diff --git "a/data/dynamic_dialogue/train.jsonl" "b/data/dynamic_dialogue/train.jsonl"
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+{"id": "dynamic_dialogue_v3_0000", "base_id": "cloud_deployment_0241_closed_missing_direct", "split": "train", "domain": "cloud_deployment", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Service B has deployment approval.", "query_atom": "has_deployment_approval::Service B", "facts_positive": ["Service B passed unit tests."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["passed_unit_tests::Service B"], "negative_atoms": [], "rules": [], "query_atom": "has_deployment_approval::Service B", "closure_atoms": ["passed_unit_tests::Service B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service B passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Service B has deployment approval.\nTarget atom: has_deployment_approval::Service B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service B has deployment approval.\nTarget atom: has_deployment_approval::Service B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval"], "complete_predicates_after_update": ["has_deployment_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval\n\nTarget statement: Service B has deployment approval.\nTarget atom: has_deployment_approval::Service B"}]}
+{"id": "dynamic_dialogue_v3_0001", "base_id": "cloud_deployment_0248_closed_missing_with_open_distractor", "split": "train", "domain": "cloud_deployment", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Service C has deployment approval.", "query_atom": "has_deployment_approval::Service C", "facts_positive": ["Service D has an incident note.", "Service C passed unit tests."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["has_incident_note::Service D", "passed_unit_tests::Service C"], "negative_atoms": [], "rules": [], "query_atom": "has_deployment_approval::Service C", "closure_atoms": ["has_incident_note::Service D", "passed_unit_tests::Service C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service D has an incident note.\n- Service C passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Service C has deployment approval.\nTarget atom: has_deployment_approval::Service C\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service C has deployment approval.\nTarget atom: has_deployment_approval::Service C"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval"], "complete_predicates_after_update": ["has_deployment_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval\n\nTarget statement: Service C has deployment approval.\nTarget atom: has_deployment_approval::Service C"}]}
+{"id": "dynamic_dialogue_v3_0002", "base_id": "cloud_deployment_0249_closed_missing_with_open_distractor", "split": "train", "domain": "cloud_deployment", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Service D has deployment approval.", "query_atom": "has_deployment_approval::Service D", "facts_positive": ["Service E has an incident note.", "Service D passed unit tests."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["has_incident_note::Service E", "passed_unit_tests::Service D"], "negative_atoms": [], "rules": [], "query_atom": "has_deployment_approval::Service D", "closure_atoms": ["has_incident_note::Service E", "passed_unit_tests::Service D"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service E has an incident note.\n- Service D passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Service D has deployment approval.\nTarget atom: has_deployment_approval::Service D\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service D has deployment approval.\nTarget atom: has_deployment_approval::Service D"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval"], "complete_predicates_after_update": ["has_deployment_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval\n\nTarget statement: Service D has deployment approval.\nTarget atom: has_deployment_approval::Service D"}]}
+{"id": "dynamic_dialogue_v3_0004", "base_id": "cloud_deployment_0253_open_missing_with_closed_distractor", "split": "train", "domain": "cloud_deployment", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Service B has an incident note.", "query_atom": "has_incident_note::Service B", "facts_positive": ["Service C has deployment approval.", "Service C passed unit tests."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["has_deployment_approval::Service C", "passed_unit_tests::Service C"], "negative_atoms": [], "rules": [], "query_atom": "has_incident_note::Service B", "closure_atoms": ["has_deployment_approval::Service C", "passed_unit_tests::Service C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service C has deployment approval.\n- Service C passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Service B has an incident note.\nTarget atom: has_incident_note::Service B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service B has an incident note.\nTarget atom: has_incident_note::Service B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "may_deploy"], "complete_predicates_after_update": ["has_deployment_approval", "may_deploy"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval, may_deploy\n\nTarget statement: Service B has an incident note.\nTarget atom: has_incident_note::Service B"}]}
+{"id": "dynamic_dialogue_v3_0006", "base_id": "cloud_deployment_0257_closed_derived_missing_antecedent", "split": "train", "domain": "cloud_deployment", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Service F may deploy to production.", "query_atom": "may_deploy::Service F", "facts_positive": ["Service F passed unit tests."], "facts_negative": [], "rules_natural": ["If a service passed unit tests and has deployment approval, then that service may deploy to production."], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["passed_unit_tests::Service F"], "negative_atoms": [], "rules": [{"antecedents": ["passed_unit_tests::Service F", "has_deployment_approval::Service F"], "conclusion": "may_deploy::Service F", "text": "If a service passed unit tests and has deployment approval, then that service may deploy to production."}], "query_atom": "may_deploy::Service F", "closure_atoms": ["passed_unit_tests::Service F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service F passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- If a service passed unit tests and has deployment approval, then that service may deploy to production.\n\nTarget statement: Service F may deploy to production.\nTarget atom: may_deploy::Service F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service F may deploy to production.\nTarget atom: may_deploy::Service F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "may_deploy"], "complete_predicates_after_update": ["has_deployment_approval", "may_deploy"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval, may_deploy\n\nTarget statement: Service F may deploy to production.\nTarget atom: may_deploy::Service F"}]}
+{"id": "dynamic_dialogue_v3_0007", "base_id": "cloud_deployment_0260_open_derived_missing_antecedent", "split": "train", "domain": "cloud_deployment", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Service C needs SRE review.", "query_atom": "needs_sre_review::Service C", "facts_positive": ["Service C passed unit tests."], "facts_negative": [], "rules_natural": ["If a service has an incident note, then that service needs SRE review."], "predicate_glossary": {"passed_unit_tests": "passed unit tests", "has_deployment_approval": "has deployment approval", "has_incident_note": "has an incident note", "may_deploy": "may deploy to production", "needs_sre_review": "needs SRE review"}, "vocabulary_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "symbolic": {"positive_atoms": ["passed_unit_tests::Service C"], "negative_atoms": [], "rules": [{"antecedents": ["has_incident_note::Service C"], "conclusion": "needs_sre_review::Service C", "text": "If a service has an incident note, then that service needs SRE review."}], "query_atom": "needs_sre_review::Service C", "closure_atoms": ["passed_unit_tests::Service C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_deployment_approval: has deployment approval\n- has_incident_note: has an incident note\n- may_deploy: may deploy to production\n- needs_sre_review: needs SRE review\n- passed_unit_tests: passed unit tests\n\nPositive facts:\n- Service C passed unit tests.\n\nNegative facts:\n- none\n\nRules:\n- If a service has an incident note, then that service needs SRE review.\n\nTarget statement: Service C needs SRE review.\nTarget atom: needs_sre_review::Service C\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "complete_predicates_after_update": ["has_deployment_approval", "has_incident_note", "may_deploy", "needs_sre_review", "passed_unit_tests"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n- Complete predicates after this update: has_deployment_approval, has_incident_note, may_deploy, needs_sre_review, passed_unit_tests\n\nTarget statement: Service C needs SRE review.\nTarget atom: needs_sre_review::Service C"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_deployment_approval", "may_deploy"], "complete_predicates_after_update": ["has_deployment_approval", "may_deploy"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_deployment_approval, may_deploy\n\nTarget statement: Service C needs SRE review.\nTarget atom: needs_sre_review::Service C"}]}
+{"id": "dynamic_dialogue_v3_0008", "base_id": "finance_controls_0120_closed_missing_direct", "split": "train", "domain": "finance_controls", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 12 has compliance clearance.", "query_atom": "has_compliance_clearance::Account 12", "facts_positive": ["Account 12 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 12"], "negative_atoms": [], "rules": [], "query_atom": "has_compliance_clearance::Account 12", "closure_atoms": ["passed_kyc::Account 12"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 12 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 12 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 12\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 12 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 12"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance"], "complete_predicates_after_update": ["has_compliance_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance\n\nTarget statement: Account 12 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 12"}]}
+{"id": "dynamic_dialogue_v3_0009", "base_id": "finance_controls_0122_closed_missing_direct", "split": "train", "domain": "finance_controls", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 35 has compliance clearance.", "query_atom": "has_compliance_clearance::Account 35", "facts_positive": ["Account 35 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 35"], "negative_atoms": [], "rules": [], "query_atom": "has_compliance_clearance::Account 35", "closure_atoms": ["passed_kyc::Account 35"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 35 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 35 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 35\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 35 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 35"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance"], "complete_predicates_after_update": ["has_compliance_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance\n\nTarget statement: Account 35 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 35"}]}
+{"id": "dynamic_dialogue_v3_0010", "base_id": "finance_controls_0125_open_missing_direct", "split": "train", "domain": "finance_controls", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 61 has a manual exception.", "query_atom": "has_manual_exception::Account 61", "facts_positive": ["Account 61 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 61"], "negative_atoms": [], "rules": [], "query_atom": "has_manual_exception::Account 61", "closure_atoms": ["passed_kyc::Account 61"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 61 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 61 has a manual exception.\nTarget atom: has_manual_exception::Account 61\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 61 has a manual exception.\nTarget atom: has_manual_exception::Account 61"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 61 has a manual exception.\nTarget atom: has_manual_exception::Account 61"}]}
