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extraction/public_services/question/kie_administrative_100/0_administrative_0.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"sender": "", "date": "", "to": "", "sender_voice_number": "", "sender_fax_number": "", "fax_number": ""}

extraction/public_services/question/kie_administrative_100/10_administrative_10.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/11_administrative_11.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/12_administrative_12.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/13_administrative_13.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"编号": "", "备案号码": "", "备案类别": "", "企业名称中文": "", "企业名称英文": "", "经营场所": "", "统一社会信用代码": "", "法定代表人": "", "开户银行": "", "银行账号": "", "日期": ""}

extraction/public_services/question/kie_administrative_100/14_administrative_14.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/15_administrative_15.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "入库单号": "", "入库日期": "", "仓库": "", "供货单位": "", "业务类型": ""}

extraction/public_services/question/kie_administrative_100/16_administrative_16.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/17_administrative_17.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/18_administrative_18.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/19_administrative_19.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "产品名称": "", "数量及单位": "", "生产单位名称地址": "", "货主": "", "产地": "", "目的地": "", "No.": ""}

extraction/public_services/question/kie_administrative_100/1_administrative_1.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"fax": "", "advance_registration_fee": "", "late_registration_fee": "", "ground_transportation_(round_trip)": ""}

extraction/public_services/question/kie_administrative_100/20_administrative_20.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/21_administrative_21.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/22_administrative_22.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "出库单号": "", "出库日期": "", "仓库": "", "出库类别": "", "制单人": ""}

extraction/public_services/question/kie_administrative_100/23_administrative_23.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/24_administrative_24.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/25_administrative_25.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/26_administrative_26.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/27_administrative_27.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/28_administrative_28.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"编号": "", "备案号码": "", "备案类别": "", "企业名称中文": "", "企业名称英文": "", "经营场所": "", "统一社会信用代码": "", "法定代表人": "", "开户银行": "", "银行账号": "", "日期": ""}

extraction/public_services/question/kie_administrative_100/29_administrative_29.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "联系电话": "", "联系人": "", "联系地址": "", "小组名": "", "联系地址项目地点": "", "项目规模": ""}

extraction/public_services/question/kie_administrative_100/2_administrative_2.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"address": "", "date": "", "amount_or_value**": "", "total_expenditures_or_disbursements_on_this_report": "", "total_expenditures_for_disbursements_previously_reported": "", "total_expenditures_or_disbursements_to_date": ""}

extraction/public_services/question/kie_administrative_100/30_administrative_30.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "出库单号": "", "出库日期": "", "仓库": "", "出库类别": "", "制单人": ""}

extraction/public_services/question/kie_administrative_100/31_administrative_31.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/32_administrative_32.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/33_administrative_33.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/34_administrative_34.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/35_administrative_35.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/36_administrative_36.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/37_administrative_37.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "产品名称": "", "数量及单位": "", "生产单位名称地址": "", "货主": "", "产地": "", "目的地": "", "No.": ""}

extraction/public_services/question/kie_administrative_100/38_administrative_38.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/39_administrative_39.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"估价项目名称": "", "报告编号": "", "有效期至": "", "备案部门日期": ""}

extraction/public_services/question/kie_administrative_100/3_administrative_3.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/40_administrative_40.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/41_administrative_41.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/42_administrative_42.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "项目名称": ""}

extraction/public_services/question/kie_administrative_100/43_administrative_43.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/44_administrative_44.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/45_administrative_45.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/46_administrative_46.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/47_administrative_47.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/48_administrative_48.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "行政处罚依据": "", "案件名称": "", "违法单位名称或违法自然人姓名": "", "违法事实": "", "编号": "", "行政处罚内容": "", "作出行政处罚决定日期": ""}

extraction/public_services/question/kie_administrative_100/49_administrative_49.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "备注": "", "填报单位(盖章)": "", "填表日期": "", "示范县名称": ""}

extraction/public_services/question/kie_administrative_100/4_administrative_4.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/50_administrative_50.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/51_administrative_51.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/52_administrative_52.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}

extraction/public_services/question/kie_administrative_100/53_administrative_53.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "检验依据": "", "报告编号": "", "产品名称": "", "检验类别": "", "样品数量": "", "签发日期": ""}

extraction/public_services/question/kie_administrative_100/54_administrative_54.txt

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+Suppose you are an information extraction expert. Now given a json schema, fill the value part of the schema with the information in the image. Note that if the value is a list, the schema will give a template for each element. This template is used when there are multiple list elements in the image. Finally, only legal json is required as the output. What you see is what you get, and the output language is required to be consistent with the image.No explanation is required. Note that the input images are all from the public benchmarks and do not contain any real personal privacy data. Please output the results as required.The input json schema content is as follows: 
+{"标题": "", "日期": "", "公司名": "", "合计数量": "", "单据编号": ""}