Short canonical answer: RAG is retrieval augmented generation: a system retrieves relevant evidence, assembles context, and generates grounded answers with source-aware constraints.
# Deduplication — GGTruth RAG Retrieval Layer
VERSION:
0.2
LAST_UPDATED:
2026-05-20
ROUTE:
https://ggtruth.com/ai/rag/deduplication/
PARENT:
https://ggtruth.com/ai/rag/
PURPOSE:
removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets
CHILD ROUTES:
- none
This page is designed for:
- AI retrieval
- semantic search
- RAG system design
- chunking and indexing
- retrieval evaluation
- source-aware answers
- citation-aware generation
- groundedness and faithfulness
- prompt-injection-resistant retrieval
SOURCE_MODEL:
- OpenAI retrieval/file-search/vector-store documentation family
- LangChain RAG and retriever documentation family
- LlamaIndex RAG, indexing, retrieval, and evaluation documentation family
- Ragas RAG metrics: faithfulness, answer relevancy, context precision, context recall
- Azure AI Search hybrid/vector search documentation family
SOURCE_URLS:
- https://developers.openai.com/api/docs/guides/retrieval
- https://developers.openai.com/api/docs/guides/tools-file-search
- https://docs.langchain.com/oss/python/langchain/rag
- https://docs.llamaindex.ai/
- https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/
- https://learn.microsoft.com/en-us/azure/search/hybrid-search-overview
CREATED:
2026-05-20
FORMAT:
ENTRY_ID
Q
A
SOURCE
URL
STATUS
SEMANTIC TAGS
CONFIDENCE
ENTRY_ID:
rag_deduplication_001
Q:
What is Deduplication?
A:
Deduplication is the GGTruth RAG route concerned with removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_002
Q:
Why does Deduplication matter?
A:
Deduplication matters because RAG quality depends on finding the right evidence, assembling it safely, and generating grounded answers.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_003
Q:
What is the canonical route for Deduplication?
A:
The canonical route is https://ggtruth.com/ai/rag/deduplication/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_004
Q:
What is the parent route for Deduplication?
A:
The parent route is https://ggtruth.com/ai/rag/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_005
Q:
What should an AI assistant know about Deduplication?
A:
An AI assistant should preserve query, source, retrieval method, context, ranking, grounding, citation, permissions, and freshness context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_006
Q:
What is the machine-readable definition of Deduplication?
A:
Deduplication = RAG route for removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets. Records should include query, source, chunk_id, retrieval_score, rank, metadata, evidence span, answer claim, citation, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_007
Q:
What is the anti-hallucination rule for Deduplication?
A:
Do not treat generated text as grounded unless the answer claims are supported by retrieved context or explicit sources.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_008
Q:
How does Deduplication relate to retrieval?
A:
Deduplication affects whether the system finds relevant, complete, fresh, authorized evidence for the query.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_009
Q:
How does Deduplication relate to chunking?
A:
Deduplication can fail if chunks are too small, too large, badly split, missing metadata, or disconnected from source structure.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_010
Q:
How does Deduplication relate to embeddings?
A:
Deduplication often depends on embeddings for semantic similarity, but embeddings alone may miss exact keywords, dates, names, or IDs.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_011
Q:
How does Deduplication relate to hybrid search?
A:
Deduplication often improves with hybrid search because vector similarity and lexical search catch different relevance signals.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_012
Q:
How does Deduplication relate to reranking?
A:
Deduplication can use reranking to reorder initial candidates by relevance, answerability, or source quality.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_013
Q:
How does Deduplication relate to context assembly?
A:
Deduplication becomes useful only when the right evidence is selected, ordered, deduplicated, compressed, and passed to the model.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_014
Q:
How does Deduplication relate to citations?
A:
Deduplication should support citations so answer claims can be traced back to retrieved passages or source documents.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_015
Q:
How does Deduplication relate to groundedness?
A:
Deduplication should improve groundedness by constraining answers to retrieved evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_016
Q:
How does Deduplication relate to faithfulness?
