auto backup: 2026-05-29 08:10:01

memory/.dreams/events.jsonl

@@ -69,3 +69,10 @@
 {"type":"memory.recall.recorded","timestamp":"2026-05-27T07:13:49.224Z","query":"lesson 421 17-1 知识点 推送 后台","resultCount":1,"results":[{"path":"memory/2026-05-21.md","startLine":65,"endLine":75,"score":1}]}
 {"type":"memory.recall.recorded","timestamp":"2026-05-27T07:13:49.225Z","query":"pushRelationKp 知识点推送 接口 notify","resultCount":1,"results":[{"path":"memory/2026-05-21.md","startLine":65,"endLine":75,"score":1}]}
 {"type":"memory.recall.recorded","timestamp":"2026-05-27T07:13:57.033Z","query":"U17 421 push 推送到后台 组件配置 知识点推送 知识↑","resultCount":4,"results":[{"path":"memory/2026-05-20.md","startLine":1,"endLine":31,"score":1},{"path":"memory/2026-05-18.md","startLine":740,"endLine":770,"score":1},{"path":"memory/2026-05-18.md","startLine":766,"endLine":797,"score":1},{"path":"memory/2026-05-21.md","startLine":39,"endLine":56,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T02:24:09.414Z","query":"武钰涵 组件配置 json","resultCount":2,"results":[{"path":"memory/2026-05-07.md","startLine":354,"endLine":368,"score":1},{"path":"memory/2026-04-22.md","startLine":1,"endLine":8,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T02:35:33.338Z","query":"单词题型 难度分级 word question type difficulty level","resultCount":1,"results":[{"path":"memory/2026-05-12.md","startLine":137,"endLine":149,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T02:35:41.380Z","query":"单词题型 word question types 词义选择 拼写判断 vocabulary grading classification","resultCount":1,"results":[{"path":"memory/2026-05-12.md","startLine":137,"endLine":149,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T03:07:41.725Z","query":"6题 文本 配置json 单元挑战","resultCount":1,"results":[{"path":"memory/2026-05-12.md","startLine":137,"endLine":149,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T03:07:46.098Z","query":"6题 刘彦江 看图拼词 imgMakeWord","resultCount":1,"results":[{"path":"memory/2026-05-12.md","startLine":137,"endLine":149,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T03:08:15.128Z","query":"看图拼词 imgMakeWord 样例 6题 刘彦江 2026-05-25","resultCount":1,"results":[{"path":"memory/2026-05-07.md","startLine":1,"endLine":20,"score":1}]}
+{"type":"memory.recall.recorded","timestamp":"2026-05-28T10:04:34.024Z","query":"李若松 身份 user_id","resultCount":2,"results":[{"path":"memory/2026-04-30.md","startLine":50,"endLine":63,"score":1},{"path":"memory/2026-05-08.md","startLine":18,"endLine":38,"score":1}]}

memory/.dreams/short-term-recall.json

@@ -1,6 +1,6 @@
 {
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-  "updatedAt": "2026-05-27T07:13:57.033Z",
+  "updatedAt": "2026-05-28T10:04:34.024Z",
   "entries": {
     "memory:memory/2026-05-07.md:57:74": {
       "key": "memory:memory/2026-05-07.md:57:74",
@@ -117,13 +117,13 @@
