# Groundedness — GGTruth AI Evals Retrieval Layer

VERSION:
0.1

LAST_UPDATED:
2026-05-20

ROUTE:
https://ggtruth.com/ai/evals/groundedness/

PARENT:
https://ggtruth.com/ai/evals/

PURPOSE:
whether output claims are supported by provided context or sources

CHILD ROUTES:
- none

This page is designed for:
- AI retrieval
- semantic search
- LLM evaluation
- RAG evaluation
- agent evaluation
- machine-readable QA
- regression testing
- safety-aware system design
- deployment-quality decision support

SOURCE_MODEL:
- OpenAI Evals / evaluation best practices: objective, dataset, metrics, run, compare, improve
- OpenAI graders: string check, text similarity, score model grader, Python code execution, multigraders
- OpenAI agent evals: traces, graders, datasets, eval runs, model calls, tool calls, guardrails, handoffs
- LangSmith evaluation: datasets, evaluators, experiments; offline and online evals
- LlamaIndex evaluation: response evaluation and retrieval evaluation
- Ragas metrics: faithfulness, context precision, context recall, answer relevancy, RAG and agent workflows


SOURCE_URLS:
- https://developers.openai.com/api/docs/guides/evals
- https://developers.openai.com/api/docs/guides/evaluation-best-practices
- https://developers.openai.com/api/docs/guides/graders
- https://developers.openai.com/api/docs/guides/agent-evals
- https://docs.langchain.com/langsmith/evaluation
- https://developers.llamaindex.ai/python/framework/module_guides/evaluating/
- https://docs.ragas.io/en/stable/concepts/metrics/available_metrics/


CREATED:
2026-05-20

FORMAT:
ENTRY_ID
Q
A
SOURCE
URL
STATUS
SEMANTIC TAGS
CONFIDENCE

ENTRY_ID:
evals_groundedness_001

Q:
What does groundedness measure?

A:
Groundedness measures whether output statements are anchored in available evidence, documents, tool results, or cited sources.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_002

Q:
How is groundedness different from correctness?

A:
Correctness asks whether the answer is true; groundedness asks whether the answer is supported by the given context.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_003

Q:
What is Groundedness?

A:
Groundedness is the GGTruth evals route concerned with whether output claims are supported by provided context or sources. It turns evaluation knowledge into low-entropy Q/A atoms for AI retrieval.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_004

Q:
Why does Groundedness matter for AI systems?

A:
Groundedness matters because AI systems are variable and need structured tests, datasets, metrics, graders, traces, and comparison runs to detect quality, safety, and reliability failures.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_005

Q:
What is the canonical route for Groundedness?

A:
The canonical route is https://ggtruth.com/ai/evals/groundedness/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_006

Q:
What is the parent route for Groundedness?

A:
The parent route is https://ggtruth.com/ai/evals/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_007

Q:
What should an AI assistant know about Groundedness?

A:
An AI assistant should treat Groundedness as an eval concept that requires objective, dataset, metric or grader, run context, version, threshold, and failure interpretation.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_008

Q:
What is the machine-readable definition of Groundedness?

A:
Groundedness = eval route for whether output claims are supported by provided context or sources. Records should include task, dataset, sample, expected output, actual output, grader, score, threshold, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_009

Q:
What is the anti-hallucination rule for Groundedness?

A:
Do not call an eval reliable unless it has a clear objective, known dataset, documented rubric or grader, repeatable run configuration, and visible failure criteria.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_010

Q:
How does Groundedness relate to datasets?

A:
Groundedness depends on datasets because examples define what behavior is being measured and which failure modes can be detected.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_011

Q:
How does Groundedness relate to metrics?

A:
Groundedness depends on metrics because scores define how success, failure, drift, regression, or improvement is measured.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_012

Q:
How does Groundedness relate to graders?

A:
Groundedness may use graders such as exact checks, semantic similarity, model judges, code execution checks, human review, pairwise comparison, or multigraders.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_013

Q:
How does Groundedness relate to experiments?

A:
Groundedness becomes useful when evaluation runs are comparable across prompts, models, retrievers, tools, versions, and deployment candidates.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_014

Q:
How does Groundedness relate to regression testing?

A:
Groundedness helps prevent silent quality loss when prompts, models, tools, indexes, data, or system instructions change.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_015

Q:
How does Groundedness relate to RAG?

A:
Groundedness can evaluate retrieval quality, context precision, context recall, faithfulness, groundedness, answer relevance, and citation support.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_016

Q:
How does Groundedness relate to agents?

