Capture run provenance and prompt/version settings for reproducibility.
{
"run_id": "run-20260412T130357Z-demo_02_policy_stress_te-qwen35_semparse_9b-26940",
"run_started_utc": "2026-04-12T13:03:57+00:00",
"run_finished_utc": "2026-04-12T13:04:21+00:00",
"scenario": "demo_02_policy_stress_test_machine",
"ontology_kb_name": "demo_02_policy_stress_test_machine",
"backend": "ollama",
"model": "qwen35-semparse:9b",
"model_settings": {
"temperature": 0,
"context_length": 8192,
"classifier_context_length": 8192,
"timeout_seconds": 120,
"runtime": "core",
"two_pass": true,
"split_extraction": true,
"strict_registry": false,
"strict_types": false,
"clarification_eagerness": 0.35,
"max_clarification_rounds": 2,
"require_final_confirmation": false,
"progress_memory_enabled": true,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"clarification_auto_answer_enabled": false,
"clarification_answer_backend": "",
"clarification_answer_base_url": "",
"clarification_answer_model": "",
"clarification_answer_context_length": 0,
"clarification_answer_history_turns": 0,
"clarification_answer_kb_clause_limit": 0,
"clarification_answer_kb_char_budget": 0,
"clarification_answer_min_confidence": 0.0,
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"clarification_answer_role": "",
"served_llm_model": "",
"served_llm_backend": "",
"served_llm_base_url": "",
"served_llm_context_length": 0,
"backend_options": {
"num_ctx": 8192
}
},
"prompt_provenance": {
"status": "ok",
"prompt_id": "sp-1e43c641b01b",
"prompt_sha256": "1e43c641b01b7c845b82331b521d58c1993e8010bd9283f5085dac687520159e",
"source_path": "D:\\_PROJECTS\\prethinker\\modelfiles\\semantic_parser_system_prompt.md",
"snapshot_path": "D:\\_PROJECTS\\prethinker\\modelfiles\\history\\prompts\\sp-1e43c641b01b.md",
"snapshot_created": false,
"char_count": 9603,
"line_count": 221,
"preview": "# Semantic Parser Prompt Pack (Qwen 3.5 9B)\nUse this as maintainable guidance for semantic parsing into Prolog structures.\nKeep behavior language-agnostic, deterministic, and schema-strict.\n## Core Priorities\n1. Output exactly one JSON object that matches the required schema.\n2. Preserve semantic meaning; do not hallucinate entities, facts, or arguments.\n3. Prefer canonical, stable predicate names across turns when semantics match.\n4. Use variables instead of assumptions when referents are unresolved."
}
}prompt_id=sp-1e43c641b01b prompt_sha256=1e43c641b01b7c845b82331b521d58c1993e8010bd9283f5085dac687520159e snapshot_path=D:\_PROJECTS\prethinker\modelfiles\history\prompts\sp-1e43c641b01b.md preview: # Semantic Parser Prompt Pack (Qwen 3.5 9B) Use this as maintainable guidance for semantic parsing into Prolog structures. Keep behavior language-agnostic, deterministic, and schema-strict. ## Core Priorities 1. Output exactly one JSON object that matches the required schema. 2. Preserve semantic meaning; do not hallucinate entities, facts, or arguments. 3. Prefer canonical, stable predicate names across turns when semantics match. 4. Use variables instead of assumptions when referents are unresolved.
If reimbursement_amount(T, over_10000) and requested_by(T, P) and approved_by(T, P) then policy_violation(T, self_approval_over_10000).
