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### 🧾 Dataset Summary
`Text2Sparql-Raw` is a multilingual dataset designed for the task of translating natural language questions into SPARQL queries over the DBpedia knowledge graph. This dataset aggregates and harmonizes four widely used benchmarks in the text-to-SPARQL domain:
* **QALD (versions 1–9)**
* **LC-QuAD 1.0**
* **Orange/paraqa-sparqltotext**
* **julioc-p/Question-Sparql**
It contains questions in both **English** and **Spanish**, making it suitable for multilingual and cross-lingual question answering tasks over knowledge graphs.
This is the **first version** of the dataset.
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### ✅ Supported Tasks and Leaderboards
* **Text-to-SPARQL generation**: Given a natural language question, the task is to generate a syntactically correct and semantically accurate SPARQL query that retrieves the answer from the DBpedia knowledge graph.
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### 🌍 Languages
* **English** (`en`)
* **Spanish** (`es`)
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### 📁 Dataset Structure
Each instance in the dataset includes:
* `question`: The question in natural language (English or Spanish)
* `query`: The corresponding SPARQL query
* `dataset-id`: Original dataset source (e.g., `QALD-X`, `LCQUAD`, `Orange`, `JULIOC`)
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### 🔧 Dataset Creation
The dataset is a **curated compilation** of four public datasets:
* **QALD 1-9**: https://github.com/ag-sc/QALD
* **LC-QuAD 1.0**: https://github.com/AskNowQA/LC-QuAD
* **Paraqa-SparqlToText**: https://huggingface.co/datasets/Orange/paraqa-sparqltotext
* **Question-Sparql**: https://huggingface.co/datasets/julioc-p/Question-Sparql
The merged dataset aims to provide a unified resource for training multilingual text-to-SPARQL models.
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### 💡 Use Cases
This dataset is intended for training and evaluating models that:
* Generate SPARQL from natural language
* Support multilingual question answering over knowledge graphs
* Learn cross-lingual representations for semantic parsing
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### 📚 Citation
If you use this dataset in your research, please cite:
```
@misc{text2sparql-raw,
author = {Marcos Gôlo, Paulo do Carmo, Edgard Marx, Ricardo Marcacini},
title = {text2sparql-raw: Natural Language Text to SPARQL for DBpedia Dataset},
year = {2025},
howpublished = {\url{https://huggingface.co/datasets/aksw/Text2Sparql-Raw}},
}
```
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### 🪪 Licensing
license: apache-2.0
Check each dataset’s original repository for full licensing terms.
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