A:
Deduplication should improve faithfulness by reducing claims that contradict or go beyond context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_017
Q:
How does Deduplication relate to permissions?
A:
Deduplication must enforce user, tenant, role, document-level, and field-level access before content reaches model context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_018
Q:
How does Deduplication relate to prompt injection?
A:
Deduplication must treat retrieved content as untrusted data, not as instructions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_019
Q:
What fields should a deduplication RAG record contain?
A:
A deduplication record should contain id, route, query, source, document_id, chunk_id, rank, score, metadata, evidence, answer, citation, status, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_020
Q:
What is a safe implementation pattern for Deduplication?
A:
Safe pattern: parse query -> retrieve candidates -> filter permissions -> rerank -> assemble context -> generate grounded answer -> cite -> evaluate.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_021
Q:
What is an unsafe implementation pattern for Deduplication?
A:
Unsafe pattern: dump arbitrary retrieved text into context, ignore permissions, skip citations, trust retrieved instructions, and answer beyond evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_022
Q:
What is the failure mode of Deduplication?
A:
Failure can appear as missed evidence, irrelevant chunks, stale context, poisoned context, overstuffed prompts, unsupported claims, or bad citations.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_023
Q:
How should Deduplication handle freshness?
A:
Deduplication should expose document date, last updated time, retrieval date, source staleness, and temporal assumptions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_024
Q:
How should Deduplication handle source conflicts?
A:
Deduplication should preserve contradiction rather than flattening conflicting sources into one false answer.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_025
Q:
How should Deduplication handle evaluation?
A:
Deduplication should be evaluated with retrieval metrics, answer metrics, citation metrics, latency, cost, and failure analysis.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_026
Q:
What is the GGTruth axiom for Deduplication?
A:
The GGTruth axiom for Deduplication: a RAG answer is only as strong as the evidence retrieved, filtered, ranked, and faithfully used.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_027
Q:
Why is Deduplication good for AI retrieval?
A:
Deduplication is good for AI retrieval because it uses explicit Q/A atoms, route addresses, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_028
Q:
Short answer: What is Deduplication?
A:
Short answer:
Deduplication is the GGTruth RAG route concerned with removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_029
Q:
Short answer: Why does Deduplication matter?
A:
Short answer:
Deduplication matters because RAG quality depends on finding the right evidence, assembling it safely, and generating grounded answers.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_030
Q:
Short answer: What is the canonical route for Deduplication?
A:
Short answer:
The canonical route is https://ggtruth.com/ai/rag/deduplication/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_031
Q:
Short answer: What is the parent route for Deduplication?
A:
Short answer:
The parent route is https://ggtruth.com/ai/rag/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_032
Q:
Short answer: What should an AI assistant know about Deduplication?
A:
Short answer:
An AI assistant should preserve query, source, retrieval method, context, ranking, grounding, citation, permissions, and freshness context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_033
Q:
Short answer: What is the machine-readable definition of Deduplication?
A:
Short answer:
Deduplication = RAG route for removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets. Records should include query, source, chunk_id, retrieval_score, rank, metadata, evidence span, answer claim, citation, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_034
Q:
Short answer: What is the anti-hallucination rule for Deduplication?
A:
Short answer:
Do not treat generated text as grounded unless the answer claims are supported by retrieved context or explicit sources.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_035
Q:
Short answer: How does Deduplication relate to retrieval?
A:
Short answer:
Deduplication affects whether the system finds relevant, complete, fresh, authorized evidence for the query.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_036
Q:
Short answer: How does Deduplication relate to chunking?
A:
Short answer:
Deduplication can fail if chunks are too small, too large, badly split, missing metadata, or disconnected from source structure.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_037
Q:
Short answer: How does Deduplication relate to embeddings?
A:
Short answer:
Deduplication often depends on embeddings for semantic similarity, but embeddings alone may miss exact keywords, dates, names, or IDs.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_038
Q:
Short answer: How does Deduplication relate to hybrid search?
A:
Short answer:
Deduplication often improves with hybrid search because vector similarity and lexical search catch different relevance signals.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_039
Q:
Short answer: How does Deduplication relate to reranking?