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       "snippet": "# 2026-05-07 工作日志 ## 会话记录 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 单元挑战新增3个题型 - **时间：** 11:19 ~ 11:28 - **需求：** 单元挑战新增3个题型：阅读看图回答题（reading_pic_qa）、阅读看图判断题（reading_pic_judge）、写作看图回答题（writing_pic_qa） - **状态：** ✅ 已完成题型规范落地 - **交付内容：** 1. 创建3个题型SKILL.md： - `reading/common/reading_pic_qa/SKILL.md` — 阅读看图回答题（共享大图+多题Yes/No判断） - `reading/common/reading_pic_judge/SKILL.md` — 阅读看图判断题（每题独立配图+Yes/No判断） - `writing/common/writing_pic_qa/SKILL.md` — 写作看图回答题（看图+提示答案开头+填空） 2. 更新 `MEMORY.md` 全题型阶段归属规则 3. 明确题型JSON结构、难度等级（A/B/C/D四级）、能力标签、校验规则 - **关键决策：** 3个题型均为 L1&L2 共用，通过难度参数区分阶段；reading_pic_qa 共享大图，reading_pic_judge 每题独立配图 ### 李应瑛 (ou_1bd7317ae2ccfeb57e1132028847279e) — 单词表对比请求",
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+      "totalScore": 11,
       "maxScore": 1,
       "firstRecalledAt": "2026-05-08T01:18:18.412Z",
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         "2026-05-08",
@@ -143,7 +144,8 @@
         "2026-05-12",
         "2026-05-14",
         "2026-05-17",
-        "2026-05-26"
+        "2026-05-26",
+        "2026-05-28"
       ],
       "conceptTags": [
         "reading-pic-qa",
@@ -435,18 +437,20 @@
       "endLine": 63,
       "source": "memory",
       "snippet": "格式: 【任务标题】【情境引入】【互动内容】【互动反馈】【后置对话】。目标词用$...$包裹，选项为图片区域编号(00/01/02)。 #### 5. 对话选择 (1条) — 规则: 参考 teaching_config 示例格式 + mid_dialog_choose prompt | ID | 任务标题 | 选项 | 知识点 | |---|---------|------|--------| | 1115514 | 判断蕃茄的好坏 | It is a good one. / It is a bad one. | one | 格式: 【任务标题】【资源配置】【情境引入】【互动内容】【后置对话】。互动内容含要求+选项+反馈。 ### 关键经验 - **组件配置列位置变更**: 本轮操作中发现sheet新增了「配置信息」列(C列)，导致组件配置从F列移至G列。后续操作需先确认列结构。 - **Bot身份操作**: 所有飞书 sheet 写入均使用 Bot 身份（App ID: cli_a931175d41799cc7），Feishu API Token: t-g1044ubUXXMPFXBW75RILL7YZKRGAKQGWWDV2R3D - **对话选择组件**: 无独立 SKILL.md，需参照 interactive-component-json 的 prompt_registry.py 中 mid_dialog_choose 模板 + bitable 中已有的 teaching_config 示例格式",
-      "recallCount": 1,
+      "recallCount": 2,
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       "maxScore": 1,
       "firstRecalledAt": "2026-05-13T03:09:54.362Z",
-      "lastRecalledAt": "2026-05-13T03:09:54.362Z",
+      "lastRecalledAt": "2026-05-28T10:04:34.024Z",
       "queryHashes": [
-        "f151bc633ad1"
+        "f151bc633ad1",
+        "71e44ea68b09"
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       "recallDays": [
-        "2026-05-13"
+        "2026-05-13",
+        "2026-05-28"
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       "conceptTags": [
         "00/01/02",
@@ -864,13 +868,13 @@
       "endLine": 368,
       "source": "memory",
       "snippet": "- **需求：** 将 020102（I am...）和 020103（I am ready / Thank you）两套题合并为一个 `{first:..., second:...}` JSON，统一 questionSetID=0000001 - **状态：** ✅ 已完成 - **核心考点分析（用户强调）：** 需分析每个句型的核心考点（孩子最容易犯错的地方），挖空对准核心考点 - I am/from 组：am（系动词第一人称）、from（介词选择）、student（a+名词结构） - Thank you for 组：for（介词选择，非 you）、helping（for+动名词，非 help/to help） - **输出文件：** `output/writing_pic_qa_combined.json` ### 刘彦江 — 组件配置-json 请求（L1-S2-U13-L4 沙漠之花） - **时间：** 16:45 ~ 17:51 - **文档：** `https://makee-interactive.feishu.cn/wiki/K5E1wzwk7it9t7kXvcbc6Xugnhc` - **状态：** ⚠️ 未完成 — pipeline 识别到 0 组件 - **根因：** 剧本文档的13个组件数据存储在 markdown 内联表格中（lark-table，5列×36行），而非内嵌 Sheet。当前 pipeline 的 parse_script 只从内嵌 Sheet 读取组件数据，不支持 markdown 表格组件解析 - **已识别组件（ma",
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       "firstRecalledAt": "2026-05-15T07:13:08.147Z",
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         "2026-05-15",
