Get a separate answer for each reading
Intent
Section titled “Intent”I want to get a separate answer for each reading.
Wrong form and why it stays silent
Section titled “Wrong form and why it stays silent”Mixing alternative results means executing a third program that the author did not choose.
alternatives Broad;Correct form
Section titled “Correct form”language "law.core" version "0.2";package recipe.m07 version "1.0.0";namespace "urn:recipe:m-queries:07";source Act { kind policy; }edition E of Act { language ru; officiality unofficial; materialization_status ABSTRACT_ONLY; in_force [@2026-01-01, infinity); }fragment F in E { kind article; locator "1"; text ru unofficial "Учебная норма имеет два прочтения."; }entity Person;relation filed(p: Person);relation accepted(p: Person);rule Allow strict { for p: Person; when filed(p); then accepted(p); }rule Deny strict { for p: Person; when filed(p); then not accepted(p); }interpretation Broad of F { status disputed; include Allow; }interpretation Narrow of F { status disputed; include Deny; }interpretation_group Meaning { alternatives Broad, Narrow; selection exactly_one; }Frozen execution scene
Section titled “Frozen execution scene”| Input / variant | Question | Expectation |
|---|---|---|
| 1. both branches separately | interpretation_analysis(Meaning, truth(accepted(entity_ref("urn:recipe:m-queries:p")))) | evaluation_status == INTERPRETATION_REQUIRED; |
| 2. broad | truth(accepted(entity_ref("urn:recipe:m-queries:p"))) | truth_status == TRUE_ONLY; evaluation_status == COMPUTED; |
| 3. narrow | truth(accepted(entity_ref("urn:recipe:m-queries:p"))) | truth_status == FALSE_ONLY; evaluation_status == COMPUTED; |
both readings answered separately
test "both readings answered separately" { given { context { legal_time @2026-09-13; decision_time @2026-09-13T09:00:00Z; knowledge_time @2026-09-13T09:00:00Z; timezone "UTC"; } assert filed(entity_ref("urn:recipe:m-queries:p")); } evaluate interpretation_analysis(Meaning, truth(accepted(entity_ref("urn:recipe:m-queries:p")))); expect evaluation_status == INTERPRETATION_REQUIRED;}broad reading establishes
test "broad reading establishes" { given { context { legal_time @2026-09-13; decision_time @2026-09-13T09:00:00Z; knowledge_time @2026-09-13T09:00:00Z; timezone "UTC"; interpretation Broad; } assert filed(entity_ref("urn:recipe:m-queries:p")); } evaluate truth(accepted(entity_ref("urn:recipe:m-queries:p"))); expect truth_status == TRUE_ONLY; expect evaluation_status == COMPUTED;}narrow reading refutes
test "narrow reading refutes" { given { context { legal_time @2026-09-13; decision_time @2026-09-13T09:00:00Z; knowledge_time @2026-09-13T09:00:00Z; timezone "UTC"; interpretation Narrow; } assert filed(entity_ref("urn:recipe:m-queries:p")); } evaluate truth(accepted(entity_ref("urn:recipe:m-queries:p"))); expect truth_status == FALSE_ONLY; expect evaluation_status == COMPUTED;}Nested results are pinned by the reading StableId:
| Reading | truthStatus | evaluationStatus |
|---|---|---|
| Broad | TRUE_ONLY | COMPUTED |
| Narrow | FALSE_ONLY | COMPUTED |
They match the separate scenes 2 and 3. The outer DATA result measured INTERPRETATION_REQUIRED: the current status projection keeps the absence of a choice from the original case. Results stay separate, but no separate rule sets the outer analysis status; this is an interface boundary, not a claim that nested branches were uncomputed.
Scene 1 runs on both evaluators, but the canonical documents differ in exactly four paths: the nested per-reading hashes of both alternatives and the derived proof and result hashes. The nested answers themselves match, and the separate scenes 2 and 3 keep full parity. Scene 1 therefore lives in resources and is pinned by the adapter to that concrete gap without normalization; the normative expectation is checked by both engines.
The analysis test is shown in a lawtest block: lower-test knows this form, while a program check, if the test is placed in law, reports E2105/E2109. This is inconsistency of surface stages; the nested hash divergence below is pinned separately.
Check of result fields and extra inputs:
>>> import runpy>>> checks = runpy.run_path("docs/recipes/m-queries/resources/check.py")>>> checks["alternatives"](https://github.com/arxohq/law/blob/master/docs/recipes/m-queries/7)TrueCounterfactual
Section titled “Counterfactual”The sidecar mutation reproduces LDC-E0201. Counterfactual table variants are executed separately; input errors are not passed off as NEITHER.
Boundary
Section titled “Boundary”results_by_interpretation is a descriptive record. The surface query is interpretation_analysis; nesting is allowed once. No separate result of the example is Contradiction.
Pitfall
Section titled “Pitfall”A choice must not leak between independent runs — see Two readings of one norm.
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