A powerful integration that transforms natural language questions into complex SPARQL queries to extract and visualize structured data from DBpedia.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install query-dbpedia
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install query-dbpedia using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is DBpedia Query Skill?
The DBpedia Query Skill is a sophisticated tool designed for AI agents to bridge the gap between human language and the semantic web. By utilizing Openclaw Skills, developers can allow users to query the vast DBpedia knowledge graph—containing millions of entities from Wikipedia—using plain English. The skill automates the translation of intent into structured SPARQL code, executes it against live endpoints, and formats the resulting data into actionable insights.
Whether you are building a research assistant or a data visualization tool, this skill provides the necessary logic to map properties, handle prefixes, and ensure data integrity. It represents a significant advancement in making linked open data accessible to non-technical users through the power of Openclaw Skills.
DBpedia Query Skill Use Cases
- Performing complex research on entities such as movies, books, historical figures, and geographic locations.
- Automatically generating interactive HTML reports and data tables from Wikipedia's structured data.
- Converting plain English questions like "Who directed Interstellar?" into executable SPARQL queries.
- Building knowledge-graph-powered applications that leverage Openclaw Skills for real-time data retrieval.
How DBpedia Query Skill Works
- The skill analyzes the natural language input to identify the subject, predicate, and specific constraints like sorting or limits.
- It maps identified terms to the DBpedia Ontology (dbo) or Property (dbp) namespaces.
- A syntactically valid SPARQL query is constructed using standard prefixes and language filters to ensure high-quality English results.
- The skill executes the query against the DBpedia SPARQL endpoint using an optimized HTTP request.
- Retreived JSON data is processed and transformed into the user's chosen format, such as a styled HTML page or a Markdown table.
DBpedia Query Skill Setup
To get started with this skill within the Openclaw Skills framework, ensure your environment can make outbound HTTP requests to the DBpedia endpoint. You can verify connectivity and query logic using the following command:
curl -s -G "https://dbpedia.org/sparql" \
--data-urlencode "query=SELECT DISTINCT ?label WHERE { dbr:Christopher_Nolan rdfs:label ?label . FILTER(LANG(?label) = 'en') }" \
--data-urlencode "format=json"
No API keys are required as DBpedia is a public SPARQL endpoint.
DBpedia Query Skill Data Schema & Taxonomy
The skill organizes data into a structured format suitable for both automated processing and human reading.
| Component | Description |
|---|---|
| SPARQL Prefixes | Standard mappings for dbo, dbr, and rdfs to ensure query accuracy. |
| Entity Mapping | Translation of natural language subjects to DBpedia URIs. |
| Result Set | Structured JSON containing variables, types, and values from the graph. |
| HTML Template | A responsive wrapper including statistics, the source query, and interactive tables. |
DBpedia Query Skill Advanced Features
- Intelligent Property Mapping: Automatically translates common phrases into precise ontology predicates.
- Interactive HTML Generation: Creates beautiful, mobile-friendly result pages with gradient backgrounds and hover effects.
- Robust Error Recovery: Automatically suggests query reformulations or adds LIMIT clauses if a timeout occurs.
- Multi-format Export: Seamlessly switch between JSON, Markdown, and HTML outputs using Openclaw Skills logic.
SKILL.md
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