{
  "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\": \"E000001\", \"name\": \"Alice\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0001\", \"last\": \"C0009\"}, \"mention_count\": 10, \"descriptions\": [\"女孩\", \"好奇\"], \"matched_terms\": [\"Alice\"], \"relations\": [\"Alice|前往|garden\", \"Alice|位于|hall\"]}, {\"entity_id\": \"E000014\", \"name\": \"hall\", \"type\": \"地点\", \"seen_range\": {\"first\": \"C0003\", \"last\": \"C0007\"}, \"mention_count\": 3, \"descriptions\": [\"长而低矮的大厅\", \"大厅\"], \"matched_terms\": [\"hall\"], \"relations\": [\"Alice|位于|hall\", \"doors|位于|hall\"]}, {\"entity_id\": \"E000017\", \"name\": \"key\", \"type\": \"物品\", \"seen_range\": {\"first\": \"C0003\", \"last\": \"C0009\"}, \"mention_count\": 6, \"aliases\": [\"golden key\", \"little golden key\"], \"descriptions\": [\"小金钥匙\"], \"relations\": [\"key|位于|table\", \"Alice|拿取|key\"]}, {\"entity_id\": \"E000002\", \"name\": \"White Rabbit\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0001\", \"last\": \"C0009\"}, \"mention_count\": 5, \"aliases\": [\"Rabbit\"], \"descriptions\": [\"白兔\", \"粉眼睛\"], \"relations\": [\"Alice|跟随|White Rabbit\", \"White Rabbit|担心|Duchess\"]}, {\"entity_id\": \"E000019\", \"name\": \"garden\", \"type\": \"地点\", \"seen_range\": {\"first\": \"C0004\", \"last\": \"C0009\"}, \"mention_count\": 5, \"aliases\": [\"lovely garden\"], \"descriptions\": [\"美丽花园\", \"花园\"], \"relations\": [\"Alice|前往|garden\", \"Alice|想要|garden\"]}, {\"entity_id\": \"E000016\", \"name\": \"table\", \"type\": \"物品\", \"seen_range\": {\"first\": \"C0003\", \"last\": \"C0009\"}, \"mention_count\": 5, \"aliases\": [\"three-legged table\", \"glass table\"], \"descriptions\": [\"三腿玻璃桌\", \"玻璃桌\"], \"relations\": [\"key|位于|table\", \"Alice|返回|table\"]}, {\"entity_id\": \"E000025\", \"name\": \"Mabel\", \"type\": \"人物\", \"seen_range\": {\"first\": \"C0008\", \"last\": \"C0009\"}, \"mention_count\": 2, \"descriptions\": [\"知识有限的女孩\"], \"relations\": [\"Alice|思考|Mabel\"]}, {\"entity_id\": \"E000026\", \"name\": \"fan\", \"type\": \"物品\", \"seen_range\": {\"first\": \"C0008\", \"last\": \"C0009\"}, \"mention_count\": 2, \"aliases\": [\"large fan\"], \"descriptions\": [\"扇子\"], \"relations\": [\"Alice|拥有|fan\", \"fan|导致|Alice\"]}]\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\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: C0010 | PARA_RANGE: 132-145\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:\nAs she said these words her foot slipped, and in another moment,\nsplash! she was up to her chin in salt water. Her first idea was that\nshe had somehow fallen into the sea, “and in that case I can go back by\n\nrailway,” she said to herself. (Alice had been to the seaside once in\nher life, and had come to the general conclusion, that wherever you go\nto on the English coast you find a number of bathing machines in the\n\nsea, some children digging in the sand with wooden spades, then a row\nof lodging houses, and behind them a railway station.) However, she\nsoon made out that she was in the pool of tears which she had wept when\n\nshe was nine feet high.\n\n“I wish I hadn’t cried so much!” said Alice, as she swam about, trying\n\nto find her way out. “I shall be punished for it now, I suppose, by\nbeing drowned in my own tears! That _will_ be a queer thing, to be\nsure! However, everything is queer to-day.”\n\nJust then she heard something splashing about in the pool a little way\noff, and she swam nearer to make out what it was: at first she thought\nit must be a walrus or hippopotamus, but then she remembered how small\n\nshe was now, and she soon made out that it was only a mouse that had\nslipped in like herself.\n\n“Would it be of any use, now,” thought Alice, “to speak to this mouse?\n\nEverything is so out-of-the-way down here, that I should think very\nlikely it can talk: at any rate, there’s no harm in trying.” So she\nbegan: “O Mouse, do you know the way out of this pool? I am very tired\n\nof swimming about here, O Mouse!” (Alice thought this must be the right\nway of speaking to a mouse: she had never done such a thing before, but\nshe remembered having seen in her brother’s Latin Grammar, “A mouse—of\n\na mouse—to a mouse—a mouse—O mouse!”) The Mouse looked at her rather\ninquisitively, and seemed to her to wink with one of its little eyes,\nbut it said nothing.\n\n“Perhaps it doesn’t understand English,” thought Alice; “I daresay it’s\n\na French mouse, come over with William the Conqueror.” (For, with all\nher knowledge of history, Alice had no very clear notion how long ago\nanything had happened.) So she began again: “Où est ma chatte?” which"
    }
  ]
}