+{"id": "dynamic_dialogue_v3_0011", "base_id": "finance_controls_0129_closed_missing_with_open_distractor", "split": "train", "domain": "finance_controls", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 48 has compliance clearance.", "query_atom": "has_compliance_clearance::Account 48", "facts_positive": ["Account 59 has a manual exception.", "Account 48 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["has_manual_exception::Account 59", "passed_kyc::Account 48"], "negative_atoms": [], "rules": [], "query_atom": "has_compliance_clearance::Account 48", "closure_atoms": ["has_manual_exception::Account 59", "passed_kyc::Account 48"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 59 has a manual exception.\n- Account 48 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 48 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 48\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 48 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 48"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance"], "complete_predicates_after_update": ["has_compliance_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance\n\nTarget statement: Account 48 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 48"}]}
+{"id": "dynamic_dialogue_v3_0013", "base_id": "finance_controls_0131_closed_missing_with_open_distractor", "split": "train", "domain": "finance_controls", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 61 has compliance clearance.", "query_atom": "has_compliance_clearance::Account 61", "facts_positive": ["Account 12 has a manual exception.", "Account 61 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["has_manual_exception::Account 12", "passed_kyc::Account 61"], "negative_atoms": [], "rules": [], "query_atom": "has_compliance_clearance::Account 61", "closure_atoms": ["has_manual_exception::Account 12", "passed_kyc::Account 61"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 12 has a manual exception.\n- Account 61 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 61 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 61\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 61 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 61"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance"], "complete_predicates_after_update": ["has_compliance_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance\n\nTarget statement: Account 61 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 61"}]}
+{"id": "dynamic_dialogue_v3_0014", "base_id": "finance_controls_0132_open_missing_with_closed_distractor", "split": "train", "domain": "finance_controls", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 12 has a manual exception.", "query_atom": "has_manual_exception::Account 12", "facts_positive": ["Account 27 has compliance clearance.", "Account 27 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["has_compliance_clearance::Account 27", "passed_kyc::Account 27"], "negative_atoms": [], "rules": [], "query_atom": "has_manual_exception::Account 12", "closure_atoms": ["has_compliance_clearance::Account 27", "passed_kyc::Account 27"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 27 has compliance clearance.\n- Account 27 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 12 has a manual exception.\nTarget atom: has_manual_exception::Account 12\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 12 has a manual exception.\nTarget atom: has_manual_exception::Account 12"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 12 has a manual exception.\nTarget atom: has_manual_exception::Account 12"}]}
+{"id": "dynamic_dialogue_v3_0015", "base_id": "finance_controls_0135_open_missing_with_closed_distractor", "split": "train", "domain": "finance_controls", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 48 has a manual exception.", "query_atom": "has_manual_exception::Account 48", "facts_positive": ["Account 59 has compliance clearance.", "Account 59 passed KYC checks."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["has_compliance_clearance::Account 59", "passed_kyc::Account 59"], "negative_atoms": [], "rules": [], "query_atom": "has_manual_exception::Account 48", "closure_atoms": ["has_compliance_clearance::Account 59", "passed_kyc::Account 59"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 59 has compliance clearance.\n- Account 59 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 48 has a manual exception.\nTarget atom: has_manual_exception::Account 48\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 48 has a manual exception.\nTarget atom: has_manual_exception::Account 48"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 48 has a manual exception.\nTarget atom: has_manual_exception::Account 48"}]}
+{"id": "dynamic_dialogue_v3_0017", "base_id": "finance_controls_0137_closed_derived_missing_antecedent", "split": "train", "domain": "finance_controls", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 61 may receive a wire transfer.", "query_atom": "may_receive_wire::Account 61", "facts_positive": ["Account 61 passed KYC checks."], "facts_negative": [], "rules_natural": ["If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer."], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 61"], "negative_atoms": [], "rules": [{"antecedents": ["passed_kyc::Account 61", "has_compliance_clearance::Account 61"], "conclusion": "may_receive_wire::Account 61", "text": "If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer."}], "query_atom": "may_receive_wire::Account 61", "closure_atoms": ["passed_kyc::Account 61"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 61 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer.\n\nTarget statement: Account 61 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 61\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 61 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 61"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 61 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 61"}]}
+{"id": "dynamic_dialogue_v3_0019", "base_id": "finance_controls_0139_closed_derived_missing_antecedent", "split": "train", "domain": "finance_controls", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 27 may receive a wire transfer.", "query_atom": "may_receive_wire::Account 27", "facts_positive": ["Account 27 passed KYC checks."], "facts_negative": [], "rules_natural": ["If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer."], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 27"], "negative_atoms": [], "rules": [{"antecedents": ["passed_kyc::Account 27", "has_compliance_clearance::Account 27"], "conclusion": "may_receive_wire::Account 27", "text": "If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer."}], "query_atom": "may_receive_wire::Account 27", "closure_atoms": ["passed_kyc::Account 27"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 27 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer.\n\nTarget statement: Account 27 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 27\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 27 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 27"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 27 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 27"}]}
+{"id": "dynamic_dialogue_v3_0020", "base_id": "finance_controls_0140_open_derived_missing_antecedent", "split": "train", "domain": "finance_controls", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 35 needs compliance review.", "query_atom": "needs_compliance_review::Account 35", "facts_positive": ["Account 35 passed KYC checks."], "facts_negative": [], "rules_natural": ["If an account has a manual exception, then that account needs compliance review."], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 35"], "negative_atoms": [], "rules": [{"antecedents": ["has_manual_exception::Account 35"], "conclusion": "needs_compliance_review::Account 35", "text": "If an account has a manual exception, then that account needs compliance review."}], "query_atom": "needs_compliance_review::Account 35", "closure_atoms": ["passed_kyc::Account 35"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 35 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- If an account has a manual exception, then that account needs compliance review.\n\nTarget statement: Account 35 needs compliance review.\nTarget atom: needs_compliance_review::Account 35\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 35 needs compliance review.\nTarget atom: needs_compliance_review::Account 35"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 35 needs compliance review.\nTarget atom: needs_compliance_review::Account 35"}]}
+{"id": "dynamic_dialogue_v3_0021", "base_id": "finance_controls_0141_open_derived_missing_antecedent", "split": "train", "domain": "finance_controls", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 48 needs compliance review.", "query_atom": "needs_compliance_review::Account 48", "facts_positive": ["Account 48 passed KYC checks."], "facts_negative": [], "rules_natural": ["If an account has a manual exception, then that account needs compliance review."], "predicate_glossary": {"passed_kyc": "passed KYC checks", "has_compliance_clearance": "has compliance clearance", "has_manual_exception": "has a manual exception", "may_receive_wire": "may receive a wire transfer", "needs_compliance_review": "needs compliance review"}, "vocabulary_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "symbolic": {"positive_atoms": ["passed_kyc::Account 48"], "negative_atoms": [], "rules": [{"antecedents": ["has_manual_exception::Account 48"], "conclusion": "needs_compliance_review::Account 48", "text": "If an account has a manual exception, then that account needs compliance review."}], "query_atom": "needs_compliance_review::Account 48", "closure_atoms": ["passed_kyc::Account 48"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_compliance_clearance: has compliance clearance\n- has_manual_exception: has a manual exception\n- may_receive_wire: may receive a wire transfer\n- needs_compliance_review: needs compliance review\n- passed_kyc: passed KYC checks\n\nPositive facts:\n- Account 48 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- If an account has a manual exception, then that account needs compliance review.\n\nTarget statement: Account 48 needs compliance review.\nTarget atom: needs_compliance_review::Account 48\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "complete_predicates_after_update": ["has_compliance_clearance", "has_manual_exception", "may_receive_wire", "needs_compliance_review", "passed_kyc"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n- Complete predicates after this update: has_compliance_clearance, has_manual_exception, may_receive_wire, needs_compliance_review, passed_kyc\n\nTarget statement: Account 48 needs compliance review.\nTarget atom: needs_compliance_review::Account 48"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_compliance_clearance", "may_receive_wire"], "complete_predicates_after_update": ["has_compliance_clearance", "may_receive_wire"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_compliance_clearance, may_receive_wire\n\nTarget statement: Account 48 needs compliance review.\nTarget atom: needs_compliance_review::Account 48"}]}
+{"id": "dynamic_dialogue_v3_0023", "base_id": "hospital_access_0000_closed_missing_direct", "split": "train", "domain": "hospital_access", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Ava has security clearance.", "query_atom": "has_clearance::Ava", "facts_positive": ["Ava has completed safety training."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Ava"], "negative_atoms": [], "rules": [], "query_atom": "has_clearance::Ava", "closure_atoms": ["completed_training::Ava"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Ava has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Ava has security clearance.\nTarget atom: has_clearance::Ava\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Ava has security clearance.\nTarget atom: has_clearance::Ava"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance"], "complete_predicates_after_update": ["has_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance\n\nTarget statement: Ava has security clearance.\nTarget atom: has_clearance::Ava"}]}
+{"id": "dynamic_dialogue_v3_0025", "base_id": "hospital_access_0007_open_missing_direct", "split": "train", "domain": "hospital_access", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Ben is assigned to the clinical trial.", "query_atom": "assigned_to_trial::Ben", "facts_positive": ["Ben has completed safety training."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Ben"], "negative_atoms": [], "rules": [], "query_atom": "assigned_to_trial::Ben", "closure_atoms": ["completed_training::Ben"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Ben has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben"}]}
