Definition
Named Entity Recognition (NER) in RAG pipelines is the process of extracting and classifying specific spans of text—such as product IDs, locations, or technical terms—from unstructured queries to enable precise metadata filtering or to populate arguments for agentic tool calls. It transforms natural language into structured parameters, significantly reducing the search space and improving retrieval precision.
In RAG, NER is a structural extraction tool for query narrowing, not just a linguistic labeling task.
"A digital highlighter that automatically marks specific keywords on a document and files them into labeled folders."
- Metadata Filtering(Component: NER provides the values used to apply hard filters to vector database queries.)
- Entity Linking(Sequential: The process of connecting a recognized entity to a unique identifier in a Knowledge Graph.)
- Query Decomposition(Prerequisite: Breaking down a complex query into parts where NER can identify specific constraints.)
Conceptual Overview
Named Entity Recognition (NER) in RAG pipelines is the process of extracting and classifying specific spans of text—such as product IDs, locations, or technical terms—from unstructured queries to enable precise metadata filtering or to populate arguments for agentic tool calls. It transforms natural language into structured parameters, significantly reducing the search space and improving retrieval precision.
Disambiguation
In RAG, NER is a structural extraction tool for query narrowing, not just a linguistic labeling task.
Visual Analog
A digital highlighter that automatically marks specific keywords on a document and files them into labeled folders.