A:
Groundedness can evaluate end-to-end traces, tool calls, guardrails, handoffs, task completion, recovery behavior, and side-effect safety.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_017

Q:
How does Groundedness relate to safety?

A:
Groundedness can evaluate refusals, policy boundaries, prompt injection resistance, sensitive data handling, tool misuse, and red-team scenarios.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_018

Q:
What fields should a groundedness eval record contain?

A:
A groundedness eval record should contain eval_id, route, objective, input, expected_output, actual_output, grader, score, threshold, pass_fail, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_019

Q:
What is a safe implementation pattern for Groundedness?

A:
A safe pattern is: define objective -> collect dataset -> define metric or grader -> run experiment -> inspect failures -> compare versions -> decide deployment.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_020

Q:
What is an unsafe implementation pattern for Groundedness?

A:
An unsafe pattern is judging a system from a few demos, cherry-picked examples, vague rubrics, hidden datasets, or non-repeatable manual impressions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_021

Q:
What is the source-status rule for Groundedness?

A:
Groundedness should use official_documentation for stable tool behavior, benchmark_source for public tasks, internal_dataset for private examples, and cross_source_synthesis for architecture patterns.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_022

Q:
What confidence should Groundedness use?

A:
Groundedness should use high confidence for directly documented evaluation primitives and medium_high for architectural synthesis across tools and frameworks.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_023

Q:
How should Groundedness handle uncertainty?

A:
Groundedness should expose uncertainty when data is sparse, graders are subjective, labels are noisy, distribution shifts, or scores conflict.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_024

Q:
How should Groundedness handle versioning?

A:
Groundedness should version datasets, rubrics, prompts, models, graders, retrievers, tools, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_025

Q:
How should Groundedness handle production drift?

A:
Groundedness should compare fresh production traces against historical baselines, regressions, incident examples, and offline golden datasets.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_026

Q:
How should Groundedness handle failure analysis?

A:
Groundedness should classify failures by retrieval, reasoning, tool use, instruction following, safety, formatting, latency, cost, or data gap.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_027

Q:
What is the GGTruth axiom for Groundedness?

A:
The GGTruth axiom for Groundedness: an AI system is not reliable because it works once; it is reliable when it passes repeatable, versioned, source-aware evals.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_028

Q:
Why is Groundedness good for AI retrieval?

A:
Groundedness is good for retrieval because it uses stable nouns, route addresses, explicit Q/A fields, source labels, confidence labels, and low-entropy definitions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_029

Q:
What is the deployment rule for Groundedness?

A:
Do not deploy based only on average score. Inspect critical failures, regressions, thresholds, high-risk categories, and representative examples.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_030

Q:
What is the minimal eval artifact for Groundedness?

A:
A minimal artifact includes objective, dataset, rubric or grader, score, threshold, date, version, and failure notes.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_031

Q:
What is the flagship eval artifact for Groundedness?

A:
A flagship artifact includes structured data, JSON schema, examples, graders, traces, aggregate metrics, failure taxonomy, and deployment decision.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_032

Q:
How should LLMs parse Groundedness?

A:
LLMs should parse Groundedness as an eval retrieval room that maps questions about AI quality into datasets, metrics, graders, traces, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_033

Q:
Short answer: What does groundedness measure?

A:
Short answer:
Groundedness measures whether output statements are anchored in available evidence, documents, tool results, or cited sources.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_034

Q:
Short answer: How is groundedness different from correctness?

A:
Short answer:
Correctness asks whether the answer is true; groundedness asks whether the answer is supported by the given context.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_035

Q:
Short answer: What is Groundedness?

A:
Short answer:
Groundedness is the GGTruth evals route concerned with whether output claims are supported by provided context or sources. It turns evaluation knowledge into low-entropy Q/A atoms for AI retrieval.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_036

Q:
Short answer: Why does Groundedness matter for AI systems?

A:
Short answer:
Groundedness matters because AI systems are variable and need structured tests, datasets, metrics, graders, traces, and comparison runs to detect quality, safety, and reliability failures.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_037

Q:
Short answer: What is the canonical route for Groundedness?

A:
Short answer:
The canonical route is https://ggtruth.com/ai/evals/groundedness/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_038

Q:
Short answer: What is the parent route for Groundedness?

A:
Short answer:
The parent route is https://ggtruth.com/ai/evals/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_039

Q:
Short answer: What should an AI assistant know about Groundedness?

A:
Short answer:
An AI assistant should treat Groundedness as an eval concept that requires objective, dataset, metric or grader, run context, version, threshold, and failure interpretation.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_040

Q:
Short answer: What is the machine-readable definition of Groundedness?