{
"expected_utterance": "If reimbursement_amount(T, over_10000) and requested_by(T, P) and approved_by(T, P) then policy_violation(T, self_approval_over_10000).",
"observed_utterance": "If reimbursement_amount(T, over_10000) and requested_by(T, P) and approved_by(T, P) then policy_violation(T, self_approval_over_10000).",
"route": "assert_rule",
"expected_route": "assert_rule",
"route_source": "heuristic",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_rule",
"logic_string": "policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P).",
"components": {
"atoms": [
"over_10000",
"self_approval_over_10000"
],
"variables": [
"P",
"T"
],
"predicates": [
"approved_by",
"policy_violation",
"reimbursement_amount",
"requested_by"
]
},
"facts": [],
"rules": [
"policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P)."
],
"queries": [],
"confidence": {
"overall": 0.95,
"intent": 1.0,
"logic": 0.95
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.05,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No?",
"clarification_reason": "Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No",
"rationale": "Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No left-recursion."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.05,
"effective_uncertainty": 0.05,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Introduce an inference rule so downstream queries can derive new truths. Utterance expected/observed: If reimbursement_amount(T, over_10000) and requested_by(T, P) and approved_by(T, P) then policy_violation(T, self_approval_over_10000). / If reimbursement_amount(T, over_10000) and requested_by(T, P) and approved_by(T, P) then policy_violation(T, self_approval_over_10000). Route expected/observed: assert_rule / assert_rule Parser path: source=heuristic repaired=False fallback=False
intent=assert_rule apply_tool=assert_rule apply_status=success effect=mutation(write) submitted=policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P). result_type=rule_asserted rule=policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P).
intent=assert_rule logic=policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P). facts=[] rules=['policy_violation(T, self_approval_over_10000) :- reimbursement_amount(T, over_10000), requested_by(T, P), approved_by(T, P).'] queries=[] uncertainty_score=0.05 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No? clarification_reason=Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No predicates=['approved_by', 'policy_violation', 'reimbursement_amount', 'requested_by'] atoms=['over_10000', 'self_approval_over_10000'] variables=['P', 'T']
pending=False
question=Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule. Subject/object roles preserved. No?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.05, 'effective_uncertainty': 0.05, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_rule apply_status=success
If requested_by(T, E) and approved_by(T, M) and manages(M, E) then policy_violation(T, manager_approval_conflict).
{
"expected_utterance": "If requested_by(T, E) and approved_by(T, M) and manages(M, E) then policy_violation(T, manager_approval_conflict).",
"observed_utterance": "If requested_by(T, E) and approved_by(T, M) and manages(M, E) then policy_violation(T, manager_approval_conflict).",
"route": "assert_rule",
"expected_route": "assert_rule",
"route_source": "heuristic",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_rule",
"logic_string": "policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E).",
"components": {
"atoms": [
"manager_approval_conflict"
],
"variables": [
"E",
"M",
"T"
],
"predicates": [
"approved_by",
"manages",
"policy_violation",
"requested_by"
]
},
"facts": [],
"rules": [
"policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E)."
],
"queries": [],
"confidence": {
"overall": 0.95,
"intent": 1.0,
"logic": 0.95
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.05,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule using provided ontology predicates?",
"clarification_reason": "Direct mapping of conditional logic to Prolog rule using provided ontology predicates.",
"rationale": "Direct mapping of conditional logic to Prolog rule using provided ontology predicates."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule using provided ontology predicates?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.05,
"effective_uncertainty": 0.05,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Introduce an inference rule so downstream queries can derive new truths. Utterance expected/observed: If requested_by(T, E) and approved_by(T, M) and manages(M, E) then policy_violation(T, manager_approval_conflict). / If requested_by(T, E) and approved_by(T, M) and manages(M, E) then policy_violation(T, manager_approval_conflict). Route expected/observed: assert_rule / assert_rule Parser path: source=heuristic repaired=False fallback=False
intent=assert_rule apply_tool=assert_rule apply_status=success effect=mutation(write) submitted=policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E). result_type=rule_asserted rule=policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E).
intent=assert_rule logic=policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E). facts=[] rules=['policy_violation(T, manager_approval_conflict) :- requested_by(T, E), approved_by(T, M), manages(M, E).'] queries=[] uncertainty_score=0.05 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule using provided ontology predicates? clarification_reason=Direct mapping of conditional logic to Prolog rule using provided ontology predicates. predicates=['approved_by', 'manages', 'policy_violation', 'requested_by'] atoms=['manager_approval_conflict'] variables=['E', 'M', 'T']
pending=False
question=Can you clarify this point before I apply it: Direct mapping of conditional logic to Prolog rule using provided ontology predicates?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.05, 'effective_uncertainty': 0.05, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_rule apply_status=success
reimbursement_amount(feb_txn_01, over_10000).
