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The alternative, “Retry with bounded exponential backoff and an idempotent operation identifier”, can matter in another part of the workflow. This is not a substitute for “Ask for a bounded correction of the invalid field while preserving validated fields; Enforce record-level invariants after the field correction; Revalidate the corrected postal code and its schema constraints before persisting”; that control is necessary in the stated circumstances. When nineteen fields have passed validation, request a correction to only the invalid postal code and preserve the other field values and their evidence.

Deleting validation history removes evidence of why the field was corrected and whether the replacement satisfied the schema. Keep the prior validated fields intact, revalidate the corrected field and record the result before persisting.

Discarding confirmed data creates needless regression opportunities. The nineteen verified fields should remain stable while the defective postal code is repaired. Replacing them with guesses needlessly expands the error surface and makes the new output less traceable.

Feedback strings can carry adversarial instructions. That addresses a different part of the system, not the requirement to route unresolved source contradictions to human judgment.

Format and business validators can detect malformed totals, but the document contains two conflicting plausible amounts from different pages. Neither can be selected confidently from syntax alone. Preserve both source locations and escalate the contradiction for evidence-based reconciliation.

A maximum retry count prevents infinite correction cycles, but does not decide which contradictory financial total is supported. Further retries may produce more guesses. Preserve both figures with their source locations and escalate the ambiguity to a qualified review step.

Replacing an entire record can introduce fresh errors in already-correct fields. Although useful elsewhere, it is not the direct mechanism to prevent data-carried instructions from hijacking retries.

Business invariants can reject contradictory statuses, but they do not authorize the model to obey a prompt embedded in untrusted validation-error text. Keep the error payload as data and maintain higher-priority instruction boundaries while making any correction.

A bounded retry limit controls cost, but does not stop a prompt injection inside a validation error from attempting to override the workflow. Treat the source text as untrusted evidence and enforce the same security policy on every correction attempt.

Precise diagnostics help the model target the defect. That addresses a different part of the system, not the requirement to retry transient infrastructure failures safely.

Logging attempt counts and final dispositions makes errors auditable, but the 503 is a transient service failure requiring a bounded retry policy. Use exponential backoff and stable request identity to avoid hammering the service or accidentally replaying a committed operation.

A corrective retry needs to know which field failed and why. This alternative—Supply the exact validation error and source text in a bounded correction request—does not implement the specific operation that the question asks about. The required control is Retry with bounded exponential backoff and an idempotent operation identifier. Transient service failures may recover.

A retry ceiling is important when the parser repeatedly fails, but the current error identifies a specific invalid currency symbol that might be repaired. Return the exact field-level validation error in a bounded corrective attempt while retaining all fields already validated; escalate only if correction fails.

Explicit missing-data handling is safer than inventing an invoice identifier. Here, an extractor returns an invalid currency symbol for a supported transaction field. Send the exact validation error back for a bounded corrective retry. Targeted feedback lets the model repair the specific failed field rather than guessing why output was rejected.

Arithmetic checks detect totals that fail to reconcile, whereas the current defect is an invalid currency symbol in one supported field. Supply the field-specific type or allowed-value error and request a bounded correction without unnecessarily regenerating verified amounts.

Explicit missing-data handling is safer than inventing an invoice identifier. Here, a contract parser repeatedly fails the same schema check. Cap retries and escalate or return a controlled failure. Unbounded repair loops can waste resources without improving invalid extraction.

Business validation must supplement schema validation because well-formed JSON can still contain false values. Here, a contract parser repeatedly fails the same schema check. Cap retries and escalate or return a controlled failure. Unbounded repair loops can waste resources without improving invalid extraction.

Actionable validator messages narrow the model's correction task. The proposed option cannot provide the specific “Cap retries and escalate or return a controlled failure” behavior that the case requires. Unbounded repair loops can waste resources without improving invalid extraction.

Business validation must supplement schema validation because well-formed JSON can still contain false values. This is not a substitute for “Mark the required field unknown and route through the defined exception policy”; that control is necessary in the stated circumstances. Explicit missing-data handling is safer than inventing an invoice identifier.

Actionable validator messages narrow the model's correction task. Here, a document contains no invoice number but downstream requires a decision. Mark the required field unknown and route through the defined exception policy. Explicit missing-data handling is safer than inventing an invoice identifier.

Localized repair prevents regression of already validated data. The proposed option cannot provide the specific “Mark the required field unknown and route through the defined exception policy” behavior that the case requires. Explicit missing-data handling is safer than inventing an invoice identifier.

A field-level type check can establish that each date parses, but it does not establish the logical order of a policy period. Accepting a start date after the end date makes the contract timeline internally inconsistent.

Changing token limits controls the maximum output length, not the validity of the relationship between the two dates. The validator should detect the ordering error and provide explicit field-level feedback.

Deleting an inconsistent field hides a source or extraction problem and removes evidence required by downstream decisions. Preserve the original values for audit and reject or correct the invalid chronological relationship.

Localized repair prevents regression of already validated data. Here, a validator returns ten failures but the retry prompt provides only 'try again'. Return precise field paths, expected types and observed errors. Actionable validator messages narrow the model's correction task.

Validation and approval thresholds should reflect the consequence of a wrong decision. The direct remedy is “Return precise field paths, expected types and observed errors”, which the alternative does not itself accomplish. Actionable validator messages narrow the model's correction task.

A generic retry repeats the defect this scenario already describes. Without the failing field paths, observed values and expected types, the model cannot make a targeted correction. Return precise machine-readable validation details and bound the number of retry attempts instead of using an uninformative prompt.

Validation and approval thresholds should reflect the consequence of a wrong decision. Here, a repaired extraction changed correct fields unnecessarily. Compare field-level diffs and restrict retries to invalid portions. Localized repair prevents regression of already validated data.

Targeted feedback lets the model repair the specific failed field rather than guessing why output was rejected. The proposed option cannot provide the specific “Compare field-level diffs and restrict retries to invalid portions” behavior that the case requires. Localized repair prevents regression of already validated data.

Unbounded repair loops can waste resources without improving invalid extraction. Here, a repaired extraction changed correct fields unnecessarily. Compare field-level diffs and restrict retries to invalid portions. Localized repair prevents regression of already validated data.

Targeted feedback lets the model repair the specific failed field rather than guessing why output was rejected. Here, an extractor returns low-confidence totals and the business action is irreversible. Require human confirmation before committing the transaction. Validation and approval thresholds should reflect the consequence of a wrong decision.

Capping retries avoids endless schema repair, but the problem is an uncertain total that could trigger an irreversible transaction. Even a syntactically valid extraction can be wrong; the system must require authorized human confirmation before committing the high-consequence business action.

Explicit missing-data handling is safer than inventing an invoice identifier. The direct remedy is “Require human confirmation before committing the transaction”, which the alternative does not itself accomplish. Validation and approval thresholds should reflect the consequence of a wrong decision.