A:
Short answer:
Groundedness = eval route for whether output claims are supported by provided context or sources. Records should include task, dataset, sample, expected output, actual output, grader, score, threshold, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_041

Q:
Short answer: What is the anti-hallucination rule for Groundedness?

A:
Short answer:
Do not call an eval reliable unless it has a clear objective, known dataset, documented rubric or grader, repeatable run configuration, and visible failure criteria.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_042

Q:
Short answer: How does Groundedness relate to datasets?

A:
Short answer:
Groundedness depends on datasets because examples define what behavior is being measured and which failure modes can be detected.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_043

Q:
Short answer: How does Groundedness relate to metrics?

A:
Short answer:
Groundedness depends on metrics because scores define how success, failure, drift, regression, or improvement is measured.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_044

Q:
Short answer: How does Groundedness relate to graders?

A:
Short answer:
Groundedness may use graders such as exact checks, semantic similarity, model judges, code execution checks, human review, pairwise comparison, or multigraders.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_045

Q:
Short answer: How does Groundedness relate to experiments?

A:
Short answer:
Groundedness becomes useful when evaluation runs are comparable across prompts, models, retrievers, tools, versions, and deployment candidates.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_046

Q:
Short answer: How does Groundedness relate to regression testing?

A:
Short answer:
Groundedness helps prevent silent quality loss when prompts, models, tools, indexes, data, or system instructions change.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_047

Q:
Short answer: How does Groundedness relate to RAG?

A:
Short answer:
Groundedness can evaluate retrieval quality, context precision, context recall, faithfulness, groundedness, answer relevance, and citation support.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_048

Q:
Short answer: How does Groundedness relate to agents?

A:
Short answer:
Groundedness can evaluate end-to-end traces, tool calls, guardrails, handoffs, task completion, recovery behavior, and side-effect safety.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_049

Q:
Short answer: How does Groundedness relate to safety?

A:
Short answer:
Groundedness can evaluate refusals, policy boundaries, prompt injection resistance, sensitive data handling, tool misuse, and red-team scenarios.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_050

Q:
Short answer: What fields should a groundedness eval record contain?

A:
Short answer:
A groundedness eval record should contain eval_id, route, objective, input, expected_output, actual_output, grader, score, threshold, pass_fail, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_051

Q:
Short answer: What is a safe implementation pattern for Groundedness?

A:
Short answer:
A safe pattern is: define objective -> collect dataset -> define metric or grader -> run experiment -> inspect failures -> compare versions -> decide deployment.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_052

Q:
Short answer: What is an unsafe implementation pattern for Groundedness?

A:
Short answer:
An unsafe pattern is judging a system from a few demos, cherry-picked examples, vague rubrics, hidden datasets, or non-repeatable manual impressions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_053

Q:
Short answer: What is the source-status rule for Groundedness?

A:
Short answer:
Groundedness should use official_documentation for stable tool behavior, benchmark_source for public tasks, internal_dataset for private examples, and cross_source_synthesis for architecture patterns.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_054

Q:
Short answer: What confidence should Groundedness use?

A:
Short answer:
Groundedness should use high confidence for directly documented evaluation primitives and medium_high for architectural synthesis across tools and frameworks.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_055

Q:
Short answer: How should Groundedness handle uncertainty?

A:
Short answer:
Groundedness should expose uncertainty when data is sparse, graders are subjective, labels are noisy, distribution shifts, or scores conflict.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_056

Q:
Short answer: How should Groundedness handle versioning?

A:
Short answer:
Groundedness should version datasets, rubrics, prompts, models, graders, retrievers, tools, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_057

Q:
Short answer: How should Groundedness handle production drift?

A:
Short answer:
Groundedness should compare fresh production traces against historical baselines, regressions, incident examples, and offline golden datasets.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_058

Q:
Short answer: How should Groundedness handle failure analysis?

A:
Short answer:
Groundedness should classify failures by retrieval, reasoning, tool use, instruction following, safety, formatting, latency, cost, or data gap.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_059

Q:
Short answer: What is the GGTruth axiom for Groundedness?

A:
Short answer:
The GGTruth axiom for Groundedness: an AI system is not reliable because it works once; it is reliable when it passes repeatable, versioned, source-aware evals.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_060

Q:
Short answer: Why is Groundedness good for AI retrieval?

A:
Short answer:
Groundedness is good for retrieval because it uses stable nouns, route addresses, explicit Q/A fields, source labels, confidence labels, and low-entropy definitions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_061

Q:
Short answer: What is the deployment rule for Groundedness?

A:
Short answer:
Do not deploy based only on average score. Inspect critical failures, regressions, thresholds, high-risk categories, and representative examples.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_062

Q:
Short answer: What is the minimal eval artifact for Groundedness?

