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"title": "Pipeline-Refactoring 1\/6: DB-Schema für Textsemantik und Wissenssemantik",
"type": "ai_task",
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"description": "## Ziel\nZwei neue Tabellen in ki_content erstellen für die semantischen Analyse-Ergebnisse.\n\n---\n\n## Analyse\n\n### Textsemantik (Phase 4)\nAnalysiert WIE etwas gesagt wird, bevor wir wissen WAS gesagt wird.\n\n**Dimensionen:**\n| Dimension | Werte | Beispiel |\n|-----------|-------|----------|\n| statement_form | assertion, question, command, conditional | \"Systemische Therapie ist...\" → assertion |\n| intent | explain, argue, define, compare, contrast, exemplify, warn | \"erklärt\" → explain |\n| frame | theoretical, practical, historical, methodological, critical | Kontext der Aussage |\n| negation | true\/false | \"ist NICHT geeignet\" → true |\n| discourse_role | thesis, evidence, example, counter, transition, summary | Rolle im Text |\n\n### Wissenssemantik (Phase 6)\nAnalysiert die BEDEUTUNG der Entitäten im spezifischen Kontext.\n\n**Dimensionen:**\n| Dimension | Werte | Beispiel |\n|-----------|-------|----------|\n| role | agent, patient, instrument, location, cause, effect | Wer\/was tut? |\n| properties | JSON | {\"duration\": \"6 Monate\", \"setting\": \"ambulant\"} |\n| functional_category | method, tool, concept, actor, outcome, constraint | Was IST es? |\n| context_meaning | Text | Spezifische Bedeutung hier |\n\n---\n\n## Planung\n\n### Tabelle 1: chunk_text_semantics\n```sql\nCREATE TABLE chunk_text_semantics (\n id INT AUTO_INCREMENT PRIMARY KEY,\n chunk_id INT NOT NULL,\n \n -- Aussageform\n statement_form ENUM('assertion', 'question', 'command', 'conditional', 'exclamation') NOT NULL,\n \n -- Kommunikative Absicht\n intent ENUM('explain', 'argue', 'define', 'compare', 'contrast', 'exemplify', \n 'warn', 'recommend', 'describe', 'narrate', 'instruct') DEFAULT NULL,\n \n -- Referenzrahmen\n frame ENUM('theoretical', 'practical', 'historical', 'methodological', \n 'critical', 'empirical', 'normative') DEFAULT NULL,\n \n -- Negation\n is_negated BOOLEAN DEFAULT FALSE,\n \n -- Diskursrolle\n discourse_role ENUM('thesis', 'evidence', 'example', 'counter', 'transition', \n 'summary', 'definition', 'elaboration', 'conclusion') DEFAULT NULL,\n \n -- Qualität\n confidence DECIMAL(3,2) DEFAULT NULL,\n model_used VARCHAR(100) DEFAULT NULL,\n \n -- Zeitstempel\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,\n \n -- Constraints\n FOREIGN KEY (chunk_id) REFERENCES chunks(id) ON DELETE CASCADE,\n INDEX idx_chunk (chunk_id),\n INDEX idx_intent (intent),\n INDEX idx_discourse (discourse_role)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;\n```\n\n### Tabelle 2: entity_knowledge_semantics\n```sql\nCREATE TABLE entity_knowledge_semantics (\n id INT AUTO_INCREMENT PRIMARY KEY,\n entity_id INT NOT NULL,\n chunk_id INT NOT NULL, -- Kontext der Bedeutung\n \n -- Semantische Rolle\n semantic_role ENUM('agent', 'patient', 'instrument', 'location', 'cause', \n 'effect', 'beneficiary', 'source', 'goal', 'theme') DEFAULT NULL,\n \n -- Eigenschaften (flexibel)\n properties JSON DEFAULT NULL,\n \n -- Funktionale Kategorie\n functional_category ENUM('method', 'tool', 'concept', 'actor', 'outcome', \n 'constraint', 'resource', 'process', 'artifact', 'principle') DEFAULT NULL,\n \n -- Kontextuelle Bedeutung\n context_meaning TEXT DEFAULT NULL,\n \n -- Qualität\n confidence DECIMAL(3,2) DEFAULT NULL,\n model_used VARCHAR(100) DEFAULT NULL,\n \n -- Zeitstempel\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,\n \n -- Constraints\n FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE CASCADE,\n FOREIGN KEY (chunk_id) REFERENCES chunks(id) ON DELETE CASCADE,\n INDEX idx_entity (entity_id),\n INDEX idx_chunk (chunk_id),\n INDEX idx_role (semantic_role),\n INDEX idx_category (functional_category)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;\n```\n\n---\n\n## Abhängigkeiten\n- Keine (erste Aufgabe)\n\n## Akzeptanzkriterien\n- [ ] Beide Tabellen existieren in ki_content\n- [ ] Foreign Keys funktionieren\n- [ ] Indizes sind angelegt\n- [ ] Test-Insert erfolgreich"
