Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Query DBpedia using Natural Language
Transform natural language questions into SPARQL queries for DBpedia and generate beautiful HTML results pages. Query the DBpedia knowledge graph using plain...
skill openclawclawhub Free
Transform natural language questions into SPARQL queries for DBpedia and generate beautiful HTML results pages. Query the DBpedia knowledge graph using plain...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- christopher_nolan_films.html, README.md, examples/sample-queries.md, SKILL.md, templates/html-template.html
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- kidehen
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
When to Use This Skill
Use this skill when users want to: Query DBpedia using natural language Ask questions about people, places, movies, books, organizations, etc. Get structured data from Wikipedia via DBpedia Create visualizations of DBpedia query results Generate HTML reports from SPARQL queries
Core Capabilities
โ Natural Language to SPARQL: Convert user questions into valid SPARQL queries โ Query Execution: Execute queries against DBpedia endpoint โ HTML Generation: Create beautiful, interactive HTML result pages โ Multiple Output Formats: JSON, Markdown tables, or HTML โ Error Handling: Graceful handling of malformed queries or no results
DBpedia Endpoint
SPARQL Endpoint: https://dbpedia.org/sparql Format: JSON results (format=json) Method: HTTP GET with URL-encoded query
Common DBpedia Prefixes
PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX dbp: <http://dbpedia.org/property/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX dct: <http://purl.org/dc/terms/>
Query Conversion Workflow
When a user provides a natural language prompt:
1. Analyze the Question
Identify the subject (who/what is being asked about) Identify the predicate (what information is requested) Determine if filtering, sorting, or limiting is needed
2. Map to DBpedia Properties
Common mappings: "directed by" โ dbo:director "release date" โ dbp:date or dbo:releaseDate "budget" โ dbo:budget "born in" โ dbo:birthPlace "population" โ dbo:populationTotal "capital of" โ dbo:capital "written by" โ dbo:author "starring" โ dbo:starring
3. Construct SPARQL Query
Template: PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> SELECT DISTINCT ?variable ?label WHERE { ?variable <predicate> <object> ; rdfs:label ?label . FILTER(LANG(?label) = 'en') } ORDER BY <sort_criteria> LIMIT <number>
4. Execute Query
Use curl to execute against DBpedia: curl -s -G "https://dbpedia.org/sparql" \ --data-urlencode "query=<SPARQL_QUERY>" \ --data-urlencode "format=json"
5. Generate Output
Options: JSON: Raw query results Markdown Table: Formatted for terminal display HTML Page: Interactive, styled results page
Pattern 1: Films by Director
User: "Show me movies directed by Christopher Nolan" SPARQL: PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> SELECT DISTINCT ?film ?title ?releaseDate WHERE { ?film dbo:director dbr:Christopher_Nolan ; a dbo:Film ; rdfs:label ?title . OPTIONAL { ?film dbo:releaseDate ?releaseDate } FILTER(LANG(?title) = 'en') } ORDER BY DESC(?releaseDate)
Pattern 2: Population Queries
User: "What are the 10 most populous cities in France?" SPARQL: PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> SELECT ?city ?name ?population WHERE { ?city dbo:country dbr:France ; a dbo:City ; rdfs:label ?name ; dbo:populationTotal ?population . FILTER(LANG(?name) = 'en') } ORDER BY DESC(?population) LIMIT 10
Pattern 3: Person Information
User: "Tell me about Albert Einstein - when was he born and where?" SPARQL: PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> SELECT ?birthDate ?birthPlace ?placeLabel WHERE { dbr:Albert_Einstein dbo:birthDate ?birthDate ; dbo:birthPlace ?birthPlace . ?birthPlace rdfs:label ?placeLabel . FILTER(LANG(?placeLabel) = 'en') }
HTML Template Generation
When generating HTML results:
Required Elements
Title: Question or query description Statistics: Number of results, query execution time Table: Results with hyperlinked DBpedia URIs SPARQL Query Display: Show the executed query Footer: Link to DBpedia, data source attribution
Styling Guidelines
Use gradient backgrounds Responsive design (mobile-friendly) Hover effects on table rows Hyperlink all DBpedia resources Color-code different data types Include icons for visual appeal
HTML Template Structure
<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>[Query Description] - DBpedia</title> <style> /* Modern, responsive styling */ /* Gradient backgrounds */ /* Hover effects */ /* Mobile-first design */ </style> </head> <body> <div class="container"> <h1>[Question/Title]</h1> <div class="stats">[Results count]</div> <table>[Results]</table> <div class="sparql-query">[Query code]</div> <div class="footer">[Attribution]</div> </div> </body> </html>
No Results
If query returns 0 results: Inform user clearly Suggest alternative phrasings Check for typos in entity names
Query Errors
If SPARQL syntax error: Display error message Show attempted query Offer to reformulate
Timeout
If query times out: Add LIMIT clause Simplify query complexity Suggest narrowing criteria
Output Preferences
Always ask the user: "Would you like the results as: 1. JSON (raw data) 2. Markdown table (terminal display) 3. HTML page (interactive visualization)"
Best Practices
Always use DISTINCT: Avoid duplicate results Filter by language: Use FILTER(LANG(?label) = 'en') Add LIMIT: Default to LIMIT 100 unless specified Use OPTIONAL: For properties that may not exist Order results: Make results meaningful with ORDER BY Hyperlink in HTML: All DBpedia URIs should be clickable
Example Session
User: "List books written by J.K. Rowling with publication dates" Assistant: "I'll query DBpedia for books authored by J.K. Rowling. Executing SPARQL query against DBpedia endpoint..." [Constructs and executes query] "Found 15 books! Would you like the results as: JSON Markdown table HTML page" User: "HTML page" Assistant: [Generates beautiful HTML page with results] "โ HTML page generated and saved to: ./jk_rowling_books.html โ 15 books found with publication dates"
Scope
This skill handles: Queries about entities in DBpedia Structured data extraction Result formatting and visualization This skill does NOT handle: Text search (use DBpedia Lookup API instead) Data modification (read-only queries) Real-time data (DBpedia updates periodically) Version: 1.0.0 Endpoint: https://dbpedia.org/sparql Data Source: DBpedia (Wikipedia structured data)
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs2 Files
- SKILL.md
- examples/sample-queries.md
- README.md
- christopher_nolan_films.html
- templates/html-template.html