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@@ -228,17 +228,17 @@ The following statistics are aligned with the configuration of the benchmark web
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  - The expected answer is in `"ground_truth"`, which contains the annotation results from our annotators as the ground truth.
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- - **Element-Recognition (ER)**: Provided in multiple-choice and fill-in formats.
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  - Example
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  - plaintext
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  ```
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- {"qid": "IMG000001-P2-Q3_O001_L1", "image_id": "IMG000001", "phase": "P2", "question_no": "Q3_O001_L1",
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- "type": "ER_choice", "answer_format": "single_choice",
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- "prompt": "请观察红框中的主体物象,判断其一级类别。\n\n要求:\n1)依据红框内容作答,不参考画面其他区域。\n2)本题为单选题,只输出一个选项字母(如 A)。\n\n选项:\nA. 植物\nB. 动物\nC. 人物\nD. 神佛\nE. 建筑\nF. 家具\nG. 交通\nH. 文玩\nI. 乐器\nJ. 水\nK. 峰峦\nL. 云雾\nM. 地形\nN. 环境\nO. 器物杂具\nP. 服饰纹样\nQ. 民俗节庆\n\n输出格式硬约束:\n- 输出一个选项字母(如 A)。\n- 禁止输出解释、标点、额外文本。",
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- "ground_truth": "E",
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  "image_paths": ["images/IMG000001_4.jpg"], "focus_bbox": [213.36073997944501, 233.20400194911036, 384.7893114080165, 407.0991715277332], "focus_image_index": 5, "focus_sub_image_path": "images/IMG000001_4.jpg"}
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  ```
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@@ -248,17 +248,21 @@ The following statistics are aligned with the configuration of the benchmark web
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  - The expected answer is in `"ground_truth"`.
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- - **Technique-Recognition (TR)**: Provided in multiple-choice and fill-in formats.
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  - Example
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  - plaintext
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  ```
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- {"qid": "IMG000001-P3-Q1_R001", "image_id": "IMG000001", "phase": "P3", "question_no": "Q1_R001", "type": "TR_choice", "answer_format": "single_choice", "prompt": "请只根据红框区域中的笔法与皴法特征作答。\n这是单选题。\nA. 披麻皴\nB. 解索皴\nC. 荷叶皴\nD. 牛毛皴\nE. 斧劈皴\nF. 雨点皴\nG. 拖泥带水皴\nH. 乱柴皴\nI. 弹涡皴\nJ. 卷云皴\nK. 米点皴\nL. 折带皴\n只输出一个选项字母,不要解释。\n\n输出格式硬约束:\n- 只输出一个选项字母(如 A)。\n- 禁止输出解释、标点、额外文本。", "ground_truth": "A", "image_paths": ["images/IMG000001_0.jpg"], "focus_bbox": [158.2181562604731, 537.6836388751759, 783.4618818175318, 727.151434498527], "focus_image_index": 1, "focus_sub_image_path": "images/IMG000001_0.jpg"}
 
 
 
 
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  ```
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- - The uploaded materials include the image itself (`"image_paths": ["images/IMG000001_4.jpg"]`) and a red annotation box (`"focus_bbox": [213.36073997944501, 233.20400194911036, 384.7893114080165, 407.0991715277332]`).
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  - The question is in `"prompt"`, which requires the model to identify the painting technique used in the given red box.
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  - The expected answer is in `"ground_truth"`, which contains the annotation results from our annotators as the ground truth.
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+ - **Element-Recognition (ER)**: Provided in fill-in formats.
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  - Example
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  - plaintext
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  ```
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+ {"qid": "IMG000001-P2-Q3_O001_L2_FILLIN", "image_id": "IMG000001", "phase": "P2", "question_no": "Q3_O001_L2_FILLIN",
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+ "type": "ER_fillin", "answer_format": "text",
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+ "prompt": "请观察红框中的主体物象,判断它具体是什么。\n只输出一个最合适的物象名称:松树、拱桥、高士,不要输出路径或解释。\n\n输出格式硬约束:\n- 输出最终答案,不要解释。",
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+ "ground_truth": "茅屋",
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  "image_paths": ["images/IMG000001_4.jpg"], "focus_bbox": [213.36073997944501, 233.20400194911036, 384.7893114080165, 407.0991715277332], "focus_image_index": 5, "focus_sub_image_path": "images/IMG000001_4.jpg"}
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  ```
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  - The expected answer is in `"ground_truth"`.
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+ - **Technique-Recognition (TR)**: Provided in fill-in formats.
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  - Example
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  - plaintext
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  ```
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+ {"qid": "IMG000001-P3-Q1_R001", "image_id": "IMG000001", "phase": "P3", "question_no": "Q1_R001",
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+ "type": "TR_fillin", "answer_format": "text",
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+ "prompt": "请观察红框区域,判断主要绘画技法。\n请直接输出技法名称,不要输出选项字母。\n\n输出格式硬约束:\n- 仅输出最终答案,不要解释。",
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+ "ground_truth": "披麻皴",
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+ "image_paths": ["images/IMG000001_0.jpg"], "focus_bbox": [158.2181562604731, 537.6836388751759, 783.4618818175318, 727.151434498527], "focus_image_index": 1, "focus_sub_image_path": "images/IMG000001_0.jpg"}
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  ```
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+ - The uploaded materials include the image itself (`"image_paths": ["images/IMG000001_0.jpg"]]`) and a red annotation box (`"focus_bbox": [158.2181562604731, 537.6836388751759, 783.4618818175318, 727.151434498527]`).
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  - The question is in `"prompt"`, which requires the model to identify the painting technique used in the given red box.
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