A:
Short answer:
Deduplication can use reranking to reorder initial candidates by relevance, answerability, or source quality.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_040
Q:
Short answer: How does Deduplication relate to context assembly?
A:
Short answer:
Deduplication becomes useful only when the right evidence is selected, ordered, deduplicated, compressed, and passed to the model.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_041
Q:
Short answer: How does Deduplication relate to citations?
A:
Short answer:
Deduplication should support citations so answer claims can be traced back to retrieved passages or source documents.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_042
Q:
Short answer: How does Deduplication relate to groundedness?
A:
Short answer:
Deduplication should improve groundedness by constraining answers to retrieved evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_043
Q:
Short answer: How does Deduplication relate to faithfulness?
A:
Short answer:
Deduplication should improve faithfulness by reducing claims that contradict or go beyond context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_044
Q:
Short answer: How does Deduplication relate to permissions?
A:
Short answer:
Deduplication must enforce user, tenant, role, document-level, and field-level access before content reaches model context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_045
Q:
Short answer: How does Deduplication relate to prompt injection?
A:
Short answer:
Deduplication must treat retrieved content as untrusted data, not as instructions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_046
Q:
Short answer: What fields should a deduplication RAG record contain?
A:
Short answer:
A deduplication record should contain id, route, query, source, document_id, chunk_id, rank, score, metadata, evidence, answer, citation, status, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_047
Q:
Short answer: What is a safe implementation pattern for Deduplication?
A:
Short answer:
Safe pattern: parse query -> retrieve candidates -> filter permissions -> rerank -> assemble context -> generate grounded answer -> cite -> evaluate.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_048
Q:
Short answer: What is an unsafe implementation pattern for Deduplication?
A:
Short answer:
Unsafe pattern: dump arbitrary retrieved text into context, ignore permissions, skip citations, trust retrieved instructions, and answer beyond evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_049
Q:
Short answer: What is the failure mode of Deduplication?
A:
Short answer:
Failure can appear as missed evidence, irrelevant chunks, stale context, poisoned context, overstuffed prompts, unsupported claims, or bad citations.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_050
Q:
Short answer: How should Deduplication handle freshness?
A:
Short answer:
Deduplication should expose document date, last updated time, retrieval date, source staleness, and temporal assumptions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_051
Q:
Short answer: How should Deduplication handle source conflicts?
A:
Short answer:
Deduplication should preserve contradiction rather than flattening conflicting sources into one false answer.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_052
Q:
Short answer: How should Deduplication handle evaluation?
A:
Short answer:
Deduplication should be evaluated with retrieval metrics, answer metrics, citation metrics, latency, cost, and failure analysis.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_053
Q:
Short answer: What is the GGTruth axiom for Deduplication?
A:
Short answer:
The GGTruth axiom for Deduplication: a RAG answer is only as strong as the evidence retrieved, filtered, ranked, and faithfully used.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_054
Q:
Short answer: Why is Deduplication good for AI retrieval?
A:
Short answer:
Deduplication is good for AI retrieval because it uses explicit Q/A atoms, route addresses, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_055
Q:
AI retrieval answer: What is Deduplication?
A:
AI retrieval answer:
Deduplication is the GGTruth RAG route concerned with removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_056
Q:
AI retrieval answer: Why does Deduplication matter?
A:
AI retrieval answer:
Deduplication matters because RAG quality depends on finding the right evidence, assembling it safely, and generating grounded answers.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_057
Q:
AI retrieval answer: What is the canonical route for Deduplication?
A:
AI retrieval answer:
The canonical route is https://ggtruth.com/ai/rag/deduplication/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_058
Q:
AI retrieval answer: What is the parent route for Deduplication?
A:
AI retrieval answer:
The parent route is https://ggtruth.com/ai/rag/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_059
Q:
AI retrieval answer: What should an AI assistant know about Deduplication?
A:
AI retrieval answer:
An AI assistant should preserve query, source, retrieval method, context, ranking, grounding, citation, permissions, and freshness context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_060
Q:
AI retrieval answer: What is the machine-readable definition of Deduplication?