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"text": "{\n \"success\": true,\n \"task\": {\n \"id\": 493,\n \"uuid\": \"23345776-c1bc-4e62-8093-53ac508ddd42\",\n \"title\": \"Pipeline-Refactoring 1\/6: DB-Schema für Textsemantik und Wissenssemantik\",\n \"description\": \"## Ziel\\nZwei neue Tabellen in ki_content erstellen für die semantischen Analyse-Ergebnisse.\\n\\n---\\n\\n## Analyse\\n\\n### Textsemantik (Phase 4)\\nAnalysiert WIE etwas gesagt wird, bevor wir wissen WAS gesagt wird.\\n\\n**Dimensionen:**\\n| Dimension | Werte | Beispiel |\\n|-----------|-------|----------|\\n| statement_form | assertion, question, command, conditional | \\\"Systemische Therapie ist...\\\" → assertion |\\n| intent | explain, argue, define, compare, contrast, exemplify, warn | \\\"erklärt\\\" → explain |\\n| frame | theoretical, practical, historical, methodological, critical | Kontext der Aussage |\\n| negation | true\/false | \\\"ist NICHT geeignet\\\" → true |\\n| discourse_role | thesis, evidence, example, counter, transition, summary | Rolle im Text |\\n\\n### Wissenssemantik (Phase 6)\\nAnalysiert die BEDEUTUNG der Entitäten im spezifischen Kontext.\\n\\n**Dimensionen:**\\n| Dimension | Werte | Beispiel |\\n|-----------|-------|----------|\\n| role | agent, patient, instrument, location, cause, effect | Wer\/was tut? |\\n| properties | JSON | {\\\"duration\\\": \\\"6 Monate\\\", \\\"setting\\\": \\\"ambulant\\\"} |\\n| functional_category | method, tool, concept, actor, outcome, constraint | Was IST es? |\\n| context_meaning | Text | Spezifische Bedeutung hier |\\n\\n---\\n\\n## Planung\\n\\n### Tabelle 1: chunk_text_semantics\\n```sql\\nCREATE TABLE chunk_text_semantics (\\n id INT AUTO_INCREMENT PRIMARY KEY,\\n chunk_id INT NOT NULL,\\n \\n -- Aussageform\\n statement_form ENUM('assertion', 'question', 'command', 'conditional', 'exclamation') NOT NULL,\\n \\n -- Kommunikative Absicht\\n intent ENUM('explain', 'argue', 'define', 'compare', 'contrast', 'exemplify', \\n 'warn', 'recommend', 'describe', 'narrate', 'instruct') DEFAULT NULL,\\n \\n -- Referenzrahmen\\n frame ENUM('theoretical', 'practical', 'historical', 'methodological', \\n 'critical', 'empirical', 'normative') DEFAULT NULL,\\n \\n -- Negation\\n is_negated BOOLEAN DEFAULT FALSE,\\n \\n -- Diskursrolle\\n discourse_role ENUM('thesis', 'evidence', 'example', 'counter', 'transition', \\n 'summary', 'definition', 'elaboration', 'conclusion') DEFAULT NULL,\\n \\n -- Qualität\\n confidence DECIMAL(3,2) DEFAULT NULL,\\n model_used VARCHAR(100) DEFAULT NULL,\\n \\n -- Zeitstempel\\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,\\n \\n -- Constraints\\n FOREIGN KEY (chunk_id) REFERENCES chunks(id) ON DELETE CASCADE,\\n INDEX idx_chunk (chunk_id),\\n INDEX idx_intent (intent),\\n INDEX idx_discourse (discourse_role)\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;\\n```\\n\\n### Tabelle 2: entity_knowledge_semantics\\n```sql\\nCREATE TABLE entity_knowledge_semantics (\\n id INT AUTO_INCREMENT PRIMARY KEY,\\n entity_id INT NOT NULL,\\n chunk_id INT NOT NULL, -- Kontext der Bedeutung\\n \\n -- Semantische Rolle\\n semantic_role ENUM('agent', 'patient', 'instrument', 'location', 'cause', \\n 'effect', 'beneficiary', 'source', 'goal', 'theme') DEFAULT NULL,\\n \\n -- Eigenschaften (flexibel)\\n properties JSON DEFAULT NULL,\\n \\n -- Funktionale Kategorie\\n functional_category ENUM('method', 'tool', 'concept', 'actor', 'outcome', \\n 'constraint', 'resource', 'process', 'artifact', 'principle') DEFAULT NULL,\\n \\n -- Kontextuelle Bedeutung\\n context_meaning TEXT DEFAULT NULL,\\n \\n -- Qualität\\n confidence DECIMAL(3,2) DEFAULT NULL,\\n model_used VARCHAR(100) DEFAULT NULL,\\n \\n -- Zeitstempel\\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,\\n \\n -- Constraints\\n FOREIGN KEY (entity_id) REFERENCES entities(id) ON DELETE CASCADE,\\n FOREIGN KEY (chunk_id) REFERENCES chunks(id) ON DELETE CASCADE,\\n INDEX idx_entity (entity_id),\\n INDEX idx_chunk (chunk_id),\\n INDEX idx_role (semantic_role),\\n INDEX idx_category (functional_category)\\n) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;\\n```\\n\\n---\\n\\n## Abhängigkeiten\\n- Keine (erste Aufgabe)\\n\\n## Akzeptanzkriterien\\n- [ ] Beide Tabellen existieren in ki_content\\n- [ ] Foreign Keys funktionieren\\n- [ ] Indizes sind angelegt\\n- [ ] Test-Insert erfolgreich\",\n \"type\": \"ai_task\",\n \"status\": \"pending\",\n \"created_by\": \"mcp-tasks\",\n \"created_by_type\": \"ai\",\n \"parent_task_id\": 492,\n \"due_date\": null,\n \"created_at\": \"2025-12-28T01:30:02.004003\",\n \"updated_at\": \"2025-12-28T01:30:02.004004\",\n \"completed_at\": null,\n \"metadata\": {}\n },\n \"message\": \"Task #493 created\"\n}"
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