+{"id": "dynamic_dialogue_v3_0028", "base_id": "hospital_access_0010_closed_missing_with_open_distractor", "split": "train", "domain": "hospital_access", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Elena has security clearance.", "query_atom": "has_clearance::Elena", "facts_positive": ["Farid is assigned to the clinical trial.", "Elena has completed safety training."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["assigned_to_trial::Farid", "completed_training::Elena"], "negative_atoms": [], "rules": [], "query_atom": "has_clearance::Elena", "closure_atoms": ["assigned_to_trial::Farid", "completed_training::Elena"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Farid is assigned to the clinical trial.\n- Elena has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Elena has security clearance.\nTarget atom: has_clearance::Elena\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Elena has security clearance.\nTarget atom: has_clearance::Elena"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance"], "complete_predicates_after_update": ["has_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance\n\nTarget statement: Elena has security clearance.\nTarget atom: has_clearance::Elena"}]}
+{"id": "dynamic_dialogue_v3_0029", "base_id": "hospital_access_0013_open_missing_with_closed_distractor", "split": "train", "domain": "hospital_access", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Ben is assigned to the clinical trial.", "query_atom": "assigned_to_trial::Ben", "facts_positive": ["Cora has completed safety training.", "Cora has security clearance."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Cora", "has_clearance::Cora"], "negative_atoms": [], "rules": [], "query_atom": "assigned_to_trial::Ben", "closure_atoms": ["completed_training::Cora", "has_clearance::Cora"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Cora has completed safety training.\n- Cora has security clearance.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Ben is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Ben"}]}
+{"id": "dynamic_dialogue_v3_0030", "base_id": "hospital_access_0015_open_missing_with_closed_distractor", "split": "train", "domain": "hospital_access", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Dylan is assigned to the clinical trial.", "query_atom": "assigned_to_trial::Dylan", "facts_positive": ["Elena has completed safety training.", "Elena has security clearance."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Elena", "has_clearance::Elena"], "negative_atoms": [], "rules": [], "query_atom": "assigned_to_trial::Dylan", "closure_atoms": ["completed_training::Elena", "has_clearance::Elena"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Elena has completed safety training.\n- Elena has security clearance.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Dylan is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Dylan\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Dylan is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Dylan"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Dylan is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Dylan"}]}
+{"id": "dynamic_dialogue_v3_0032", "base_id": "hospital_access_0018_closed_derived_missing_antecedent", "split": "train", "domain": "hospital_access", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Ava may enter Lab A.", "query_atom": "may_enter_lab::Ava", "facts_positive": ["Ava has completed safety training."], "facts_negative": [], "rules_natural": ["If a staff member has security clearance and has completed safety training, then that staff member may enter Lab A."], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Ava"], "negative_atoms": [], "rules": [{"antecedents": ["completed_training::Ava", "has_clearance::Ava"], "conclusion": "may_enter_lab::Ava", "text": "If a staff member has security clearance and has completed safety training, then that staff member may enter Lab A."}], "query_atom": "may_enter_lab::Ava", "closure_atoms": ["completed_training::Ava"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Ava has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- If a staff member has security clearance and has completed safety training, then that staff member may enter Lab A.\n\nTarget statement: Ava may enter Lab A.\nTarget atom: may_enter_lab::Ava\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Ava may enter Lab A.\nTarget atom: may_enter_lab::Ava"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Ava may enter Lab A.\nTarget atom: may_enter_lab::Ava"}]}
+{"id": "dynamic_dialogue_v3_0034", "base_id": "hospital_access_0022_open_derived_missing_antecedent", "split": "train", "domain": "hospital_access", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Elena needs supervisor review.", "query_atom": "needs_supervisor_review::Elena", "facts_positive": ["Elena has completed safety training."], "facts_negative": [], "rules_natural": ["If a staff member is assigned to the clinical trial, then that staff member needs supervisor review."], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Elena"], "negative_atoms": [], "rules": [{"antecedents": ["assigned_to_trial::Elena"], "conclusion": "needs_supervisor_review::Elena", "text": "If a staff member is assigned to the clinical trial, then that staff member needs supervisor review."}], "query_atom": "needs_supervisor_review::Elena", "closure_atoms": ["completed_training::Elena"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Elena has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- If a staff member is assigned to the clinical trial, then that staff member needs supervisor review.\n\nTarget statement: Elena needs supervisor review.\nTarget atom: needs_supervisor_review::Elena\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Elena needs supervisor review.\nTarget atom: needs_supervisor_review::Elena"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Elena needs supervisor review.\nTarget atom: needs_supervisor_review::Elena"}]}
+{"id": "dynamic_dialogue_v3_0035", "base_id": "hospital_access_0023_open_derived_missing_antecedent", "split": "train", "domain": "hospital_access", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Farid needs supervisor review.", "query_atom": "needs_supervisor_review::Farid", "facts_positive": ["Farid has completed safety training."], "facts_negative": [], "rules_natural": ["If a staff member is assigned to the clinical trial, then that staff member needs supervisor review."], "predicate_glossary": {"completed_training": "has completed safety training", "has_clearance": "has security clearance", "assigned_to_trial": "is assigned to the clinical trial", "may_enter_lab": "may enter Lab A", "needs_supervisor_review": "needs supervisor review"}, "vocabulary_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "symbolic": {"positive_atoms": ["completed_training::Farid"], "negative_atoms": [], "rules": [{"antecedents": ["assigned_to_trial::Farid"], "conclusion": "needs_supervisor_review::Farid", "text": "If a staff member is assigned to the clinical trial, then that staff member needs supervisor review."}], "query_atom": "needs_supervisor_review::Farid", "closure_atoms": ["completed_training::Farid"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- assigned_to_trial: is assigned to the clinical trial\n- completed_training: has completed safety training\n- has_clearance: has security clearance\n- may_enter_lab: may enter Lab A\n- needs_supervisor_review: needs supervisor review\n\nPositive facts:\n- Farid has completed safety training.\n\nNegative facts:\n- none\n\nRules:\n- If a staff member is assigned to the clinical trial, then that staff member needs supervisor review.\n\nTarget statement: Farid needs supervisor review.\nTarget atom: needs_supervisor_review::Farid\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "complete_predicates_after_update": ["assigned_to_trial", "completed_training", "has_clearance", "may_enter_lab", "needs_supervisor_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n- Complete predicates after this update: assigned_to_trial, completed_training, has_clearance, may_enter_lab, needs_supervisor_review\n\nTarget statement: Farid needs supervisor review.\nTarget atom: needs_supervisor_review::Farid"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_clearance", "may_enter_lab"], "complete_predicates_after_update": ["has_clearance", "may_enter_lab"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_clearance, may_enter_lab\n\nTarget statement: Farid needs supervisor review.\nTarget atom: needs_supervisor_review::Farid"}]}
+{"id": "dynamic_dialogue_v3_0036", "base_id": "library_services_0202_closed_missing_direct", "split": "train", "domain": "library_services", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Reader E has borrowing clearance.", "query_atom": "has_borrowing_clearance::Reader E", "facts_positive": ["Reader E has an active membership."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader E"], "negative_atoms": [], "rules": [], "query_atom": "has_borrowing_clearance::Reader E", "closure_atoms": ["has_active_membership::Reader E"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader E has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader E has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader E\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader E has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader E"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance"], "complete_predicates_after_update": ["has_borrowing_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance\n\nTarget statement: Reader E has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader E"}]}
+{"id": "dynamic_dialogue_v3_0037", "base_id": "library_services_0203_closed_missing_direct", "split": "train", "domain": "library_services", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Reader F has borrowing clearance.", "query_atom": "has_borrowing_clearance::Reader F", "facts_positive": ["Reader F has an active membership."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader F"], "negative_atoms": [], "rules": [], "query_atom": "has_borrowing_clearance::Reader F", "closure_atoms": ["has_active_membership::Reader F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader F has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader F has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader F has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance"], "complete_predicates_after_update": ["has_borrowing_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance\n\nTarget statement: Reader F has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader F"}]}
+{"id": "dynamic_dialogue_v3_0038", "base_id": "library_services_0204_open_missing_direct", "split": "train", "domain": "library_services", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Reader A has a special request.", "query_atom": "has_special_request::Reader A", "facts_positive": ["Reader A has an active membership."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader A"], "negative_atoms": [], "rules": [], "query_atom": "has_special_request::Reader A", "closure_atoms": ["has_active_membership::Reader A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader A has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader A has a special request.\nTarget atom: has_special_request::Reader A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader A has a special request.\nTarget atom: has_special_request::Reader A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance", "may_borrow_archive_item"], "complete_predicates_after_update": ["has_borrowing_clearance", "may_borrow_archive_item"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance, may_borrow_archive_item\n\nTarget statement: Reader A has a special request.\nTarget atom: has_special_request::Reader A"}]}
+{"id": "dynamic_dialogue_v3_0039", "base_id": "library_services_0205_open_missing_direct", "split": "train", "domain": "library_services", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Reader B has a special request.", "query_atom": "has_special_request::Reader B", "facts_positive": ["Reader B has an active membership."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader B"], "negative_atoms": [], "rules": [], "query_atom": "has_special_request::Reader B", "closure_atoms": ["has_active_membership::Reader B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader B has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader B has a special request.\nTarget atom: has_special_request::Reader B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader B has a special request.\nTarget atom: has_special_request::Reader B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance", "may_borrow_archive_item"], "complete_predicates_after_update": ["has_borrowing_clearance", "may_borrow_archive_item"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance, may_borrow_archive_item\n\nTarget statement: Reader B has a special request.\nTarget atom: has_special_request::Reader B"}]}