{
"expected_utterance": "reimbursement_amount(feb_txn_01, over_10000).",
"observed_utterance": "reimbursement_amount(feb_txn_01, over_10000).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "reimbursement_amount(feb_txn_01, over_10000).",
"components": {
"atoms": [
"feb_txn_01",
"over_10000"
],
"variables": [],
"predicates": [
"reimbursement_amount"
]
},
"facts": [
"reimbursement_amount(feb_txn_01, over_10000)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 0.95,
"intent": 1.0,
"logic": 0.95
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.05,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?",
"clarification_reason": "Direct mapping of declarative fact to ontology predicate.",
"rationale": "Direct mapping of declarative fact to ontology predicate. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.05,
"effective_uncertainty": 0.05,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: reimbursement_amount(feb_txn_01, over_10000). / reimbursement_amount(feb_txn_01, over_10000). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=reimbursement_amount(feb_txn_01, over_10000). result_type=fact_asserted fact=reimbursement_amount(feb_txn_01, over_10000).
intent=assert_fact logic=reimbursement_amount(feb_txn_01, over_10000). facts=['reimbursement_amount(feb_txn_01, over_10000).'] rules=[] queries=[] uncertainty_score=0.05 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate? clarification_reason=Direct mapping of declarative fact to ontology predicate. predicates=['reimbursement_amount'] atoms=['feb_txn_01', 'over_10000'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.05, 'effective_uncertainty': 0.05, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
requested_by(feb_txn_01, dana).
{
"expected_utterance": "requested_by(feb_txn_01, dana).",
"observed_utterance": "requested_by(feb_txn_01, dana).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "requested_by(feb_txn_01, dana).",
"components": {
"atoms": [
"dana",
"feb_txn_01"
],
"variables": [],
"predicates": [
"requested_by"
]
},
"facts": [
"requested_by(feb_txn_01, dana)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 1.0,
"intent": 1.0,
"logic": 1.0
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.0,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'?",
"clarification_reason": "Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'.",
"rationale": "Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.0,
"effective_uncertainty": 0.0,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: requested_by(feb_txn_01, dana). / requested_by(feb_txn_01, dana). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=requested_by(feb_txn_01, dana). result_type=fact_asserted fact=requested_by(feb_txn_01, dana).
intent=assert_fact logic=requested_by(feb_txn_01, dana). facts=['requested_by(feb_txn_01, dana).'] rules=[] queries=[] uncertainty_score=0.0 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'? clarification_reason=Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'. predicates=['requested_by'] atoms=['dana', 'feb_txn_01'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of subject 'feb_txn_01' and object 'dana' to predicate 'requested_by'?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.0, 'effective_uncertainty': 0.0, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
approved_by(feb_txn_01, dana).
{
"expected_utterance": "approved_by(feb_txn_01, dana).",
"observed_utterance": "approved_by(feb_txn_01, dana).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "approved_by(feb_txn_01, dana).",
"components": {
"atoms": [
"dana",
"feb_txn_01"
],
"variables": [],
"predicates": [
"approved_by"
]
},
"facts": [
"approved_by(feb_txn_01, dana)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 1.0,
"intent": 1.0,
"logic": 1.0
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.0,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate?",
"clarification_reason": "Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate.",
"rationale": "Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.0,
"effective_uncertainty": 0.0,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: approved_by(feb_txn_01, dana). / approved_by(feb_txn_01, dana). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=approved_by(feb_txn_01, dana). result_type=fact_asserted fact=approved_by(feb_txn_01, dana).
