data/dynamic_dialogue/validation.jsonl

{"id": "dynamic_dialogue_v3_0012", "base_id": "finance_controls_0130_closed_missing_with_open_distractor", "split": "dev", "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 59 has compliance clearance.", "query_atom": "has_compliance_clearance::Account 59", "facts_positive": ["Account 61 has a manual exception.", "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_manual_exception::Account 61", "passed_kyc::Account 59"], "negative_atoms": [], "rules": [], "query_atom": "has_compliance_clearance::Account 59", "closure_atoms": ["has_manual_exception::Account 61", "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 61 has a manual exception.\n- Account 59 passed KYC checks.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Account 59 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 59\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 59 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 59"}, {"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 59 has compliance clearance.\nTarget atom: has_compliance_clearance::Account 59"}]}
{"id": "dynamic_dialogue_v3_0018", "base_id": "finance_controls_0138_closed_derived_missing_antecedent", "split": "dev", "domain": "finance_controls", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Account 12 may receive a wire transfer.", "query_atom": "may_receive_wire::Account 12", "facts_positive": ["Account 12 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 12"], "negative_atoms": [], "rules": [{"antecedents": ["passed_kyc::Account 12", "has_compliance_clearance::Account 12"], "conclusion": "may_receive_wire::Account 12", "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 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- If an account passed KYC checks and has compliance clearance, then that account may receive a wire transfer.\n\nTarget statement: Account 12 may receive a wire transfer.\nTarget atom: may_receive_wire::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 may receive a wire transfer.\nTarget atom: may_receive_wire::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": "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 12 may receive a wire transfer.\nTarget atom: may_receive_wire::Account 12"}]}
{"id": "dynamic_dialogue_v3_0022", "base_id": "finance_controls_0142_open_derived_missing_antecedent", "split": "dev", "domain": "finance_controls", "family": "open_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Account 59 needs compliance review.", "query_atom": "needs_compliance_review::Account 59", "facts_positive": ["Account 59 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 59"], "negative_atoms": [], "rules": [{"antecedents": ["has_manual_exception::Account 59"], "conclusion": "needs_compliance_review::Account 59", "text": "If an account has a manual exception, then that account needs compliance review."}], "query_atom": "needs_compliance_review::Account 59", "closure_atoms": ["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 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 59 needs compliance review.\nTarget atom: needs_compliance_review::Account 59\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 59 needs compliance review.\nTarget atom: needs_compliance_review::Account 59"}, {"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 59 needs compliance review.\nTarget atom: needs_compliance_review::Account 59"}]}
{"id": "dynamic_dialogue_v3_0024", "base_id": "hospital_access_0004_open_missing_direct", "split": "dev", "domain": "hospital_access", "family": "open_missing_direct", "subset": "core_contrastive", "gold_pattern": "unknown|false|unknown", "dialogue_type": "reopen", "target_statement": "Elena is assigned to the clinical trial.", "query_atom": "assigned_to_trial::Elena", "facts_positive": ["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": ["completed_training::Elena"], "negative_atoms": [], "rules": [], "query_atom": "assigned_to_trial::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- none\n\nTarget statement: Elena is assigned to the clinical trial.\nTarget atom: assigned_to_trial::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 is assigned to the clinical trial.\nTarget atom: assigned_to_trial::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 is assigned to the clinical trial.\nTarget atom: assigned_to_trial::Elena"}]}
{"id": "dynamic_dialogue_v3_0031", "base_id": "hospital_access_0017_closed_derived_missing_antecedent", "split": "dev", "domain": "hospital_access", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Farid may enter Lab A.", "query_atom": "may_enter_lab::Farid", "facts_positive": ["Farid 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::Farid"], "negative_atoms": [], "rules": [{"antecedents": ["completed_training::Farid", "has_clearance::Farid"], "conclusion": "may_enter_lab::Farid", "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::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 has security clearance and has completed safety training, then that staff member may enter Lab A.\n\nTarget statement: Farid may enter Lab A.\nTarget atom: may_enter_lab::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 may enter Lab A.\nTarget atom: may_enter_lab::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": "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: Farid may enter Lab A.\nTarget atom: may_enter_lab::Farid"}]}