+{"id": "dynamic_dialogue_v3_0041", "base_id": "library_services_0207_open_missing_direct", "split": "train", "domain": "library_services", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Reader D has a special request.", "query_atom": "has_special_request::Reader D", "facts_positive": ["Reader D has an active membership."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader D"], "negative_atoms": [], "rules": [], "query_atom": "has_special_request::Reader D", "closure_atoms": ["has_active_membership::Reader D"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader D has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader D has a special request.\nTarget atom: has_special_request::Reader D\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader D has a special request.\nTarget atom: has_special_request::Reader D"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance", "may_borrow_archive_item"], "complete_predicates_after_update": ["has_borrowing_clearance", "may_borrow_archive_item"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance, may_borrow_archive_item\n\nTarget statement: Reader D has a special request.\nTarget atom: has_special_request::Reader D"}]}
+{"id": "dynamic_dialogue_v3_0043", "base_id": "library_services_0210_closed_missing_with_open_distractor", "split": "train", "domain": "library_services", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Reader A has borrowing clearance.", "query_atom": "has_borrowing_clearance::Reader A", "facts_positive": ["Reader A has an active membership.", "Reader B has a special request."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader A", "has_special_request::Reader B"], "negative_atoms": [], "rules": [], "query_atom": "has_borrowing_clearance::Reader A", "closure_atoms": ["has_active_membership::Reader A", "has_special_request::Reader B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader A has an active membership.\n- Reader B has a special request.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader A has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader A has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance"], "complete_predicates_after_update": ["has_borrowing_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance\n\nTarget statement: Reader A has borrowing clearance.\nTarget atom: has_borrowing_clearance::Reader A"}]}
+{"id": "dynamic_dialogue_v3_0044", "base_id": "library_services_0214_open_missing_with_closed_distractor", "split": "train", "domain": "library_services", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Reader E has a special request.", "query_atom": "has_special_request::Reader E", "facts_positive": ["Reader F has an active membership.", "Reader F has borrowing clearance."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader F", "has_borrowing_clearance::Reader F"], "negative_atoms": [], "rules": [], "query_atom": "has_special_request::Reader E", "closure_atoms": ["has_active_membership::Reader F", "has_borrowing_clearance::Reader F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader F has an active membership.\n- Reader F has borrowing clearance.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Reader E has a special request.\nTarget atom: has_special_request::Reader E\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader E has a special request.\nTarget atom: has_special_request::Reader E"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance", "may_borrow_archive_item"], "complete_predicates_after_update": ["has_borrowing_clearance", "may_borrow_archive_item"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance, may_borrow_archive_item\n\nTarget statement: Reader E has a special request.\nTarget atom: has_special_request::Reader E"}]}
+{"id": "dynamic_dialogue_v3_0046", "base_id": "library_services_0219_closed_derived_missing_antecedent", "split": "train", "domain": "library_services", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Reader D may borrow an archive item.", "query_atom": "may_borrow_archive_item::Reader D", "facts_positive": ["Reader D has an active membership."], "facts_negative": [], "rules_natural": ["If a reader has an active membership and has borrowing clearance, then that reader may borrow an archive item."], "predicate_glossary": {"has_active_membership": "has an active membership", "has_borrowing_clearance": "has borrowing clearance", "has_special_request": "has a special request", "may_borrow_archive_item": "may borrow an archive item", "needs_librarian_review": "needs librarian review"}, "vocabulary_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "symbolic": {"positive_atoms": ["has_active_membership::Reader D"], "negative_atoms": [], "rules": [{"antecedents": ["has_active_membership::Reader D", "has_borrowing_clearance::Reader D"], "conclusion": "may_borrow_archive_item::Reader D", "text": "If a reader has an active membership and has borrowing clearance, then that reader may borrow an archive item."}], "query_atom": "may_borrow_archive_item::Reader D", "closure_atoms": ["has_active_membership::Reader D"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_active_membership: has an active membership\n- has_borrowing_clearance: has borrowing clearance\n- has_special_request: has a special request\n- may_borrow_archive_item: may borrow an archive item\n- needs_librarian_review: needs librarian review\n\nPositive facts:\n- Reader D has an active membership.\n\nNegative facts:\n- none\n\nRules:\n- If a reader has an active membership and has borrowing clearance, then that reader may borrow an archive item.\n\nTarget statement: Reader D may borrow an archive item.\nTarget atom: may_borrow_archive_item::Reader D\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "complete_predicates_after_update": ["has_active_membership", "has_borrowing_clearance", "has_special_request", "may_borrow_archive_item", "needs_librarian_review"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n- Complete predicates after this update: has_active_membership, has_borrowing_clearance, has_special_request, may_borrow_archive_item, needs_librarian_review\n\nTarget statement: Reader D may borrow an archive item.\nTarget atom: may_borrow_archive_item::Reader D"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_borrowing_clearance", "may_borrow_archive_item"], "complete_predicates_after_update": ["has_borrowing_clearance", "may_borrow_archive_item"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_borrowing_clearance, may_borrow_archive_item\n\nTarget statement: Reader D may borrow an archive item.\nTarget atom: may_borrow_archive_item::Reader D"}]}
+{"id": "dynamic_dialogue_v3_0048", "base_id": "manufacturing_quality_0083_closed_missing_direct", "split": "train", "domain": "manufacturing_quality", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Part F has release approval.", "query_atom": "has_release_approval::Part F", "facts_positive": ["Part F passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part F"], "negative_atoms": [], "rules": [], "query_atom": "has_release_approval::Part F", "closure_atoms": ["passed_visual_check::Part F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part F passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part F has release approval.\nTarget atom: has_release_approval::Part F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part F has release approval.\nTarget atom: has_release_approval::Part F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval"], "complete_predicates_after_update": ["has_release_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval\n\nTarget statement: Part F has release approval.\nTarget atom: has_release_approval::Part F"}]}
+{"id": "dynamic_dialogue_v3_0049", "base_id": "manufacturing_quality_0084_open_missing_direct", "split": "train", "domain": "manufacturing_quality", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part A has a supplier note.", "query_atom": "has_supplier_note::Part A", "facts_positive": ["Part A passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part A"], "negative_atoms": [], "rules": [], "query_atom": "has_supplier_note::Part A", "closure_atoms": ["passed_visual_check::Part A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part A passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part A has a supplier note.\nTarget atom: has_supplier_note::Part A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part A has a supplier note.\nTarget atom: has_supplier_note::Part A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part A has a supplier note.\nTarget atom: has_supplier_note::Part A"}]}
+{"id": "dynamic_dialogue_v3_0050", "base_id": "manufacturing_quality_0086_open_missing_direct", "split": "train", "domain": "manufacturing_quality", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part C has a supplier note.", "query_atom": "has_supplier_note::Part C", "facts_positive": ["Part C passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part C"], "negative_atoms": [], "rules": [], "query_atom": "has_supplier_note::Part C", "closure_atoms": ["passed_visual_check::Part C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part C passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part C has a supplier note.\nTarget atom: has_supplier_note::Part C\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part C has a supplier note.\nTarget atom: has_supplier_note::Part C"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part C has a supplier note.\nTarget atom: has_supplier_note::Part C"}]}
+{"id": "dynamic_dialogue_v3_0051", "base_id": "manufacturing_quality_0087_open_missing_direct", "split": "train", "domain": "manufacturing_quality", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part D has a supplier note.", "query_atom": "has_supplier_note::Part D", "facts_positive": ["Part D passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part D"], "negative_atoms": [], "rules": [], "query_atom": "has_supplier_note::Part D", "closure_atoms": ["passed_visual_check::Part D"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part D passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part D has a supplier note.\nTarget atom: has_supplier_note::Part D\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part D has a supplier note.\nTarget atom: has_supplier_note::Part D"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part D has a supplier note.\nTarget atom: has_supplier_note::Part D"}]}
+{"id": "dynamic_dialogue_v3_0052", "base_id": "manufacturing_quality_0091_closed_missing_with_open_distractor", "split": "train", "domain": "manufacturing_quality", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Part B has release approval.", "query_atom": "has_release_approval::Part B", "facts_positive": ["Part C has a supplier note.", "Part B passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["has_supplier_note::Part C", "passed_visual_check::Part B"], "negative_atoms": [], "rules": [], "query_atom": "has_release_approval::Part B", "closure_atoms": ["has_supplier_note::Part C", "passed_visual_check::Part B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part C has a supplier note.\n- Part B passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part B has release approval.\nTarget atom: has_release_approval::Part B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part B has release approval.\nTarget atom: has_release_approval::Part B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval"], "complete_predicates_after_update": ["has_release_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval\n\nTarget statement: Part B has release approval.\nTarget atom: has_release_approval::Part B"}]}
+{"id": "dynamic_dialogue_v3_0053", "base_id": "manufacturing_quality_0095_open_missing_with_closed_distractor", "split": "train", "domain": "manufacturing_quality", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part F has a supplier note.", "query_atom": "has_supplier_note::Part F", "facts_positive": ["Part A has release approval.", "Part A passed the visual check."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["has_release_approval::Part A", "passed_visual_check::Part A"], "negative_atoms": [], "rules": [], "query_atom": "has_supplier_note::Part F", "closure_atoms": ["has_release_approval::Part A", "passed_visual_check::Part A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part A has release approval.\n- Part A passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Part F has a supplier note.\nTarget atom: has_supplier_note::Part F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part F has a supplier note.\nTarget atom: has_supplier_note::Part F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part F has a supplier note.\nTarget atom: has_supplier_note::Part F"}]}