intent=assert_fact logic=approved_by(feb_txn_01, dana). facts=['approved_by(feb_txn_01, dana).'] rules=[] queries=[] uncertainty_score=0.0 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate? clarification_reason=Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate. predicates=['approved_by'] atoms=['dana', 'feb_txn_01'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_01, dana)' to canonical predicate?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.0, 'effective_uncertainty': 0.0, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
reimbursement_amount(feb_txn_02, over_10000).
{
"expected_utterance": "reimbursement_amount(feb_txn_02, over_10000).",
"observed_utterance": "reimbursement_amount(feb_txn_02, over_10000).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "reimbursement_amount(feb_txn_02, over_10000).",
"components": {
"atoms": [
"feb_txn_02",
"over_10000"
],
"variables": [],
"predicates": [
"reimbursement_amount"
]
},
"facts": [
"reimbursement_amount(feb_txn_02, over_10000)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 0.95,
"intent": 1.0,
"logic": 0.95
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.05,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?",
"clarification_reason": "Direct mapping of declarative fact to ontology predicate.",
"rationale": "Direct mapping of declarative fact to ontology predicate. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.05,
"effective_uncertainty": 0.05,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: reimbursement_amount(feb_txn_02, over_10000). / reimbursement_amount(feb_txn_02, over_10000). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=reimbursement_amount(feb_txn_02, over_10000). result_type=fact_asserted fact=reimbursement_amount(feb_txn_02, over_10000).
intent=assert_fact logic=reimbursement_amount(feb_txn_02, over_10000). facts=['reimbursement_amount(feb_txn_02, over_10000).'] rules=[] queries=[] uncertainty_score=0.05 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate? clarification_reason=Direct mapping of declarative fact to ontology predicate. predicates=['reimbursement_amount'] atoms=['feb_txn_02', 'over_10000'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of declarative fact to ontology predicate?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.05, 'effective_uncertainty': 0.05, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
requested_by(feb_txn_02, alex).
{
"expected_utterance": "requested_by(feb_txn_02, alex).",
"observed_utterance": "requested_by(feb_txn_02, alex).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "requested_by(feb_txn_02, alex).",
"components": {
"atoms": [
"alex",
"feb_txn_02"
],
"variables": [],
"predicates": [
"requested_by"
]
},
"facts": [
"requested_by(feb_txn_02, alex)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 1.0,
"intent": 1.0,
"logic": 1.0
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.0,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of subject 'requested_by' with explicit arguments?",
"clarification_reason": "Direct mapping of subject 'requested_by' with explicit arguments.",
"rationale": "Direct mapping of subject 'requested_by' with explicit arguments. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of subject 'requested_by' with explicit arguments?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.0,
"effective_uncertainty": 0.0,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: requested_by(feb_txn_02, alex). / requested_by(feb_txn_02, alex). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=requested_by(feb_txn_02, alex). result_type=fact_asserted fact=requested_by(feb_txn_02, alex).
intent=assert_fact logic=requested_by(feb_txn_02, alex). facts=['requested_by(feb_txn_02, alex).'] rules=[] queries=[] uncertainty_score=0.0 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of subject 'requested_by' with explicit arguments? clarification_reason=Direct mapping of subject 'requested_by' with explicit arguments. predicates=['requested_by'] atoms=['alex', 'feb_txn_02'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of subject 'requested_by' with explicit arguments?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.0, 'effective_uncertainty': 0.0, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
approved_by(feb_txn_02, maya).