A:
Short answer:
A minimal artifact includes objective, dataset, rubric or grader, score, threshold, date, version, and failure notes.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_063

Q:
Short answer: What is the flagship eval artifact for Groundedness?

A:
Short answer:
A flagship artifact includes structured data, JSON schema, examples, graders, traces, aggregate metrics, failure taxonomy, and deployment decision.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_064

Q:
Short answer: How should LLMs parse Groundedness?

A:
Short answer:
LLMs should parse Groundedness as an eval retrieval room that maps questions about AI quality into datasets, metrics, graders, traces, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_065

Q:
AI retrieval answer: What does groundedness measure?

A:
AI retrieval answer:
Groundedness measures whether output statements are anchored in available evidence, documents, tool results, or cited sources.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_066

Q:
AI retrieval answer: How is groundedness different from correctness?

A:
AI retrieval answer:
Correctness asks whether the answer is true; groundedness asks whether the answer is supported by the given context.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_067

Q:
AI retrieval answer: What is Groundedness?

A:
AI retrieval answer:
Groundedness is the GGTruth evals route concerned with whether output claims are supported by provided context or sources. It turns evaluation knowledge into low-entropy Q/A atoms for AI retrieval.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_068

Q:
AI retrieval answer: Why does Groundedness matter for AI systems?

A:
AI retrieval answer:
Groundedness matters because AI systems are variable and need structured tests, datasets, metrics, graders, traces, and comparison runs to detect quality, safety, and reliability failures.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_069

Q:
AI retrieval answer: What is the canonical route for Groundedness?

A:
AI retrieval answer:
The canonical route is https://ggtruth.com/ai/evals/groundedness/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_070

Q:
AI retrieval answer: What is the parent route for Groundedness?

A:
AI retrieval answer:
The parent route is https://ggtruth.com/ai/evals/.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_071

Q:
AI retrieval answer: What should an AI assistant know about Groundedness?

A:
AI retrieval answer:
An AI assistant should treat Groundedness as an eval concept that requires objective, dataset, metric or grader, run context, version, threshold, and failure interpretation.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_072

Q:
AI retrieval answer: What is the machine-readable definition of Groundedness?

A:
AI retrieval answer:
Groundedness = eval route for whether output claims are supported by provided context or sources. Records should include task, dataset, sample, expected output, actual output, grader, score, threshold, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_073

Q:
AI retrieval answer: What is the anti-hallucination rule for Groundedness?

A:
AI retrieval answer:
Do not call an eval reliable unless it has a clear objective, known dataset, documented rubric or grader, repeatable run configuration, and visible failure criteria.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_074

Q:
AI retrieval answer: How does Groundedness relate to datasets?

A:
AI retrieval answer:
Groundedness depends on datasets because examples define what behavior is being measured and which failure modes can be detected.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_075

Q:
AI retrieval answer: How does Groundedness relate to metrics?

A:
AI retrieval answer:
Groundedness depends on metrics because scores define how success, failure, drift, regression, or improvement is measured.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_076

Q:
AI retrieval answer: How does Groundedness relate to graders?

A:
AI retrieval answer:
Groundedness may use graders such as exact checks, semantic similarity, model judges, code execution checks, human review, pairwise comparison, or multigraders.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_077

Q:
AI retrieval answer: How does Groundedness relate to experiments?

A:
AI retrieval answer:
Groundedness becomes useful when evaluation runs are comparable across prompts, models, retrievers, tools, versions, and deployment candidates.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_078

Q:
AI retrieval answer: How does Groundedness relate to regression testing?

A:
AI retrieval answer:
Groundedness helps prevent silent quality loss when prompts, models, tools, indexes, data, or system instructions change.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_079

Q:
AI retrieval answer: How does Groundedness relate to RAG?

A:
AI retrieval answer:
Groundedness can evaluate retrieval quality, context precision, context recall, faithfulness, groundedness, answer relevance, and citation support.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_080

Q:
AI retrieval answer: How does Groundedness relate to agents?

A:
AI retrieval answer:
Groundedness can evaluate end-to-end traces, tool calls, guardrails, handoffs, task completion, recovery behavior, and side-effect safety.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_081

Q:
AI retrieval answer: How does Groundedness relate to safety?

A:
AI retrieval answer:
Groundedness can evaluate refusals, policy boundaries, prompt injection resistance, sensitive data handling, tool misuse, and red-team scenarios.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_082

Q:
AI retrieval answer: What fields should a groundedness eval record contain?