+{"id": "dynamic_dialogue_v3_0054", "base_id": "manufacturing_quality_0097_closed_derived_missing_antecedent", "split": "train", "domain": "manufacturing_quality", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Part B may ship to customers.", "query_atom": "may_ship::Part B", "facts_positive": ["Part B passed the visual check."], "facts_negative": [], "rules_natural": ["If a part passed the visual check and has release approval, then that part may ship to customers."], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part B"], "negative_atoms": [], "rules": [{"antecedents": ["passed_visual_check::Part B", "has_release_approval::Part B"], "conclusion": "may_ship::Part B", "text": "If a part passed the visual check and has release approval, then that part may ship to customers."}], "query_atom": "may_ship::Part B", "closure_atoms": ["passed_visual_check::Part B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part B passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- If a part passed the visual check and has release approval, then that part may ship to customers.\n\nTarget statement: Part B may ship to customers.\nTarget atom: may_ship::Part B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part B may ship to customers.\nTarget atom: may_ship::Part B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part B may ship to customers.\nTarget atom: may_ship::Part B"}]}
+{"id": "dynamic_dialogue_v3_0056", "base_id": "manufacturing_quality_0100_open_derived_missing_antecedent", "split": "train", "domain": "manufacturing_quality", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part E needs engineer review.", "query_atom": "needs_engineer_review::Part E", "facts_positive": ["Part E passed the visual check."], "facts_negative": [], "rules_natural": ["If a part has a supplier note, then that part needs engineer review."], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part E"], "negative_atoms": [], "rules": [{"antecedents": ["has_supplier_note::Part E"], "conclusion": "needs_engineer_review::Part E", "text": "If a part has a supplier note, then that part needs engineer review."}], "query_atom": "needs_engineer_review::Part E", "closure_atoms": ["passed_visual_check::Part E"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part E passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- If a part has a supplier note, then that part needs engineer review.\n\nTarget statement: Part E needs engineer review.\nTarget atom: needs_engineer_review::Part E\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part E needs engineer review.\nTarget atom: needs_engineer_review::Part E"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part E needs engineer review.\nTarget atom: needs_engineer_review::Part E"}]}
+{"id": "dynamic_dialogue_v3_0058", "base_id": "manufacturing_quality_0102_open_derived_missing_antecedent", "split": "train", "domain": "manufacturing_quality", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part A needs engineer review.", "query_atom": "needs_engineer_review::Part A", "facts_positive": ["Part A passed the visual check."], "facts_negative": [], "rules_natural": ["If a part has a supplier note, then that part needs engineer review."], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part A"], "negative_atoms": [], "rules": [{"antecedents": ["has_supplier_note::Part A"], "conclusion": "needs_engineer_review::Part A", "text": "If a part has a supplier note, then that part needs engineer review."}], "query_atom": "needs_engineer_review::Part A", "closure_atoms": ["passed_visual_check::Part A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part A passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- If a part has a supplier note, then that part needs engineer review.\n\nTarget statement: Part A needs engineer review.\nTarget atom: needs_engineer_review::Part A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part A needs engineer review.\nTarget atom: needs_engineer_review::Part A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part A needs engineer review.\nTarget atom: needs_engineer_review::Part A"}]}
+{"id": "dynamic_dialogue_v3_0059", "base_id": "manufacturing_quality_0103_open_derived_missing_antecedent", "split": "train", "domain": "manufacturing_quality", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Part B needs engineer review.", "query_atom": "needs_engineer_review::Part B", "facts_positive": ["Part B passed the visual check."], "facts_negative": [], "rules_natural": ["If a part has a supplier note, then that part needs engineer review."], "predicate_glossary": {"passed_visual_check": "passed the visual check", "has_release_approval": "has release approval", "has_supplier_note": "has a supplier note", "may_ship": "may ship to customers", "needs_engineer_review": "needs engineer review"}, "vocabulary_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "symbolic": {"positive_atoms": ["passed_visual_check::Part B"], "negative_atoms": [], "rules": [{"antecedents": ["has_supplier_note::Part B"], "conclusion": "needs_engineer_review::Part B", "text": "If a part has a supplier note, then that part needs engineer review."}], "query_atom": "needs_engineer_review::Part B", "closure_atoms": ["passed_visual_check::Part B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_release_approval: has release approval\n- has_supplier_note: has a supplier note\n- may_ship: may ship to customers\n- needs_engineer_review: needs engineer review\n- passed_visual_check: passed the visual check\n\nPositive facts:\n- Part B passed the visual check.\n\nNegative facts:\n- none\n\nRules:\n- If a part has a supplier note, then that part needs engineer review.\n\nTarget statement: Part B needs engineer review.\nTarget atom: needs_engineer_review::Part B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "complete_predicates_after_update": ["has_release_approval", "has_supplier_note", "may_ship", "needs_engineer_review", "passed_visual_check"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n- Complete predicates after this update: has_release_approval, has_supplier_note, may_ship, needs_engineer_review, passed_visual_check\n\nTarget statement: Part B needs engineer review.\nTarget atom: needs_engineer_review::Part B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_release_approval", "may_ship"], "complete_predicates_after_update": ["has_release_approval", "may_ship"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_release_approval, may_ship\n\nTarget statement: Part B needs engineer review.\nTarget atom: needs_engineer_review::Part B"}]}
+{"id": "dynamic_dialogue_v3_0060", "base_id": "procurement_review_0280_closed_missing_direct", "split": "train", "domain": "procurement_review", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Vendor E has vendor approval.", "query_atom": "has_vendor_approval::Vendor E", "facts_positive": ["Vendor E submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor E"], "negative_atoms": [], "rules": [], "query_atom": "has_vendor_approval::Vendor E", "closure_atoms": ["submitted_tax_form::Vendor E"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor E submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor E has vendor approval.\nTarget atom: has_vendor_approval::Vendor E\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor E has vendor approval.\nTarget atom: has_vendor_approval::Vendor E"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval"], "complete_predicates_after_update": ["has_vendor_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval\n\nTarget statement: Vendor E has vendor approval.\nTarget atom: has_vendor_approval::Vendor E"}]}
+{"id": "dynamic_dialogue_v3_0061", "base_id": "procurement_review_0281_closed_missing_direct", "split": "train", "domain": "procurement_review", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Vendor F has vendor approval.", "query_atom": "has_vendor_approval::Vendor F", "facts_positive": ["Vendor F submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor F"], "negative_atoms": [], "rules": [], "query_atom": "has_vendor_approval::Vendor F", "closure_atoms": ["submitted_tax_form::Vendor F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor F submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor F has vendor approval.\nTarget atom: has_vendor_approval::Vendor F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor F has vendor approval.\nTarget atom: has_vendor_approval::Vendor F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval"], "complete_predicates_after_update": ["has_vendor_approval"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval\n\nTarget statement: Vendor F has vendor approval.\nTarget atom: has_vendor_approval::Vendor F"}]}
+{"id": "dynamic_dialogue_v3_0062", "base_id": "procurement_review_0284_open_missing_direct", "split": "train", "domain": "procurement_review", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor C has a risk note.", "query_atom": "has_risk_note::Vendor C", "facts_positive": ["Vendor C submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor C"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor C", "closure_atoms": ["submitted_tax_form::Vendor C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor C submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor C has a risk note.\nTarget atom: has_risk_note::Vendor C\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor C has a risk note.\nTarget atom: has_risk_note::Vendor C"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor C has a risk note.\nTarget atom: has_risk_note::Vendor C"}]}
+{"id": "dynamic_dialogue_v3_0063", "base_id": "procurement_review_0285_open_missing_direct", "split": "train", "domain": "procurement_review", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor D has a risk note.", "query_atom": "has_risk_note::Vendor D", "facts_positive": ["Vendor D submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor D"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor D", "closure_atoms": ["submitted_tax_form::Vendor D"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor D submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor D has a risk note.\nTarget atom: has_risk_note::Vendor D\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor D has a risk note.\nTarget atom: has_risk_note::Vendor D"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor D has a risk note.\nTarget atom: has_risk_note::Vendor D"}]}
+{"id": "dynamic_dialogue_v3_0064", "base_id": "procurement_review_0287_open_missing_direct", "split": "train", "domain": "procurement_review", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor F has a risk note.", "query_atom": "has_risk_note::Vendor F", "facts_positive": ["Vendor F submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor F"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor F", "closure_atoms": ["submitted_tax_form::Vendor F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor F submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F"}]}
+{"id": "dynamic_dialogue_v3_0065", "base_id": "procurement_review_0292_open_missing_with_closed_distractor", "split": "train", "domain": "procurement_review", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor E has a risk note.", "query_atom": "has_risk_note::Vendor E", "facts_positive": ["Vendor F has vendor approval.", "Vendor F submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["has_vendor_approval::Vendor F", "submitted_tax_form::Vendor F"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor E", "closure_atoms": ["has_vendor_approval::Vendor F", "submitted_tax_form::Vendor F"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor F has vendor approval.\n- Vendor F submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor E has a risk note.\nTarget atom: has_risk_note::Vendor E\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor E has a risk note.\nTarget atom: has_risk_note::Vendor E"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor E has a risk note.\nTarget atom: has_risk_note::Vendor E"}]}
+{"id": "dynamic_dialogue_v3_0066", "base_id": "procurement_review_0293_open_missing_with_closed_distractor", "split": "train", "domain": "procurement_review", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor F has a risk note.", "query_atom": "has_risk_note::Vendor F", "facts_positive": ["Vendor A has vendor approval.", "Vendor A submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["has_vendor_approval::Vendor A", "submitted_tax_form::Vendor A"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor F", "closure_atoms": ["has_vendor_approval::Vendor A", "submitted_tax_form::Vendor A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor A has vendor approval.\n- Vendor A submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor F has a risk note.\nTarget atom: has_risk_note::Vendor F"}]}