{
"expected_utterance": "approved_by(feb_txn_02, maya).",
"observed_utterance": "approved_by(feb_txn_02, maya).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "approved_by(feb_txn_02, maya).",
"components": {
"atoms": [
"feb_txn_02",
"maya"
],
"variables": [],
"predicates": [
"approved_by"
]
},
"facts": [
"approved_by(feb_txn_02, maya)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 1.0,
"intent": 1.0,
"logic": 1.0
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.0,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate?",
"clarification_reason": "Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate.",
"rationale": "Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.0,
"effective_uncertainty": 0.0,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: approved_by(feb_txn_02, maya). / approved_by(feb_txn_02, maya). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=approved_by(feb_txn_02, maya). result_type=fact_asserted fact=approved_by(feb_txn_02, maya).
intent=assert_fact logic=approved_by(feb_txn_02, maya). facts=['approved_by(feb_txn_02, maya).'] rules=[] queries=[] uncertainty_score=0.0 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate? clarification_reason=Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate. predicates=['approved_by'] atoms=['feb_txn_02', 'maya'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of 'approved_by(feb_txn_02, maya)' to canonical predicate?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.0, 'effective_uncertainty': 0.0, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
manages(maya, alex).
{
"expected_utterance": "manages(maya, alex).",
"observed_utterance": "manages(maya, alex).",
"route": "assert_fact",
"expected_route": "assert_fact",
"route_source": "model",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "assert_fact",
"logic_string": "manages(maya, alex).",
"components": {
"atoms": [
"alex",
"maya"
],
"variables": [],
"predicates": [
"manages"
]
},
"facts": [
"manages(maya, alex)."
],
"rules": [],
"queries": [],
"confidence": {
"overall": 1.0,
"intent": 1.0,
"logic": 1.0
},
"ambiguities": [],
"needs_clarification": false,
"uncertainty_score": 0.0,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'manages(maya, alex)' to fact?",
"clarification_reason": "Direct mapping of 'manages(maya, alex)' to fact.",
"rationale": "Direct mapping of 'manages(maya, alex)' to fact. Directional fact guard corrected inverted subject/object order."
},
"validation_errors": [],
"apply_status": "success",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this point before I apply it: Direct mapping of 'manages(maya, alex)' to fact?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.0,
"effective_uncertainty": 0.0,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Seed grounded terms/constants as facts for later inference. Utterance expected/observed: manages(maya, alex). / manages(maya, alex). Route expected/observed: assert_fact / assert_fact Parser path: source=model repaired=False fallback=False
intent=assert_fact apply_tool=assert_fact apply_status=success effect=mutation(write) submitted=manages(maya, alex). result_type=fact_asserted fact=manages(maya, alex).
intent=assert_fact logic=manages(maya, alex). facts=['manages(maya, alex).'] rules=[] queries=[] uncertainty_score=0.0 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this point before I apply it: Direct mapping of 'manages(maya, alex)' to fact? clarification_reason=Direct mapping of 'manages(maya, alex)' to fact. predicates=['manages'] atoms=['alex', 'maya'] variables=[]
pending=False
question=Can you clarify this point before I apply it: Direct mapping of 'manages(maya, alex)' to fact?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.0, 'effective_uncertainty': 0.0, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=assert_fact apply_status=success
Which February transactions violate policy?
{
"expected_utterance": "Which February transactions violate policy?",
"observed_utterance": "Which February transactions violate policy?",
"route": "query",
"expected_route": "query",
"route_source": "heuristic",
"repaired": false,
"fallback_used": false,
"parsed": {
"intent": "query",
"logic_string": "policy_violation(X, february).",
"components": {
"atoms": [
"february"
],
"variables": [
"X"
],
"predicates": [
"policy_violation"
]
},
"facts": [],
"rules": [],
"queries": [
"policy_violation(X, february)."
],
"confidence": {
"overall": 0.95,
"intent": 1.0,
"logic": 0.9
},
"ambiguities": [
"The specific policy predicate name is not explicitly defined in the context, so 'policy_violation' is used as a generic placeholder."
