.
For details, see the license file or https://creativecommons.org/licenses/by-nc-nd/4.0/