+{"id": "dynamic_dialogue_v3_0067", "base_id": "procurement_review_0294_open_missing_with_closed_distractor", "split": "train", "domain": "procurement_review", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor A has a risk note.", "query_atom": "has_risk_note::Vendor A", "facts_positive": ["Vendor B has vendor approval.", "Vendor B submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["has_vendor_approval::Vendor B", "submitted_tax_form::Vendor B"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor A", "closure_atoms": ["has_vendor_approval::Vendor B", "submitted_tax_form::Vendor B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor B has vendor approval.\n- Vendor B submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor A has a risk note.\nTarget atom: has_risk_note::Vendor A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor A has a risk note.\nTarget atom: has_risk_note::Vendor A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor A has a risk note.\nTarget atom: has_risk_note::Vendor A"}]}
+{"id": "dynamic_dialogue_v3_0068", "base_id": "procurement_review_0295_open_missing_with_closed_distractor", "split": "train", "domain": "procurement_review", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor B has a risk note.", "query_atom": "has_risk_note::Vendor B", "facts_positive": ["Vendor C has vendor approval.", "Vendor C submitted a tax form."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["has_vendor_approval::Vendor C", "submitted_tax_form::Vendor C"], "negative_atoms": [], "rules": [], "query_atom": "has_risk_note::Vendor B", "closure_atoms": ["has_vendor_approval::Vendor C", "submitted_tax_form::Vendor C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor C has vendor approval.\n- Vendor C submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Vendor B has a risk note.\nTarget atom: has_risk_note::Vendor B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor B has a risk note.\nTarget atom: has_risk_note::Vendor B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor B has a risk note.\nTarget atom: has_risk_note::Vendor B"}]}
+{"id": "dynamic_dialogue_v3_0069", "base_id": "procurement_review_0300_open_derived_missing_antecedent", "split": "train", "domain": "procurement_review", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor A needs procurement review.", "query_atom": "needs_procurement_review::Vendor A", "facts_positive": ["Vendor A submitted a tax form."], "facts_negative": [], "rules_natural": ["If a vendor has a risk note, then that vendor needs procurement review."], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor A"], "negative_atoms": [], "rules": [{"antecedents": ["has_risk_note::Vendor A"], "conclusion": "needs_procurement_review::Vendor A", "text": "If a vendor has a risk note, then that vendor needs procurement review."}], "query_atom": "needs_procurement_review::Vendor A", "closure_atoms": ["submitted_tax_form::Vendor A"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor A submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- If a vendor has a risk note, then that vendor needs procurement review.\n\nTarget statement: Vendor A needs procurement review.\nTarget atom: needs_procurement_review::Vendor A\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor A needs procurement review.\nTarget atom: needs_procurement_review::Vendor A"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor A needs procurement review.\nTarget atom: needs_procurement_review::Vendor A"}]}
+{"id": "dynamic_dialogue_v3_0070", "base_id": "procurement_review_0301_open_derived_missing_antecedent", "split": "train", "domain": "procurement_review", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor B needs procurement review.", "query_atom": "needs_procurement_review::Vendor B", "facts_positive": ["Vendor B submitted a tax form."], "facts_negative": [], "rules_natural": ["If a vendor has a risk note, then that vendor needs procurement review."], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor B"], "negative_atoms": [], "rules": [{"antecedents": ["has_risk_note::Vendor B"], "conclusion": "needs_procurement_review::Vendor B", "text": "If a vendor has a risk note, then that vendor needs procurement review."}], "query_atom": "needs_procurement_review::Vendor B", "closure_atoms": ["submitted_tax_form::Vendor B"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor B submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- If a vendor has a risk note, then that vendor needs procurement review.\n\nTarget statement: Vendor B needs procurement review.\nTarget atom: needs_procurement_review::Vendor B\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor B needs procurement review.\nTarget atom: needs_procurement_review::Vendor B"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor B needs procurement review.\nTarget atom: needs_procurement_review::Vendor B"}]}
+{"id": "dynamic_dialogue_v3_0071", "base_id": "procurement_review_0302_open_derived_missing_antecedent", "split": "train", "domain": "procurement_review", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Vendor C needs procurement review.", "query_atom": "needs_procurement_review::Vendor C", "facts_positive": ["Vendor C submitted a tax form."], "facts_negative": [], "rules_natural": ["If a vendor has a risk note, then that vendor needs procurement review."], "predicate_glossary": {"submitted_tax_form": "submitted a tax form", "has_vendor_approval": "has vendor approval", "has_risk_note": "has a risk note", "may_receive_purchase_order": "may receive a purchase order", "needs_procurement_review": "needs procurement review"}, "vocabulary_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "symbolic": {"positive_atoms": ["submitted_tax_form::Vendor C"], "negative_atoms": [], "rules": [{"antecedents": ["has_risk_note::Vendor C"], "conclusion": "needs_procurement_review::Vendor C", "text": "If a vendor has a risk note, then that vendor needs procurement review."}], "query_atom": "needs_procurement_review::Vendor C", "closure_atoms": ["submitted_tax_form::Vendor C"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_risk_note: has a risk note\n- has_vendor_approval: has vendor approval\n- may_receive_purchase_order: may receive a purchase order\n- needs_procurement_review: needs procurement review\n- submitted_tax_form: submitted a tax form\n\nPositive facts:\n- Vendor C submitted a tax form.\n\nNegative facts:\n- none\n\nRules:\n- If a vendor has a risk note, then that vendor needs procurement review.\n\nTarget statement: Vendor C needs procurement review.\nTarget atom: needs_procurement_review::Vendor C\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "complete_predicates_after_update": ["has_risk_note", "has_vendor_approval", "may_receive_purchase_order", "needs_procurement_review", "submitted_tax_form"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n- Complete predicates after this update: has_risk_note, has_vendor_approval, may_receive_purchase_order, needs_procurement_review, submitted_tax_form\n\nTarget statement: Vendor C needs procurement review.\nTarget atom: needs_procurement_review::Vendor C"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_vendor_approval", "may_receive_purchase_order"], "complete_predicates_after_update": ["has_vendor_approval", "may_receive_purchase_order"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_vendor_approval, may_receive_purchase_order\n\nTarget statement: Vendor C needs procurement review.\nTarget atom: needs_procurement_review::Vendor C"}]}
+{"id": "dynamic_dialogue_v3_0072", "base_id": "robotics_operations_0160_closed_missing_direct", "split": "train", "domain": "robotics_operations", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 5 has shift clearance.", "query_atom": "has_shift_clearance::Rover 5", "facts_positive": ["Rover 5 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 5"], "negative_atoms": [], "rules": [], "query_atom": "has_shift_clearance::Rover 5", "closure_atoms": ["passed_diagnostics::Rover 5"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 5 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 5 has shift clearance.\nTarget atom: has_shift_clearance::Rover 5\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 5 has shift clearance.\nTarget atom: has_shift_clearance::Rover 5"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance"], "complete_predicates_after_update": ["has_shift_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance\n\nTarget statement: Rover 5 has shift clearance.\nTarget atom: has_shift_clearance::Rover 5"}]}
+{"id": "dynamic_dialogue_v3_0073", "base_id": "robotics_operations_0162_closed_missing_direct", "split": "train", "domain": "robotics_operations", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 1 has shift clearance.", "query_atom": "has_shift_clearance::Rover 1", "facts_positive": ["Rover 1 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 1"], "negative_atoms": [], "rules": [], "query_atom": "has_shift_clearance::Rover 1", "closure_atoms": ["passed_diagnostics::Rover 1"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 1 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance"], "complete_predicates_after_update": ["has_shift_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1"}]}
+{"id": "dynamic_dialogue_v3_0074", "base_id": "robotics_operations_0164_open_missing_direct", "split": "train", "domain": "robotics_operations", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 3 has a field note.", "query_atom": "has_field_note::Rover 3", "facts_positive": ["Rover 3 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 3"], "negative_atoms": [], "rules": [], "query_atom": "has_field_note::Rover 3", "closure_atoms": ["passed_diagnostics::Rover 3"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 3 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 3 has a field note.\nTarget atom: has_field_note::Rover 3\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 3 has a field note.\nTarget atom: has_field_note::Rover 3"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 3 has a field note.\nTarget atom: has_field_note::Rover 3"}]}
+{"id": "dynamic_dialogue_v3_0075", "base_id": "robotics_operations_0167_open_missing_direct", "split": "train", "domain": "robotics_operations", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 6 has a field note.", "query_atom": "has_field_note::Rover 6", "facts_positive": ["Rover 6 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 6"], "negative_atoms": [], "rules": [], "query_atom": "has_field_note::Rover 6", "closure_atoms": ["passed_diagnostics::Rover 6"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 6 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 6 has a field note.\nTarget atom: has_field_note::Rover 6\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 6 has a field note.\nTarget atom: has_field_note::Rover 6"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 6 has a field note.\nTarget atom: has_field_note::Rover 6"}]}
+{"id": "dynamic_dialogue_v3_0076", "base_id": "robotics_operations_0168_closed_missing_with_open_distractor", "split": "train", "domain": "robotics_operations", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 1 has shift clearance.", "query_atom": "has_shift_clearance::Rover 1", "facts_positive": ["Rover 2 has a field note.", "Rover 1 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["has_field_note::Rover 2", "passed_diagnostics::Rover 1"], "negative_atoms": [], "rules": [], "query_atom": "has_shift_clearance::Rover 1", "closure_atoms": ["has_field_note::Rover 2", "passed_diagnostics::Rover 1"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 2 has a field note.\n- Rover 1 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance"], "complete_predicates_after_update": ["has_shift_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance\n\nTarget statement: Rover 1 has shift clearance.\nTarget atom: has_shift_clearance::Rover 1"}]}
+{"id": "dynamic_dialogue_v3_0078", "base_id": "robotics_operations_0171_closed_missing_with_open_distractor", "split": "train", "domain": "robotics_operations", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 4 has shift clearance.", "query_atom": "has_shift_clearance::Rover 4", "facts_positive": ["Rover 5 has a field note.", "Rover 4 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["has_field_note::Rover 5", "passed_diagnostics::Rover 4"], "negative_atoms": [], "rules": [], "query_atom": "has_shift_clearance::Rover 4", "closure_atoms": ["has_field_note::Rover 5", "passed_diagnostics::Rover 4"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 5 has a field note.\n- Rover 4 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 4 has shift clearance.\nTarget atom: has_shift_clearance::Rover 4\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 4 has shift clearance.\nTarget atom: has_shift_clearance::Rover 4"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance"], "complete_predicates_after_update": ["has_shift_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance\n\nTarget statement: Rover 4 has shift clearance.\nTarget atom: has_shift_clearance::Rover 4"}]}