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-        "2026-05-25"
+        "2026-05-25",
+        "2026-05-28"
       ],
       "conceptTags": [
         "am/from",
@@ -907,13 +913,13 @@
       "endLine": 8,
       "source": "memory",
       "snippet": "[李应瑛 2026-04-22 提出要求] 所有需要包含对话的内容（如剧本、互动组件等）必须要有【后置对话】字段，无后置对话时填写“无”。 [李应瑛 2026-04-22 确认规则] 剧本内嵌表格组件填写位置规则：仅当表格第一列（A列）明确标注为对话类类型（对话朗读/对话挖空/对话选读/对话组句等）时，才在同一行的H列（【组件】列）填写对应的组件内容，其他类型行（TL/场景/角色/图片/非对话类等）无需填写。 [李应瑛 2026-04-22 确认格式规则] 对话类组件字段换行规则：每个结构单独占一行，格式为： 【任务标题】xxx 【情境引入】xxx 【互动内容】xxx 【后置对话】xxx 单元格内使用\\n作为换行符实现，后续所有组件均遵循此格式。",
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       "firstRecalledAt": "2026-05-15T07:13:08.147Z",
-      "lastRecalledAt": "2026-05-25T08:56:32.837Z",
+      "lastRecalledAt": "2026-05-28T02:24:09.414Z",
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         "47f8c15000b2",
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         "d6a04b711fd9",
-        "8742c0bf4e2b"
+        "8742c0bf4e2b",
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       "recallDays": [
         "2026-05-15",
         "2026-05-17",
         "2026-05-18",
         "2026-05-21",
-        "2026-05-25"
+        "2026-05-25",
+        "2026-05-28"
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       "conceptTags": [
         "对话朗读/对话挖空/对话选读/对话组句等",
@@ -980,25 +988,30 @@
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       "source": "memory",
       "snippet": "- **根因：** explanation 文本中的 ASCII `\"` (U+0022) 被当作中文双引号使用，JSON 解析器将其视为字符串终止符 - **修复策略：** 从「句意选择题」中文列提取英文原句和选项 → json.dumps 重建标准 JSON（只修格式，不修内容） - **1216007 特殊处理：** 原始 JSON 损坏严重，需从中文列完全重建 - **二次修复（Q2 丢失问题）：** 首次不完全修复导致 9 条记录的 Q2 被覆盖丢失，且 Q1 被 JSON 垃圾污染 → 从中文列全面重建 Q1+Q2 - **最终结果：10/10 条记录 sentenceMeaningMeaning 均可 json.loads 正确解析，每条含 2 题，无残留垃圾数据** - **受影响记录：** 1213004, 1213006, 1213010, 1214008, 1215005, 1216001, 1216004, 1216007, 1216008, 1216010 - **审校结果同步更新：** 移除所有 10 条的 `❌ JSON 解析失败` 标记 - **注意：** Q1 explanation 在重建时词表述可能微调（内容含义一致），如需精确原始 wording 可从中文列恢复后人工微调 ## 经验教训 ### bitable 写入需严格流程管控（2026-05-12） - 批量更新 JSON 字段时必须：写入前完整提取原始数据 → 写入后逐字段 diff 验证 → 发现异常立即回滚",
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       "firstRecalledAt": "2026-05-18T02:42:25.325Z",
-      "lastRecalledAt": "2026-05-26T06:06:25.056Z",
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       "recallDays": [
         "2026-05-18",
         "2026-05-25",
-        "2026-05-26"
+        "2026-05-26",
+        "2026-05-28"
       ],
       "conceptTags": [
         "json.dumps",
@@ -1503,13 +1516,13 @@
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       "source": "memory",
       "snippet": "4. question与questionDesc人称必须一致（统一改为 What does [角色] say? → 第一人称直接引语） - **JSON wrapper格式：** `{\"first\": 题组1完整JSON, \"second\": 题组2完整JSON}` - **输出文件：** `output/writing_pic_qa_000001_sample.json` ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — writing_pic_qa 生产流程标准化 + SKILL 重写 - **时间：** 09:34 ~ 09:46 - **需求：** 将完整生产流程补充到 SKILL.md，强化核心规则 - **状态：** ✅ 已完成 **核心规则强化（用户明确）：** 1. **挖空 = 考察句型结构本身**，不是复述图片信息（如 Thank you for → 挖 for 而非 you） 2. **考察多样化**：同句型覆盖多种搭配（for + 名词 / for + 动名词、be + 身份 / be + 状态词等） 3. **语言难度匹配欧标 A1-A2**（Starters/Movers） 4. **题干不千篇一律**：question 随语境微调（如 \"What does she say about herself?\" / \"Where does she say she is going?\" / \"What does she say to her friend?\"） **图片资源新规：** - 每个题组共享一",
