Understand the question before you retrieve.
Turn informal student language into a careful, retrieval-ready query—without trading away the semantic meaning of the original question.
Ask it how a student would
The processor recognizes intent, department, time references, spelling variants, and concise follow-ups before retrieval begins.
Try a student phrasing
Retrieval-ready interpretation
A compact signal layer guides retrieval without overriding the student’s original meaning.
Canonical query
Head of Department Computer Science and Engineering
- Intent
- hod
- Question type
- person lookup
- Department
- Computer Science and Engineering
- Time reference
- Not detected
Extracted entities & keywords
NLP confidence
74%
Intent and entities are used to enrich the embedding and hybrid re-ranking query.
Hybrid retrieval handoff
NLP narrows the search, evidence stays in control.
The processor improves query recall and precision—it never invents an answer or replaces semantic retrieval.
- 01
Understand
Normalize language, detect intent, department, entities, and time.
- 02
Retrieve
Embed the canonical query alongside the original student phrasing.
- 03
Re-rank
Blend FAQ, Pinecone, and keyword evidence into relevant NEC chunks.
- 04
Ground
Let Ollama answer only from the selected NEC evidence.