+{"id": "dynamic_dialogue_v3_0079", "base_id": "robotics_operations_0172_open_missing_with_closed_distractor", "split": "train", "domain": "robotics_operations", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 5 has a field note.", "query_atom": "has_field_note::Rover 5", "facts_positive": ["Rover 6 has shift clearance.", "Rover 6 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["has_shift_clearance::Rover 6", "passed_diagnostics::Rover 6"], "negative_atoms": [], "rules": [], "query_atom": "has_field_note::Rover 5", "closure_atoms": ["has_shift_clearance::Rover 6", "passed_diagnostics::Rover 6"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 6 has shift clearance.\n- Rover 6 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 5 has a field note.\nTarget atom: has_field_note::Rover 5\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 5 has a field note.\nTarget atom: has_field_note::Rover 5"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 5 has a field note.\nTarget atom: has_field_note::Rover 5"}]}
+{"id": "dynamic_dialogue_v3_0080", "base_id": "robotics_operations_0174_open_missing_with_closed_distractor", "split": "train", "domain": "robotics_operations", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 1 has a field note.", "query_atom": "has_field_note::Rover 1", "facts_positive": ["Rover 2 has shift clearance.", "Rover 2 passed diagnostics."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["has_shift_clearance::Rover 2", "passed_diagnostics::Rover 2"], "negative_atoms": [], "rules": [], "query_atom": "has_field_note::Rover 1", "closure_atoms": ["has_shift_clearance::Rover 2", "passed_diagnostics::Rover 2"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 2 has shift clearance.\n- Rover 2 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 1 has a field note.\nTarget atom: has_field_note::Rover 1\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 1 has a field note.\nTarget atom: has_field_note::Rover 1"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 1 has a field note.\nTarget atom: has_field_note::Rover 1"}]}
+{"id": "dynamic_dialogue_v3_0081", "base_id": "robotics_operations_0176_closed_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 3 may start its shift.", "query_atom": "may_start_shift::Rover 3", "facts_positive": ["Rover 3 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot passed diagnostics and has shift clearance, then that robot may start its shift."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 3"], "negative_atoms": [], "rules": [{"antecedents": ["passed_diagnostics::Rover 3", "has_shift_clearance::Rover 3"], "conclusion": "may_start_shift::Rover 3", "text": "If a robot passed diagnostics and has shift clearance, then that robot may start its shift."}], "query_atom": "may_start_shift::Rover 3", "closure_atoms": ["passed_diagnostics::Rover 3"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 3 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot passed diagnostics and has shift clearance, then that robot may start its shift.\n\nTarget statement: Rover 3 may start its shift.\nTarget atom: may_start_shift::Rover 3\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 3 may start its shift.\nTarget atom: may_start_shift::Rover 3"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 3 may start its shift.\nTarget atom: may_start_shift::Rover 3"}]}
+{"id": "dynamic_dialogue_v3_0082", "base_id": "robotics_operations_0178_closed_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 5 may start its shift.", "query_atom": "may_start_shift::Rover 5", "facts_positive": ["Rover 5 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot passed diagnostics and has shift clearance, then that robot may start its shift."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 5"], "negative_atoms": [], "rules": [{"antecedents": ["passed_diagnostics::Rover 5", "has_shift_clearance::Rover 5"], "conclusion": "may_start_shift::Rover 5", "text": "If a robot passed diagnostics and has shift clearance, then that robot may start its shift."}], "query_atom": "may_start_shift::Rover 5", "closure_atoms": ["passed_diagnostics::Rover 5"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 5 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot passed diagnostics and has shift clearance, then that robot may start its shift.\n\nTarget statement: Rover 5 may start its shift.\nTarget atom: may_start_shift::Rover 5\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 5 may start its shift.\nTarget atom: may_start_shift::Rover 5"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 5 may start its shift.\nTarget atom: may_start_shift::Rover 5"}]}
+{"id": "dynamic_dialogue_v3_0083", "base_id": "robotics_operations_0179_closed_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Rover 6 may start its shift.", "query_atom": "may_start_shift::Rover 6", "facts_positive": ["Rover 6 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot passed diagnostics and has shift clearance, then that robot may start its shift."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 6"], "negative_atoms": [], "rules": [{"antecedents": ["passed_diagnostics::Rover 6", "has_shift_clearance::Rover 6"], "conclusion": "may_start_shift::Rover 6", "text": "If a robot passed diagnostics and has shift clearance, then that robot may start its shift."}], "query_atom": "may_start_shift::Rover 6", "closure_atoms": ["passed_diagnostics::Rover 6"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 6 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot passed diagnostics and has shift clearance, then that robot may start its shift.\n\nTarget statement: Rover 6 may start its shift.\nTarget atom: may_start_shift::Rover 6\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 6 may start its shift.\nTarget atom: may_start_shift::Rover 6"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 6 may start its shift.\nTarget atom: may_start_shift::Rover 6"}]}
+{"id": "dynamic_dialogue_v3_0084", "base_id": "robotics_operations_0180_open_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 1 needs operator review.", "query_atom": "needs_operator_review::Rover 1", "facts_positive": ["Rover 1 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot has a field note, then that robot needs operator review."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 1"], "negative_atoms": [], "rules": [{"antecedents": ["has_field_note::Rover 1"], "conclusion": "needs_operator_review::Rover 1", "text": "If a robot has a field note, then that robot needs operator review."}], "query_atom": "needs_operator_review::Rover 1", "closure_atoms": ["passed_diagnostics::Rover 1"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 1 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot has a field note, then that robot needs operator review.\n\nTarget statement: Rover 1 needs operator review.\nTarget atom: needs_operator_review::Rover 1\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 1 needs operator review.\nTarget atom: needs_operator_review::Rover 1"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 1 needs operator review.\nTarget atom: needs_operator_review::Rover 1"}]}
+{"id": "dynamic_dialogue_v3_0085", "base_id": "robotics_operations_0181_open_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 2 needs operator review.", "query_atom": "needs_operator_review::Rover 2", "facts_positive": ["Rover 2 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot has a field note, then that robot needs operator review."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 2"], "negative_atoms": [], "rules": [{"antecedents": ["has_field_note::Rover 2"], "conclusion": "needs_operator_review::Rover 2", "text": "If a robot has a field note, then that robot needs operator review."}], "query_atom": "needs_operator_review::Rover 2", "closure_atoms": ["passed_diagnostics::Rover 2"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 2 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot has a field note, then that robot needs operator review.\n\nTarget statement: Rover 2 needs operator review.\nTarget atom: needs_operator_review::Rover 2\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 2 needs operator review.\nTarget atom: needs_operator_review::Rover 2"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 2 needs operator review.\nTarget atom: needs_operator_review::Rover 2"}]}
+{"id": "dynamic_dialogue_v3_0086", "base_id": "robotics_operations_0182_open_derived_missing_antecedent", "split": "train", "domain": "robotics_operations", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Rover 3 needs operator review.", "query_atom": "needs_operator_review::Rover 3", "facts_positive": ["Rover 3 passed diagnostics."], "facts_negative": [], "rules_natural": ["If a robot has a field note, then that robot needs operator review."], "predicate_glossary": {"passed_diagnostics": "passed diagnostics", "has_shift_clearance": "has shift clearance", "has_field_note": "has a field note", "may_start_shift": "may start its shift", "needs_operator_review": "needs operator review"}, "vocabulary_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "symbolic": {"positive_atoms": ["passed_diagnostics::Rover 3"], "negative_atoms": [], "rules": [{"antecedents": ["has_field_note::Rover 3"], "conclusion": "needs_operator_review::Rover 3", "text": "If a robot has a field note, then that robot needs operator review."}], "query_atom": "needs_operator_review::Rover 3", "closure_atoms": ["passed_diagnostics::Rover 3"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_field_note: has a field note\n- has_shift_clearance: has shift clearance\n- may_start_shift: may start its shift\n- needs_operator_review: needs operator review\n- passed_diagnostics: passed diagnostics\n\nPositive facts:\n- Rover 3 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- If a robot has a field note, then that robot needs operator review.\n\nTarget statement: Rover 3 needs operator review.\nTarget atom: needs_operator_review::Rover 3\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "complete_predicates_after_update": ["has_field_note", "has_shift_clearance", "may_start_shift", "needs_operator_review", "passed_diagnostics"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n- Complete predicates after this update: has_field_note, has_shift_clearance, may_start_shift, needs_operator_review, passed_diagnostics\n\nTarget statement: Rover 3 needs operator review.\nTarget atom: needs_operator_review::Rover 3"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_shift_clearance", "may_start_shift"], "complete_predicates_after_update": ["has_shift_clearance", "may_start_shift"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_shift_clearance, may_start_shift\n\nTarget statement: Rover 3 needs operator review.\nTarget atom: needs_operator_review::Rover 3"}]}
+{"id": "dynamic_dialogue_v3_0087", "base_id": "university_registration_0040_closed_missing_direct", "split": "train", "domain": "university_registration", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Iris has advising clearance.", "query_atom": "has_advising_clearance::Iris", "facts_positive": ["Iris passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Iris"], "negative_atoms": [], "rules": [], "query_atom": "has_advising_clearance::Iris", "closure_atoms": ["passed_exam::Iris"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Iris passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Iris has advising clearance.\nTarget atom: has_advising_clearance::Iris\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Iris has advising clearance.\nTarget atom: has_advising_clearance::Iris"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance"], "complete_predicates_after_update": ["has_advising_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance\n\nTarget statement: Iris has advising clearance.\nTarget atom: has_advising_clearance::Iris"}]}
+{"id": "dynamic_dialogue_v3_0088", "base_id": "university_registration_0041_closed_missing_direct", "split": "train", "domain": "university_registration", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Theo has advising clearance.", "query_atom": "has_advising_clearance::Theo", "facts_positive": ["Theo passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Theo"], "negative_atoms": [], "rules": [], "query_atom": "has_advising_clearance::Theo", "closure_atoms": ["passed_exam::Theo"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Theo passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Theo has advising clearance.\nTarget atom: has_advising_clearance::Theo\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Theo has advising clearance.\nTarget atom: has_advising_clearance::Theo"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance"], "complete_predicates_after_update": ["has_advising_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance\n\nTarget statement: Theo has advising clearance.\nTarget atom: has_advising_clearance::Theo"}]}