{"id": "dynamic_dialogue_v3_0042", "base_id": "library_services_0209_closed_missing_with_open_distractor", "split": "dev", "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 F has borrowing clearance.", "query_atom": "has_borrowing_clearance::Reader F", "facts_positive": ["Reader F has an active membership.", "Reader A 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 F", "has_special_request::Reader A"], "negative_atoms": [], "rules": [], "query_atom": "has_borrowing_clearance::Reader F", "closure_atoms": ["has_active_membership::Reader F", "has_special_request::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 F has an active membership.\n- Reader A has a special request.\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_0055", "base_id": "manufacturing_quality_0099_closed_derived_missing_antecedent", "split": "dev", "domain": "manufacturing_quality", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Part D may ship to customers.", "query_atom": "may_ship::Part D", "facts_positive": ["Part D 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 D"], "negative_atoms": [], "rules": [{"antecedents": ["passed_visual_check::Part D", "has_release_approval::Part D"], "conclusion": "may_ship::Part D", "text": "If a part passed the visual check and has release approval, then that part may ship to customers."}], "query_atom": "may_ship::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- If a part passed the visual check and has release approval, then that part may ship to customers.\n\nTarget statement: Part D may ship to customers.\nTarget atom: may_ship::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 may ship to customers.\nTarget atom: may_ship::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": "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 D may ship to customers.\nTarget atom: may_ship::Part D"}]}
{"id": "dynamic_dialogue_v3_0077", "base_id": "robotics_operations_0169_closed_missing_with_open_distractor", "split": "dev", "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 2 has shift clearance.", "query_atom": "has_shift_clearance::Rover 2", "facts_positive": ["Rover 3 has a field note.", "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_field_note::Rover 3", "passed_diagnostics::Rover 2"], "negative_atoms": [], "rules": [], "query_atom": "has_shift_clearance::Rover 2", "closure_atoms": ["has_field_note::Rover 3", "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 3 has a field note.\n- Rover 2 passed diagnostics.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Rover 2 has shift clearance.\nTarget atom: has_shift_clearance::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 has shift clearance.\nTarget atom: has_shift_clearance::Rover 2"}, {"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 2 has shift clearance.\nTarget atom: has_shift_clearance::Rover 2"}]}
{"id": "dynamic_dialogue_v3_0093", "base_id": "university_registration_0048_closed_missing_with_open_distractor", "split": "dev", "domain": "university_registration", "family": "closed_missing_with_open_distractor", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Mia has advising clearance.", "query_atom": "has_advising_clearance::Mia", "facts_positive": ["Noah has an external scholarship.", "Mia 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::Noah", "passed_exam::Mia"], "negative_atoms": [], "rules": [], "query_atom": "has_advising_clearance::Mia", "closure_atoms": ["has_external_scholarship::Noah", "passed_exam::Mia"]}, "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 an external scholarship.\n- Mia passed the qualifying exam.\n\nNegative facts:\n- none\n\nRules:\n- none\n\nTarget statement: Mia has advising clearance.\nTarget atom: has_advising_clearance::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 advising clearance.\nTarget atom: has_advising_clearance::Mia"}, {"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: Mia has advising clearance.\nTarget atom: has_advising_clearance::Mia"}]}
{"id": "dynamic_dialogue_v3_0098", "base_id": "university_registration_0056_closed_derived_missing_antecedent", "split": "dev", "domain": "university_registration", "family": "closed_derived_missing_antecedent", "subset": "core_contrastive", "gold_pattern": "unknown|false|false", "dialogue_type": "persist_after_narrowing", "target_statement": "Lena may register for the seminar.", "query_atom": "may_register::Lena", "facts_positive": ["Lena 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::Lena"], "negative_atoms": [], "rules": [{"antecedents": ["passed_exam::Lena", "has_advising_clearance::Lena"], "conclusion": "may_register::Lena", "text": "If a student passed the qualifying exam and has advising clearance, then that student may register for the seminar."}], "query_atom": "may_register::Lena", "closure_atoms": ["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 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: Lena may register for the seminar.\nTarget atom: may_register::Lena\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: Lena may register for the seminar.\nTarget atom: may_register::Lena"}, {"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: Lena may register for the seminar.\nTarget atom: may_register::Lena"}]}