Who should use the Semantic Document Querying workflow?
Teams or solo builders working on science & healthcare tasks who want a repeatable process instead of one-off tool experiments.
Execution Map
3-step pipeline — follow each step in order
1Setup · Step 1 of 3
Open task pageExtract entities from documents
Prepare inputs and settings through Extract entities from documents before running semantic document querying.
Why this matters
Extract entities from documents sets up the foundation for semantic document querying; clean inputs here reduce downstream rework.
What you get
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
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2Input · Step 2 of 3
Open task pagePerform semantic segmentation
Use Perform semantic segmentation to build supporting assets that improve semantic document querying quality.
Why this matters
Perform semantic segmentation strengthens semantic document querying by feeding better supporting material into the pipeline.
What you get
Supporting assets from perform semantic segmentation are prepared and connected to the main workflow.
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3Core · Step 3 of 3
Open task pageSemantic Document Querying
Execute semantic document querying with Semantic Document Querying to produce the primary document output.
Why this matters
This is the core step where semantic document querying actually happens, so it determines baseline quality for everything after it.
What you get
A first-pass document output is generated and ready for refinement in the next steps.
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