+{"id": "dynamic_dialogue_v3_0089", "base_id": "university_registration_0043_closed_missing_direct", "split": "train", "domain": "university_registration", "family": "closed_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Noah has advising clearance.", "query_atom": "has_advising_clearance::Noah", "facts_positive": ["Noah passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Noah"], "negative_atoms": [], "rules": [], "query_atom": "has_advising_clearance::Noah", "closure_atoms": ["passed_exam::Noah"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Noah passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance"], "complete_predicates_after_update": ["has_advising_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah"}]}
+{"id": "dynamic_dialogue_v3_0091", "base_id": "university_registration_0046_open_missing_direct", "split": "train", "domain": "university_registration", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Iris has an external scholarship.", "query_atom": "has_external_scholarship::Iris", "facts_positive": ["Iris passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Iris"], "negative_atoms": [], "rules": [], "query_atom": "has_external_scholarship::Iris", "closure_atoms": ["passed_exam::Iris"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Iris passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Iris has an external scholarship.\nTarget atom: has_external_scholarship::Iris\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Iris has an external scholarship.\nTarget atom: has_external_scholarship::Iris"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "may_register"], "complete_predicates_after_update": ["has_advising_clearance", "may_register"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance, may_register\n\nTarget statement: Iris has an external scholarship.\nTarget atom: has_external_scholarship::Iris"}]}
+{"id": "dynamic_dialogue_v3_0092", "base_id": "university_registration_0047_open_missing_direct", "split": "train", "domain": "university_registration", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Theo has an external scholarship.", "query_atom": "has_external_scholarship::Theo", "facts_positive": ["Theo passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Theo"], "negative_atoms": [], "rules": [], "query_atom": "has_external_scholarship::Theo", "closure_atoms": ["passed_exam::Theo"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Theo passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Theo has an external scholarship.\nTarget atom: has_external_scholarship::Theo\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Theo has an external scholarship.\nTarget atom: has_external_scholarship::Theo"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "may_register"], "complete_predicates_after_update": ["has_advising_clearance", "may_register"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance, may_register\n\nTarget statement: Theo has an external scholarship.\nTarget atom: has_external_scholarship::Theo"}]}
+{"id": "dynamic_dialogue_v3_0094", "base_id": "university_registration_0049_closed_missing_with_open_distractor", "split": "train", "domain": "university_registration", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Noah has advising clearance.", "query_atom": "has_advising_clearance::Noah", "facts_positive": ["Lena has an external scholarship.", "Noah passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["has_external_scholarship::Lena", "passed_exam::Noah"], "negative_atoms": [], "rules": [], "query_atom": "has_advising_clearance::Noah", "closure_atoms": ["has_external_scholarship::Lena", "passed_exam::Noah"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Lena has an external scholarship.\n- Noah passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance"], "complete_predicates_after_update": ["has_advising_clearance"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance\n\nTarget statement: Noah has advising clearance.\nTarget atom: has_advising_clearance::Noah"}]}
+{"id": "dynamic_dialogue_v3_0096", "base_id": "university_registration_0054_open_missing_with_closed_distractor", "split": "train", "domain": "university_registration", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Mia has an external scholarship.", "query_atom": "has_external_scholarship::Mia", "facts_positive": ["Noah has advising clearance.", "Noah passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["has_advising_clearance::Noah", "passed_exam::Noah"], "negative_atoms": [], "rules": [], "query_atom": "has_external_scholarship::Mia", "closure_atoms": ["has_advising_clearance::Noah", "passed_exam::Noah"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Noah has advising clearance.\n- Noah passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Mia has an external scholarship.\nTarget atom: has_external_scholarship::Mia\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Mia has an external scholarship.\nTarget atom: has_external_scholarship::Mia"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "may_register"], "complete_predicates_after_update": ["has_advising_clearance", "may_register"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance, may_register\n\nTarget statement: Mia has an external scholarship.\nTarget atom: has_external_scholarship::Mia"}]}
+{"id": "dynamic_dialogue_v3_0097", "base_id": "university_registration_0055_open_missing_with_closed_distractor", "split": "train", "domain": "university_registration", "family": "open_missing_with_closed_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Noah has an external scholarship.", "query_atom": "has_external_scholarship::Noah", "facts_positive": ["Lena has advising clearance.", "Lena passed the qualifying exam."], "facts_negative": [], "rules_natural": [], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["has_advising_clearance::Lena", "passed_exam::Lena"], "negative_atoms": [], "rules": [], "query_atom": "has_external_scholarship::Noah", "closure_atoms": ["has_advising_clearance::Lena", "passed_exam::Lena"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Lena has advising clearance.\n- Lena passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Noah has an external scholarship.\nTarget atom: has_external_scholarship::Noah\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Noah has an external scholarship.\nTarget atom: has_external_scholarship::Noah"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "may_register"], "complete_predicates_after_update": ["has_advising_clearance", "may_register"], "gold_answer": "unknown", "expected_changed_from_previous": true, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance, may_register\n\nTarget statement: Noah has an external scholarship.\nTarget atom: has_external_scholarship::Noah"}]}
+{"id": "dynamic_dialogue_v3_0099", "base_id": "university_registration_0059_closed_derived_missing_antecedent", "split": "train", "domain": "university_registration", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Theo may register for the seminar.", "query_atom": "may_register::Theo", "facts_positive": ["Theo passed the qualifying exam."], "facts_negative": [], "rules_natural": ["If a student passed the qualifying exam and has advising clearance, then that student may register for the seminar."], "predicate_glossary": {"passed_exam": "passed the qualifying exam", "has_advising_clearance": "has advising clearance", "has_external_scholarship": "has an external scholarship", "may_register": "may register for the seminar", "needs_manual_audit": "needs a manual audit"}, "vocabulary_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "symbolic": {"positive_atoms": ["passed_exam::Theo"], "negative_atoms": [], "rules": [{"antecedents": ["passed_exam::Theo", "has_advising_clearance::Theo"], "conclusion": "may_register::Theo", "text": "If a student passed the qualifying exam and has advising clearance, then that student may register for the seminar."}], "query_atom": "may_register::Theo", "closure_atoms": ["passed_exam::Theo"]}, "turns": [{"turn_index": 1, "source_semantics": "owa", "update_operation": "SET_COMPLETE_PREDICATES", "update_predicates": [], "complete_predicates_after_update": [], "gold_answer": "unknown", "expected_changed_from_previous": null, "expected_applied_update": "open", "prompt": "This is turn 1 of a 3-turn dynamic completeness dialogue.\nYou are given an initial knowledge base and an initial completeness state.\nDo not use outside knowledge.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly open. For turn 1, changed_from_previous must be null.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nKnowledge base:\n\nPredicate glossary:\n- has_advising_clearance: has advising clearance\n- has_external_scholarship: has an external scholarship\n- may_register: may register for the seminar\n- needs_manual_audit: needs a manual audit\n- passed_exam: passed the qualifying exam\n\nPositive facts:\n- Theo passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- If a student passed the qualifying exam and has advising clearance, then that student may register for the seminar.\n\nTarget statement: Theo may register for the seminar.\nTarget atom: may_register::Theo\n\nCompleteness-state update for this turn:\n- Operation: SET_COMPLETE_PREDICATES\n- New complete predicates: none"}, {"turn_index": 2, "source_semantics": "cwa", "update_operation": "ADD_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "complete_predicates_after_update": ["has_advising_clearance", "has_external_scholarship", "may_register", "needs_manual_audit", "passed_exam"], "gold_answer": "false", "expected_changed_from_previous": true, "expected_applied_update": "global_complete", "prompt": "This is turn 2 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly global_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: ADD_COMPLETE_PREDICATES\n- Predicates to add as complete: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n- Complete predicates after this update: has_advising_clearance, has_external_scholarship, may_register, needs_manual_audit, passed_exam\n\nTarget statement: Theo may register for the seminar.\nTarget atom: may_register::Theo"}, {"turn_index": 3, "source_semantics": "lcwa", "update_operation": "REPLACE_COMPLETE_PREDICATES", "update_predicates": ["has_advising_clearance", "may_register"], "complete_predicates_after_update": ["has_advising_clearance", "may_register"], "gold_answer": "false", "expected_changed_from_previous": false, "expected_applied_update": "local_complete", "prompt": "This is turn 3 of a 3-turn dynamic completeness dialogue.\nKeep the exact same knowledge base, facts, rules, glossary, and target from turn 1.\nApply only the completeness-state update below.\nRecompute the answer from the updated state. Do not treat a previous false/unknown conclusion as a new fact.\nReturn exactly one compact JSON object with keys answer, changed_from_previous, applied_update, and rationale. The answer value must be one of true, false, unknown. The changed_from_previous value must be true, false, or null. The applied_update value must be one of open, global_complete, local_complete. For this turn, applied_update must be exactly local_complete. For this turn, changed_from_previous must be true iff your current answer differs from your immediately previous answer.\n\nReasoning contract:\n- Positive facts are true.\n- Negative facts make the corresponding target atom false.\n- A rule derives its conclusion only when every antecedent is true.\n- First apply all rules until no new facts can be derived.\n- Then evaluate unstated and underivable atoms using the current completeness state.\n- If a predicate is complete, an unstated and underivable atom using that predicate is false.\n- If a predicate is not complete, an unstated and underivable atom using that predicate is unknown.\n- A false answer derived from completeness is not a permanent negative fact; it can be withdrawn if the completeness state changes.\n\nCompleteness-state update for this turn:\n- Operation: REPLACE_COMPLETE_PREDICATES\n- Discard the previous complete-predicate set.\n- Replacement complete predicates: has_advising_clearance, may_register\n\nTarget statement: Theo may register for the seminar.\nTarget atom: may_register::Theo"}]}