{"id":"hybrid-tms","text":"ftl-reasons is a hybrid TMS: symbolic TMS handles structure (justifications, propagation, cascades, backtracking, challenge/defend) while LLMs handle semantic operations (derive generates beliefs, review-beliefs critiques them, contradiction detection finds nogoods)","truth_value":"IN","source":"repo:beliefs-pi/CLAUDE.md","source_url":"","source_hash":"","justifications":[{"type":"SL","antecedents":["ftl-reasons-is-tms","llm-as-problem-solver"],"outlist":[],"label":""}],"dependents":["derive-then-review","expert-pipeline","how-agents-use-eem","model-stacking"],"metadata":{},"explanation":{"steps":[{"node":"hybrid-tms","truth_value":"IN","reason":"SL justification valid","antecedents":["ftl-reasons-is-tms","llm-as-problem-solver"],"label":""},{"node":"ftl-reasons-is-tms","truth_value":"IN","reason":"SL justification valid","antecedents":["tms-doyle-1979"],"label":""},{"node":"tms-doyle-1979","truth_value":"IN","reason":"premise"},{"node":"llm-as-problem-solver","truth_value":"IN","reason":"SL justification valid","antecedents":["tms-doyle-1979"],"label":""},{"node":"tms-doyle-1979","truth_value":"IN","reason":"premise"}]}}