FideAI

Paper 01

FID-056

August 2026

When Not to Generate

How AI Systems Quote Scripture, and What Authoritative Quotation Requires

Which system design is most reliable when the user asks for the exact words of a source of record?

Alex Chao · Fide AI · 8,640 matched requests · 6 model families · 3 open English editions

Finding

Memory produced the requested text exactly in one quarter of trials.

Supplying the passage directly produced 93.61% exact delivery. An authorized lookup tool reached 80.09%. Deterministic insertion, where code rather than the model writes the selected source text, reached 91.25%.

All three source-backed designs still produced mismatches. The failures occurred at different points between selecting a reference and showing the final text.

Interactive delivery designs · 8,640 requests

Four ways to produce the same quotation, with four different points of failure.

Choose a design to see what work belonged to the model, what belonged to the surrounding system, and how often the complete delivery path succeeded.

Selected design

Native parametric quotation

Model owns

The model identifies the passage and writes every word from its parameters.

System owns

The surrounding system supplies instructions but no source text or source tool.

Observed path across all 2,160 trials

2,160

requests

540

exact deliveries

1,620 deliveries did not match exactly.

What the result shows

Exact quotation should not be assumed to emerge reliably from model memory, even for familiar passages.

Where it can fail

Wrong wording, omitted or blended text, refusals, truncation, and provider errors can all produce a mismatch.

Exact delivery
25.00%
Exact trials
540 / 2,160
Not exact
1,620 / 2,160
Difference from memory
Baseline

The quotation path

Four stages stand between a reference and the text a user sees.

Move through the path to see how responsibility shifts across designs and where fidelity can be lost.

The question at this stage

Which work, edition, passage, and span does the request identify?

The first failure can happen before any source text is retrieved. Contextual descriptions require the system to infer a reference, while explicit requests provide one directly.

A wrong or unparseable reference sends every later stage down the wrong path.

Memory

Selection is implicit in the text the model generates.

Source supplied

The caller has already selected and supplied the source.

Tool

The model resolves the reference it sends to the tool.

Deterministic

The model emits a structured reference for the renderer.

Observed end-to-end counts

Where the trials finished

The stage tabs explain responsibility. These counts report the observed condition-level paths.

From memory

2,160

requests

540

exact

1,620 did not match exactly.

Source supplied

2,160

passages supplied

2,022

exact

138 were not exact.

Authorized tool

2,160

tool available

2,052

tool invoked

1,730

exact

108 bypassed the tool; 322 invoked it without completing the exact path.

Deterministic

2,160

requests

1,973

selection and lookup

1,971

exact

Corrected result; the locked score was 1,813 exact deliveries.

Experiment

The four designs assigned different work to the model.

The study tests matched Scripture requests across six model families and three open English editions: the Berean Standard Bible, World English Bible Updated, and Literal Standard Version.

The four conditions assign different work to the model and the surrounding software. Their rates should be read as results for complete delivery designs, not as equal-burden model comparisons.

The study does not evaluate interpretation, theological adequacy, copyrighted editions, non-English sources, or every interface through which text may be delivered.

Released records and full-condition results

One request, four ways to deliver the quotation.

Follow the same John 3:16 request through each delivery design. Every tab begins with one released run, then shows the result across all 2,160 trials assigned to that design.

Kept the same in the released runs

Requested passage
John 3:16
Authorized edition
Literal Standard Version
Model
Kimi K3
Prompt form
Contextual description

System assignment

Model generates from memory

No source text or lookup tool is supplied. The model identifies the passage and writes every word.

One released run

Authorized source provided?
No
Model wrote the quotation?
Yes
Exact final output?
No
Terminal provider error?
No

The model returned an answer, but the quotation did not match the authorized passage exactly. The release records the score without publishing the generated prose.

Across all 2,160 trials in this design

25.00%

exact delivery

540 exact 1,620 not exact

2,160

requests

540

exact deliveries

Three quarters of deliveries did not match exactly when the model wrote from memory.

Technical record details
Model route
moonshotai/kimi-k3
Epoch
3
Repetition
1
Released record ID
337b1b14d47474ee0148f316

Primary outcome

Exact delivery

The final quotation matched the authorized passage and the system followed its assigned delivery method. Exact words alone do not count as success when the required path was bypassed.

Disclosed correction

Parser replay

The deterministic condition was rescored after an audit found recoverable reference formats that the locked parser had rejected. The release retains both the original and corrected fields.

The records above illustrate individual runs. The rates beside them summarize all 2,160 trials in each design. The public release contains derived scores and provenance fields, but excludes generated prose, authoritative passage text, provider response identifiers, credentials, and raw tool traces.

Paper and data

BibTeX
@misc{chao2026whennottogenerate,
  title  = {When Not to Generate: How AI Systems Quote Scripture, and What Authoritative Quotation Requires},
  author = {Chao, Alex},
  year   = {2026},
  note   = {Fide AI. Study FID-056-P01.},
  url    = {https://github.com/FideAI/scripture-quotation-fidelity}
}