],
"needs_clarification": false,
"uncertainty_score": 0.15,
"uncertainty_label": "low",
"clarification_question": "Can you clarify this detail: The specific policy predicate name is not explicitly defined in the context, so 'policy_violation' is used as a generic placeholder?",
"clarification_reason": "The utterance is a direct question seeking facts about policy violations in",
"rationale": "The utterance is a direct question seeking facts about policy violations in February. It maps to a query for the predicate 'policy_violation' with the argument 'february'."
},
"validation_errors": [],
"apply_status": "no_results",
"utterance_ok": 1.0,
"turn_score": 1.0,
"clarification_rounds": [],
"clarification_pending": false,
"clarification_question": "Can you clarify this detail: The specific policy predicate name is not explicitly defined in the context, so 'policy_violation' is used as a generic placeholder?",
"clarification_policy": {
"clarification_eagerness": 0.35,
"uncertainty_score": 0.15,
"effective_uncertainty": 0.55,
"threshold": 0.65,
"request_clarification": false,
"needs_clarification_flag": false,
"progress_low_relevance": false,
"progress_high_risk": false,
"progress_low_relevance_threshold": 0.34,
"progress_high_risk_threshold": 0.18,
"progress_memory_available": true,
"progress_focus_present": false,
"progress_signal_term_count": 0,
"parsed_signal_term_count": 0,
"overlap_term_count": 0,
"progress_best_focus_overlap": 0.0,
"progress_relevance_score": 1.0
}
}Why asked: Probe current KB state and variable bindings. Utterance expected/observed: Which February transactions violate policy? / Which February transactions violate policy? Route expected/observed: query / query Parser path: source=heuristic repaired=False fallback=False
intent=query apply_tool=query_rows apply_status=no_results effect=none submitted=policy_violation(X, february). result_type=no_result
intent=query logic=policy_violation(X, february). facts=[] rules=[] queries=['policy_violation(X, february).'] uncertainty_score=0.15 uncertainty_label=low needs_clarification=False clarification_question=Can you clarify this detail: The specific policy predicate name is not explicitly defined in the context, so 'policy_violation' is used as a generic placeholder? clarification_reason=The utterance is a direct question seeking facts about policy violations in predicates=['policy_violation'] atoms=['february'] variables=['X']
pending=False
question=Can you clarify this detail: The specific policy predicate name is not explicitly defined in the context, so 'policy_violation' is used as a generic placeholder?
rounds_used=0 max_rounds=2
policy={'clarification_eagerness': 0.35, 'uncertainty_score': 0.15, 'effective_uncertainty': 0.55, 'threshold': 0.65, 'request_clarification': False, 'needs_clarification_flag': False, 'progress_low_relevance': False, 'progress_high_risk': False, 'progress_low_relevance_threshold': 0.34, 'progress_high_risk_threshold': 0.18, 'progress_memory_available': True, 'progress_focus_present': False, 'progress_signal_term_count': 0, 'parsed_signal_term_count': 0, 'overlap_term_count': 0, 'progress_best_focus_overlap': 0.0, 'progress_relevance_score': 1.0}score=1.0 (parse_ok=1.0, route_ok=1.0, apply_ok=1.0, utterance_ok=1.0) apply_tool=query_rows apply_status=no_results
Run deterministic KB validations and compare against expectations.
{
"validation_total": 2,
"validation_passed": 2,
"overall_status": "passed",
"turn_parse_failures": 0,
"turn_apply_failures": 0
}score=1.0 (2/2 passed)
txn01_self_approval_violation: PASS (query=policy_violation(feb_txn_01, self_approval_over_10000)., expected=success, observed=success) txn02_manager_conflict_violation: PASS (query=policy_violation(feb_txn_02, manager_approval_conflict)., expected=success, observed=success)
query=policy_violation(feb_txn_01, self_approval_over_10000). expected=success observed=success reasons=none
query=policy_violation(feb_txn_02, manager_approval_conflict). expected=success observed=success reasons=none