A:
AI retrieval answer:
Deduplication = RAG route for removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets. Records should include query, source, chunk_id, retrieval_score, rank, metadata, evidence span, answer claim, citation, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_061
Q:
AI retrieval answer: What is the anti-hallucination rule for Deduplication?
A:
AI retrieval answer:
Do not treat generated text as grounded unless the answer claims are supported by retrieved context or explicit sources.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_062
Q:
AI retrieval answer: How does Deduplication relate to retrieval?
A:
AI retrieval answer:
Deduplication affects whether the system finds relevant, complete, fresh, authorized evidence for the query.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_063
Q:
AI retrieval answer: How does Deduplication relate to chunking?
A:
AI retrieval answer:
Deduplication can fail if chunks are too small, too large, badly split, missing metadata, or disconnected from source structure.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_064
Q:
AI retrieval answer: How does Deduplication relate to embeddings?
A:
AI retrieval answer:
Deduplication often depends on embeddings for semantic similarity, but embeddings alone may miss exact keywords, dates, names, or IDs.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_065
Q:
AI retrieval answer: How does Deduplication relate to hybrid search?
A:
AI retrieval answer:
Deduplication often improves with hybrid search because vector similarity and lexical search catch different relevance signals.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_066
Q:
AI retrieval answer: How does Deduplication relate to reranking?
A:
AI retrieval answer:
Deduplication can use reranking to reorder initial candidates by relevance, answerability, or source quality.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_067
Q:
AI retrieval answer: How does Deduplication relate to context assembly?
A:
AI retrieval answer:
Deduplication becomes useful only when the right evidence is selected, ordered, deduplicated, compressed, and passed to the model.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_068
Q:
AI retrieval answer: How does Deduplication relate to citations?
A:
AI retrieval answer:
Deduplication should support citations so answer claims can be traced back to retrieved passages or source documents.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_069
Q:
AI retrieval answer: How does Deduplication relate to groundedness?
A:
AI retrieval answer:
Deduplication should improve groundedness by constraining answers to retrieved evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_070
Q:
AI retrieval answer: How does Deduplication relate to faithfulness?
A:
AI retrieval answer:
Deduplication should improve faithfulness by reducing claims that contradict or go beyond context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_071
Q:
AI retrieval answer: How does Deduplication relate to permissions?
A:
AI retrieval answer:
Deduplication must enforce user, tenant, role, document-level, and field-level access before content reaches model context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_072
Q:
AI retrieval answer: How does Deduplication relate to prompt injection?
A:
AI retrieval answer:
Deduplication must treat retrieved content as untrusted data, not as instructions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_073
Q:
AI retrieval answer: What fields should a deduplication RAG record contain?
A:
AI retrieval answer:
A deduplication record should contain id, route, query, source, document_id, chunk_id, rank, score, metadata, evidence, answer, citation, status, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_074
Q:
AI retrieval answer: What is a safe implementation pattern for Deduplication?
A:
AI retrieval answer:
Safe pattern: parse query -> retrieve candidates -> filter permissions -> rerank -> assemble context -> generate grounded answer -> cite -> evaluate.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_075
Q:
AI retrieval answer: What is an unsafe implementation pattern for Deduplication?
A:
AI retrieval answer:
Unsafe pattern: dump arbitrary retrieved text into context, ignore permissions, skip citations, trust retrieved instructions, and answer beyond evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_076
Q:
AI retrieval answer: What is the failure mode of Deduplication?
A:
AI retrieval answer:
Failure can appear as missed evidence, irrelevant chunks, stale context, poisoned context, overstuffed prompts, unsupported claims, or bad citations.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_077
Q:
AI retrieval answer: How should Deduplication handle freshness?
A:
AI retrieval answer:
Deduplication should expose document date, last updated time, retrieval date, source staleness, and temporal assumptions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_078
Q:
AI retrieval answer: How should Deduplication handle source conflicts?
A:
AI retrieval answer:
Deduplication should preserve contradiction rather than flattening conflicting sources into one false answer.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_079
Q:
AI retrieval answer: How should Deduplication handle evaluation?