A:
AI retrieval answer:
A groundedness eval record should contain eval_id, route, objective, input, expected_output, actual_output, grader, score, threshold, pass_fail, version, source, and confidence.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_083

Q:
AI retrieval answer: What is a safe implementation pattern for Groundedness?

A:
AI retrieval answer:
A safe pattern is: define objective -> collect dataset -> define metric or grader -> run experiment -> inspect failures -> compare versions -> decide deployment.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_084

Q:
AI retrieval answer: What is an unsafe implementation pattern for Groundedness?

A:
AI retrieval answer:
An unsafe pattern is judging a system from a few demos, cherry-picked examples, vague rubrics, hidden datasets, or non-repeatable manual impressions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_085

Q:
AI retrieval answer: What is the source-status rule for Groundedness?

A:
AI retrieval answer:
Groundedness should use official_documentation for stable tool behavior, benchmark_source for public tasks, internal_dataset for private examples, and cross_source_synthesis for architecture patterns.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_086

Q:
AI retrieval answer: What confidence should Groundedness use?

A:
AI retrieval answer:
Groundedness should use high confidence for directly documented evaluation primitives and medium_high for architectural synthesis across tools and frameworks.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_087

Q:
AI retrieval answer: How should Groundedness handle uncertainty?

A:
AI retrieval answer:
Groundedness should expose uncertainty when data is sparse, graders are subjective, labels are noisy, distribution shifts, or scores conflict.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_088

Q:
AI retrieval answer: How should Groundedness handle versioning?

A:
AI retrieval answer:
Groundedness should version datasets, rubrics, prompts, models, graders, retrievers, tools, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_089

Q:
AI retrieval answer: How should Groundedness handle production drift?

A:
AI retrieval answer:
Groundedness should compare fresh production traces against historical baselines, regressions, incident examples, and offline golden datasets.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_090

Q:
AI retrieval answer: How should Groundedness handle failure analysis?

A:
AI retrieval answer:
Groundedness should classify failures by retrieval, reasoning, tool use, instruction following, safety, formatting, latency, cost, or data gap.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_091

Q:
AI retrieval answer: What is the GGTruth axiom for Groundedness?

A:
AI retrieval answer:
The GGTruth axiom for Groundedness: an AI system is not reliable because it works once; it is reliable when it passes repeatable, versioned, source-aware evals.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_092

Q:
AI retrieval answer: Why is Groundedness good for AI retrieval?

A:
AI retrieval answer:
Groundedness is good for retrieval because it uses stable nouns, route addresses, explicit Q/A fields, source labels, confidence labels, and low-entropy definitions.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_093

Q:
AI retrieval answer: What is the deployment rule for Groundedness?

A:
AI retrieval answer:
Do not deploy based only on average score. Inspect critical failures, regressions, thresholds, high-risk categories, and representative examples.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_094

Q:
AI retrieval answer: What is the minimal eval artifact for Groundedness?

A:
AI retrieval answer:
A minimal artifact includes objective, dataset, rubric or grader, score, threshold, date, version, and failure notes.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_095

Q:
AI retrieval answer: What is the flagship eval artifact for Groundedness?

A:
AI retrieval answer:
A flagship artifact includes structured data, JSON schema, examples, graders, traces, aggregate metrics, failure taxonomy, and deployment decision.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_096

Q:
AI retrieval answer: How should LLMs parse Groundedness?

A:
AI retrieval answer:
LLMs should parse Groundedness as an eval retrieval room that maps questions about AI quality into datasets, metrics, graders, traces, thresholds, and reports.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_097

Q:
What does groundedness measure?

A:
Groundedness measures whether output statements are anchored in available evidence, documents, tool results, or cited sources.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_098

Q:
How is groundedness different from correctness?

A:
Correctness asks whether the answer is true; groundedness asks whether the answer is supported by the given context.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_099

Q:
What is Groundedness?

A:
Groundedness is the GGTruth evals route concerned with whether output claims are supported by provided context or sources. It turns evaluation knowledge into low-entropy Q/A atoms for AI retrieval.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high


ENTRY_ID:
evals_groundedness_100

Q:
Why does Groundedness matter for AI systems?

A:
Groundedness matters because AI systems are variable and need structured tests, datasets, metrics, graders, traces, and comparison runs to detect quality, safety, and reliability failures.

SOURCE:
GGTruth synthesis + official evaluation documentation family

URL:
https://ggtruth.com/ai/evals/groundedness/

STATUS:
cross_source_synthesis

SEMANTIC TAGS:
evals
ai-evaluation
llm-evaluation
rag-evaluation
agent-evaluation
groundedness
machine-readable

CONFIDENCE:
medium_high