{
  "messages": [
    {
      "role": "system",
      "content": "You are a knowledge graph extraction agent for long-form novels. Extract entities and relations from the given text chunk. Return JSON only."
    },
    {
      "role": "user",
      "content": "Retrieved existing entity cards for this chunk. Reuse these canonical names/types when the same entity reappears; do not create near-duplicate entities if a card already matches the mention:\n[{\"entity_id\": \"E000022\", \"name\": \"心月狐\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0005\", \"last\": \"C0007\"}, \"mention_count\": 4, \"aliases\": [\"则天皇帝\", \"武曌\", \"武则天\"], \"descriptions\": [\"天星临凡\", \"投胎为唐家天子\"], \"matched_terms\": [\"武后\"], \"relations\": [\"公主|告知|心月狐\", \"心月狐|前往|上苑\"]}, {\"entity_id\": \"E000032\", \"name\": \"上苑\", \"type\": \"地点\", \"seen_range\": {\"first\": \"C0006\", \"last\": \"C0007\"}, \"mention_count\": 2, \"aliases\": [\"上林苑\"], \"descriptions\": [\"挥醉笔催花处\"], \"matched_terms\": [\"上林苑\"], \"relations\": [\"心月狐|前往|上苑\"]}, {\"entity_id\": \"E000030\", \"name\": \"公主\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0006\", \"last\": \"C0007\"}, \"mention_count\": 2, \"descriptions\": [\"率众宫娥叩贺\"], \"matched_terms\": [\"公主\"], \"relations\": [\"公主|告知|心月狐\", \"心月狐|告知|公主\"]}, {\"entity_id\": \"E000033\", \"name\": \"群芳圃\", \"type\": \"地点\", \"seen_range\": {\"first\": \"C0007\", \"last\": \"C0007\"}, \"mention_count\": 1, \"descriptions\": [\"赏花处\"], \"matched_terms\": [\"群芳圃\"], \"relations\": [\"心月狐|前往|群芳圃\"]}, {\"entity_id\": \"E000001\", \"name\": \"百花仙子\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0001\", \"last\": \"C0007\"}, \"mention_count\": 8, \"aliases\": [\"仙姑\", \"百草仙子\", \"洞主\"], \"descriptions\": [\"蓬莱山红颜洞仙姑\", \"修行多年\"], \"relations\": [\"百花仙子|告知|麻姑\", \"麻姑|告知|百花仙子\"]}, {\"entity_id\": \"E000019\", \"name\": \"麻姑\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0003\", \"last\": \"C0007\"}, \"mention_count\": 4, \"aliases\": [\"麻姑洞府\"], \"descriptions\": [\"戏言惩罚\"], \"relations\": [\"百花仙子|告知|麻姑\", \"麻姑|告知|百花仙子\"]}, {\"entity_id\": \"E000031\", \"name\": \"上官婉兒\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0006\", \"last\": \"C0007\"}, \"mention_count\": 2, \"descriptions\": [\"率众宫娥叩贺\"], \"relations\": [\"上官婉兒|告知|心月狐\"]}, {\"entity_id\": \"E000034\", \"name\": \"牡丹仙子\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0007\", \"last\": \"C0007\"}, \"mention_count\": 1, \"descriptions\": [\"花仙\"], \"relations\": [\"兰花仙子|告知|牡丹仙子\", \"牡丹仙子|告知|兰花仙子\"]}]\n\nOntology constraints (prefer these core types and normalized relations):\nAllowed core entity types:\n- 人物: 角色姓名, 主角/关键人物, 配角\n- 地点: 山岳/洞天, 洞府/殿阁, 城镇/疆域, 秘境\n- 组织: 宗门, 门派, 势力, 机构\n- 物品: 兵器, 法器, 经卷典籍, 其他道具\n- 其他\nNormalized relations:\n- 告知: aliases=说道, 问道, 笑道, 答道, 开口\n- 前往: aliases=前往, 来到, 进入, 回到, 抵达\n- 修炼: aliases=修炼, 修行, 参悟, 参修, 修习\nKey rules:\n- 实体 type 必须落在核心类型集合中；subtype 仅作细分，不得替代 type。