What does semantic ranker do?
Why C is the answer
It reranks search results by using language understanding models
Semantic ranker improves relevance by reranking results. It is a premium, usage-billed feature.
In detail
- Semantic ranker reranks results with language understanding models.
- It works on the results, after the first search.
Use case
An illustrative scenario, not a real incident.
Search results are decent but poorly ordered. Semantic ranker reranks the top results using language understanding, so the best passage comes first.
See it in different ways
flowchart TD A["Query"] --> B["Full-text search"] A --> C["Vector search"] B --> D["Reciprocal Rank Fusion"] C --> D D --> E["Semantic ranker"] E --> F["Top results"]
sequenceDiagram participant Q as Query participant K as Keyword search participant V as Vector search participant R as Ranking Q->>K: Search Q->>V: Search K->>R: Ranked results V->>R: Ranked results R->>R: Reciprocal Rank Fusion R-->>Q: Merged, then semantic ranker
flowchart LR S0["Initial results"] --> S1["Semantic ranker"] --> S2["Better order"]
Key point: Semantic ranker reorders results by meaning.
Why the other options are wrong
- A. It creates embeddings for documents while they are being indexed for the first time
- It works at query time, not when embedding documents.
- B. It deletes low-quality documents from the search index
- It does not delete documents.
- D. It translates each search query into English before running it
- It does not translate queries.