QA from Public News Query in.
Query in.
Dataset out.
No data? No problem. Just a search query and a time window. We pull domain-specific news, generate forward-looking questions, and verify the answers automatically.
No data? No problem.
Start from nothing but a search query. We pull from historical news sources and build a complete, verified dataset for any topic.
Grounded in real outcomes
Questions are forward-looking, answers are verified against what actually happened. Every label is backed by evidence, not opinion.
Any topic, any time window
AI regulation, biotech, crypto, geopolitics — pick a domain and a date range. The pipeline handles sourcing, question generation, and labeling.
Simple, powerful API
Just a search query and a time window. We handle the rest.
- Pull from historical news sources across any domain
- Forward-looking questions verified against real outcomes
- Full provenance with evidence and citations
from lightningrod import Pipeline
pipeline = Pipeline([
NewsSeedGenerator(query="AI regulation"),
ForwardLookingQuestionGenerator(
instructions="Questions about policy outcomes"
),
WebSearchLabeler()
])
dataset = pipeline.run(n_samples=100) Trusted by teams building AI