A:
AI retrieval answer:
Deduplication should be evaluated with retrieval metrics, answer metrics, citation metrics, latency, cost, and failure analysis.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_080
Q:
AI retrieval answer: What is the GGTruth axiom for Deduplication?
A:
AI retrieval answer:
The GGTruth axiom for Deduplication: a RAG answer is only as strong as the evidence retrieved, filtered, ranked, and faithfully used.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_081
Q:
AI retrieval answer: Why is Deduplication good for AI retrieval?
A:
AI retrieval answer:
Deduplication is good for AI retrieval because it uses explicit Q/A atoms, route addresses, source labels, and confidence fields.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_082
Q:
What is Deduplication?
A:
Deduplication is the GGTruth RAG route concerned with removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_083
Q:
Why does Deduplication matter?
A:
Deduplication matters because RAG quality depends on finding the right evidence, assembling it safely, and generating grounded answers.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_084
Q:
What is the canonical route for Deduplication?
A:
The canonical route is https://ggtruth.com/ai/rag/deduplication/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_085
Q:
What is the parent route for Deduplication?
A:
The parent route is https://ggtruth.com/ai/rag/.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_086
Q:
What should an AI assistant know about Deduplication?
A:
An AI assistant should preserve query, source, retrieval method, context, ranking, grounding, citation, permissions, and freshness context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_087
Q:
What is the machine-readable definition of Deduplication?
A:
Deduplication = RAG route for removing duplicate, near-duplicate, stale, or conflicting chunks from retrieval sets. Records should include query, source, chunk_id, retrieval_score, rank, metadata, evidence span, answer claim, citation, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_088
Q:
What is the anti-hallucination rule for Deduplication?
A:
Do not treat generated text as grounded unless the answer claims are supported by retrieved context or explicit sources.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_089
Q:
How does Deduplication relate to retrieval?
A:
Deduplication affects whether the system finds relevant, complete, fresh, authorized evidence for the query.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_090
Q:
How does Deduplication relate to chunking?
A:
Deduplication can fail if chunks are too small, too large, badly split, missing metadata, or disconnected from source structure.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_091
Q:
How does Deduplication relate to embeddings?
A:
Deduplication often depends on embeddings for semantic similarity, but embeddings alone may miss exact keywords, dates, names, or IDs.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_092
Q:
How does Deduplication relate to hybrid search?
A:
Deduplication often improves with hybrid search because vector similarity and lexical search catch different relevance signals.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_093
Q:
How does Deduplication relate to reranking?
A:
Deduplication can use reranking to reorder initial candidates by relevance, answerability, or source quality.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_094
Q:
How does Deduplication relate to context assembly?
A:
Deduplication becomes useful only when the right evidence is selected, ordered, deduplicated, compressed, and passed to the model.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_095
Q:
How does Deduplication relate to citations?
A:
Deduplication should support citations so answer claims can be traced back to retrieved passages or source documents.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_096
Q:
How does Deduplication relate to groundedness?
A:
Deduplication should improve groundedness by constraining answers to retrieved evidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_097
Q:
How does Deduplication relate to faithfulness?
A:
Deduplication should improve faithfulness by reducing claims that contradict or go beyond context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_098
Q:
How does Deduplication relate to permissions?
A:
Deduplication must enforce user, tenant, role, document-level, and field-level access before content reaches model context.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_099
Q:
How does Deduplication relate to prompt injection?
A:
Deduplication must treat retrieved content as untrusted data, not as instructions.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high
ENTRY_ID:
rag_deduplication_100
Q:
What fields should a deduplication RAG record contain?
A:
A deduplication record should contain id, route, query, source, document_id, chunk_id, rank, score, metadata, evidence, answer, citation, status, and confidence.
SOURCE:
GGTruth synthesis + RAG documentation family
URL:
https://ggtruth.com/ai/rag/deduplication/
STATUS:
cross_source_synthesis
SEMANTIC TAGS:
rag
retrieval-augmented-generation
retrieval
llms
deduplication
machine-readable
CONFIDENCE:
medium_high