\n- 若实体更像角色身份标签而非完整人物名，优先使用职位称号。\n- 若实体强调修炼路径与长期体系，优先使用功法体系；强调施展动作时优先使用术法神通。\n- 无法安全判断时允许使用其他，但应在后续 Type Consolidation 中优先收缩。\n\nCHUNK_ID: C0008 | PARA_RANGE: 8-8\n\nFrom the text chunk below, extract entities and relations. Output STRICT JSON with keys: entities (list) and relations (list). Entity schema: {name,type,aliases,attributes,descriptions,evidence,mentions}. mentions is a list of {chunk_id,summary,attributes,evidence}. Relation schema: {subject,relation,object,evidence,mentions}. mentions is a list of {chunk_id,summary,evidence}. Use ontology core types when possible. Do not invent new top-level entity type labels outside the ontology if an existing type fits. Prefer normalized relation names from the ontology alias list. If an existing entity card clearly matches a mention in this chunk, reuse that card's canonical name. If the chunk uses a title, alias, or shortened reference that matches a card, keep it under the same entity instead of splitting it. Keep outputs compact: at most 8 entities and 8 relations for this pass. Each description/evidence/summary should be short (<=30 characters) and avoid full sentences. Limit each entity to <=2 descriptions and <=2 mentions; each relation to <=1 mention. For mentions in this chunk, set chunk_id to the provided CHUNK_ID. Only include information supported by the chunk. Return a single JSON object and nothing else (no markdown, no code fences). If unsure, return {\"entities\":[],\"relations\":[]}.\n\nTEXT CHUNK:\n猛然想起昨日寫詔之事，連忙起來，心內著實懊悔酒後舉動，過於孟浪，倘群花竟不開放，將來傳揚出去，這場羞愧，如何遮掩？正在尋思，早有上林苑、群芳圃司花太監來報，各處群花大放。武后這一喜非同小可！登時把公主宣來，用過早膳，齊到上林苑。只見滿園青翠縈目，紅紫迎人，真是錦繡乾坤，花花世界。天時甚覺和暖，池沼都已解凍，陡然變成初春光景。正是：「池魚戲葉仍合凍，谷鳥啼花乍報春。」武后細細看去，只見眾花惟牡丹尚未開放。即查群芳圃，亦是如此。不覺大怒道：「朕自進宮以來，所有上林苑、群芳圃各花，每於早晚，俱令宮人加意澆灌，百般培養，自號督花天王。因素喜牡丹，尤加愛護。冬日則圍布幔以避嚴霜，夏日則遮涼篷以避烈日。三十餘年，習以為常。朕待此花，可謂深仁厚澤。不意今日群芳大放，彼獨無花。負恩昧良，莫此為甚！」吩咐太監即將各處牡丹，逐根掘起，多架柴炭，立時燒燬。公主勸道：「此時眾花即放，牡丹為花中之王，豈敢不遵御旨。但恐其花過大，開放不易。尚望主上再寬半日限期。倘仍無花，再治其罪，彼草木有知，諒亦無怨。」武后道：「你既替他懇求，姑且施恩，再限兩個時辰。如再無花，就怨不得朕了。」因問太監道：「此處牡丹若干株？」太監奏道：「上林苑共約二千餘株，與群芳圃數目相彷。」武后道：「此時已交辰初，就以辰時為限。爾等即燒炭火千盆，先把乾株枝梗炙枯，不可傷根。炙後如放葉開花，即將炭火撤去。俟到巳時無花，再將所餘千餘株，也用炭火炙枯。一交午時，如再不開，立將各處牡丹一總掘起，用刀斧捶為齏粉。那時朕再降旨，令天下盡絕其種。所有群芳圃牡丹，亦照此處一例辦理。」太監答應，登時炭火齊備。未知後事如何，且看下回分解。"
    }
  ]
}