Feature: Natural language queries on marketing asset data
In order to quickly gain insights from marketing campaigns and asset processing data, as a marketing operations analyst
I want to use natural language questions to query the RDF triple store and get results in a readable format.
Scenario: Retrieve campaigns using HD video assets for a specific audience in a given year.
Given an RDF triple store is populated with marketing campaign data and video asset data
And RDFS and SKOS definitions for the marketing domain (covering campaigns, assets, and audiences) are loaded
And a domain-tuned language model is configured to convert natural language queries into SPARQL
And the triple store includes both the core marketing dataset and an additional asset metadata dataset
When I ask "Which campaigns targeting Millennials in 2024 used HD video assets?"
Then the system should translate the question into a SPARQL query guided by the domain's RDFS ontology and SKOS vocabularies
And the query should incorporate data from both the core campaign dataset and the asset metadata dataset to find the relevant results
And the system executes the SPARQL query against the triple store
And I should see the query results in a human-readable table format