Snapquery Cats LLM Rewrite Experiment

Prompt

Rewrite to make blazegraph independent

# "Cats" example SPARQL query
# https://www.wikidata.org
# /wiki/Wikidata:SPARQL_query_service/queries/examples#Cats
SELECT ?item ?itemLabel
WHERE
{
  ?item wdt:P31 wd:Q146. # Must be a cat
  SERVICE wikibase:label {
      bd:serviceParam 
      wikibase:language "[AUTO_LANGUAGE],en". 
  }
}

Prompt for second attempt

the result does neither work on the wikidata query service nor on qlever

ChatGPT

To rewrite your SPARQL query to be independent of Blazegraph and remove specific Wikidata or Wikibase dependencies like the SERVICE wikibase:label, you can simplify the query to work on most SPARQL endpoints that contain similar data. This would involve removing the SERVICE block and potentially including explicit property paths for labels if the endpoint doesn't support automated label service.

Here's a generalized version of the query, assuming that the endpoint has straightforward label properties and doesn't require language specification:

# "Cats" example SPARQL query
# Generalized for non-Wikidata SPARQL endpoints
SELECT ?item ?itemLabel
WHERE
{
  ?item wdt:P31 wd:Q146. # Must be a cat
  OPTIONAL { ?item rdfs:label ?itemLabel . FILTER(LANG(?itemLabel) = "en") }
}

Key Adjustments:

   Label Handling: The OPTIONAL block with rdfs:label is used to fetch labels. This is a common way to retrieve labels in RDF data. The FILTER function restricts the label language to English ("en"), similar to the original query's intent.

   Language Filter: This is an important component if your SPARQL endpoint has multilingual labels. The filter ensures that only English labels are selected.

   Prefix Definitions: Ensure that the necessary prefixes (wdt:, wd:, rdfs:) are defined in the endpoint or add prefix definitions at the beginning of your SPARQL query if the endpoint supports or requires them. For instance:

   sparql

   PREFIX wdt: <http://www.wikidata.org/prop/direct/>
   PREFIX wd: <http://www.wikidata.org/entity/>
   PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

   Property and Class IDs: Make sure that wdt:P31 and wd:Q146 (or their equivalents) are appropriate for your endpoint. In non-Wikidata environments, you may need to replace these with corresponding properties and class identifiers relevant to that dataset.

This version of the query should work on most SPARQL endpoints that have a basic setup for handling RDF data, assuming they store information about items and their labels in a similar manner to Wikidata. If you're working with a specific dataset or endpoint, you may need to adjust property and class identifiers according to that dataset's schema.

Claude AI 3.5 sonnet

Here's a rewritten version of the SPARQL query that is independent of Blazegraph and Wikidata-specific features:

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?item ?itemLabel
WHERE {
  ?item rdf:type <http://example.org/ontology/Cat>.
  ?item rdfs:label ?itemLabel.
  
  # Language filter (optional, adjust as needed)
  FILTER(LANG(?itemLabel) = "" || LANG(?itemLabel) = "en")
}

This query has been modified to be more generic and work with standard SPARQL features. Here are the key changes:

Removed Wikidata-specific prefixes and replaced them with standard RDF and RDFS prefixes. Changed the property wdt:P31 (instance of) to a more generic rdf:type. Replaced the Wikidata item wd:Q146 (cat) with a hypothetical URI <http://example.org/ontology/Cat>. Removed the Wikidata-specific SERVICE wikibase:label and instead directly query for the label using rdfs:label. Added an optional FILTER to handle language selection, which you can adjust or remove based on your needs.

To use this query, you'll need to replace <http://example.org/ontology/Cat> with the appropriate URI for the "cat" concept in your ontology. Also, ensure that your data uses rdfs:label for labeling entities. If your ontology uses a different predicate for labels, you'll need to adjust the query accordingly. Would you like me to explain or break down this SPARQL query further?