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README.md

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+---
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+## Dataset Description
+
+This dataset contains **895,954 examples** of natural language questions paired with their corresponding SPARQL queries. It spans **12 languages** and targets **15 distinct knowledge graphs**, with a significant portion focused on Wikidata and DBpedia.
+
+The dataset was developed as a contribution for the Master Thesis: *"Impact of Continual Multilingual Pre-training on Cross-Lingual Transferability for Source Languages"*. Its purpose is to facilitate research in text-to-SPARQL generation, particularly regarding multilinguality.
+
+### Key Features:
+* **Multilingual:** Covers 12 languages: English (en), German (de), Hebrew (he), Kannada (kn), Chinese (zh), Spanish (es), Italian (it), French (fr), Dutch (nl), Romanian (ro), Farsi (fa), and Russian (ru).
+* **Diverse Knowledge Graphs**: Includes queries for 15 KGs, prominently Wikidata and DBpedia.
+* **Large Scale:** Nearly 900,000 question-SPARQL pairs.
+* **Augmented Data:** Features German translations for many English questions and Wikidata entity/relationship mappings in the `context` column for most of the examples of Wikidata in German and English.
+
+## Dataset Structure
+
+The dataset is provided in Parquet format and consists of the following columns:
+
+* `text_query` (string): The natural language question.
+    * *(Example: "What is the boiling point of water?")*
+* `language` (string): The language code of the `text_query` (e.g., 'de', 'en', 'es').
+* `sparql_query` (string): The corresponding SPARQL query.
+    * *(Example: `PREFIX dbo: <http://dbpedia.org/ontology/> ... SELECT DISTINCT ?uri WHERE { ... }`)*
+* `knowledge_graphs` (string): The knowledge graph targeted by the `sparql_query` (e.g., 'DBpedia', 'Wikidata').
+* `context` (string, often null): (Optional) Wikidata entity/relationship mappings in JSON string format (e.g., `{"entities": {"United States Army": "Q9212"}, "relationships": {"spouse": "P26"}}`).
+
+### Data Splits
+
+* `train`: 895,954 rows.
+* `test`: 788 rows.
+
+## How to Use
+
+You can load the dataset using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load a specific split (e.g., train)
+dataset = load_dataset("julioc-p/Question-Sparql", split="train")
+
+# Iterate through the dataset
+for example in dataset:
+    print(f"Question ({example['language']}): {example['text_query']}")
+    print(f"Knowledge Graph: {example['knowledge_graphs']}")
+    print(f"SPARQL Query: {example['sparql_query']}")
+    if example['context']:
+        print(f"Context: {example['context']}")
+    print("-" * 20)
+    break