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       "firstRecalledAt": "2026-05-20T06:31:39.981Z",
-      "lastRecalledAt": "2026-05-26T06:03:16.405Z",
+      "lastRecalledAt": "2026-05-28T10:04:34.024Z",
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@@ -1517,12 +1530,14 @@
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-        "9c790f74fc5b"
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       "recallDays": [
         "2026-05-20",
         "2026-05-25",
-        "2026-05-26"
+        "2026-05-26",
+        "2026-05-28"
       ],
       "conceptTags": [
         "writing-pic-qa",

memory/2026-05-28.md

@@ -0,0 +1,65 @@
+# 2026-05-28 工作日志
+
+## 武钰涵（user_id: 8ag94eff）— 组件配置-json
+- 处理剧本「L1-S2-U18-L2 登龙秘笈」(https://makee-interactive.feishu.cn/wiki/KNAZwTYXsib2Ijk6BrGciRelnSf)
+- 结果：17个组件，成功16个，跳过1个（1218216 核心互动-听力选择16，因类型名"核心互动-听力选择"未被 match_component 识别）
+- HTML 报告已通过 Bot 发送给武钰涵
+
+## 武钰涵 — 词汇知识点审校（批次1: 20词）
+- 用户提交了20个 L1 词汇知识点（含释义、音标、例句）请求审校
+- 校验结果：12个超纲（motorbike, hold, show, ago, grandmother, grandfather, visit, closed, home, understand, point, a lot of）
+- 内容问题：
+  - 🔴 get 格式错误：使用 ``` 包裹内容，中英文之间缺少空格
+  - 🟡 hold：3个义项（容纳/举办/保持）偏离核心释义"抓住"
+  - 🟡 point：例句2（pointed his flashlight）不匹配核心释义"指向"
+  - 🟡 ago：两个义项区分度低
+  - 🟡 a lot of → 建议改为 lots of（与L1词库一致）
+
+## 武钰涵 — 词汇知识点审校（批次2: 20词）
+- 用户提交第二批 20 个 L1 词汇知识点审校
+- 校验结果：16个超纲（仅 read/ruler/write/pencil 4个在库）
+- 内容问题：
+  - 🔴 10个词条格式不统一（``` 包裹 + 中英文无空格）：read, line, Chinese(adj.), perfect, eraser, Chinese(n.), write, rubber, playground, English(adj.)
+  - 🔴 Chinese(n.) 例句语法错误："My neighbour is Chinese who cooks" → 应改为 "My neighbour is Chinese and cooks"
+  - 🔴 China 例句冗余："Chinese food from China"
+  - 🔴 read 释义与词库不一致：申报"阅读，读懂"，词库仅"阅读"
+  - 🟡 eraser/rubber 双重申报，内容几乎一致，建议二选一
+
+## 武钰涵 — 词汇巩固题审校（批次1: 20词×3题=60题）
+- 仅发现1个错误：home (1217116) 释义题答案设为[2]（家庭），应为[0]（回家，在家），与用户申报的词性 adv. 一致
+- 其余59题通过
+
+## 武钰涵 — 词汇巩固题审校（批次2: 20词×3题=60题）
+- 🔴 English (1218118)：
+  - 释义题解析为 LLM 兜底拒答占位文本："请你提供具体的题目和对应正确答案内容..."
+  - 答案设为[2]（英语的），与申报 adj. 英文的不符，应为[0]
+- 🟡 rubber (1218116)：释义题例句"an eraser made of rubber"解释的是橡胶材料，非橡皮擦工具
+- 🟡 Chinese(n.) (1218113)：例句"Chinese food"中 Chinese 是形容词非名词，与题目义项"中文"不符
+- 🟢 fun (1218119)：解析末尾多余一个 `"`
+- 🟢 eraser (1218111)：`"an eraser表示"` 缺少空格
+
+## 武钰涵 — 听力-P1-图片选择题生产
+- 题目集合 ID: 121601，难度 B级（L1 第3-4阶段，Starters 3）
+- 知识点验证：10个词中仅 run(v.) 在 L1 词库，feet（foot 的复数）可视为已有，其余 8 个（bus, taxi, trousers, shorts, winter, snow, cold, bee）不在 L1/L2 词库
+- 用户指示直接生产，已按 SKILL 规范生成 2 个题组（各5题），含听力文本、图片描述、正确答案、能力标签
+- 已按 bitable 配置格式输出完整 jsonData + 题目完整配置 + 图片描述
+- B级规则：听力句子 5-8 词（均 7 词），每组 3 张同类物品不同属性图片
+- 能力标签：显性事实理解｜关键词识别 ×2 + 基础语境理解｜场景/物品/动作识别
+
+## 梁辰（user_id: ou_28f02dcada1193913cfbb6310f8daf07）— HTML 诊断页面教研规则 JS 文件
+- 用户有一个 L1 关卡诊断工作台 HTML 页面（部署在腾讯云空间），当前只做数量级统计，缺少教研规则校验
+- 需求：提供可嵌入 HTML 的前端 JS 校验规则文件，使诊断有据可依
+- 输出：`output/l1_pedagogy_rules.js`（42KB），包含 8 个校验维度：
+  1. 词汇超纲检测（基于 L1/L2 词库）
+  2. 英式拼写检测（color→colour 等 115 组映射）
+  3. Markdown 标记检测（`**`/`#`/`>` 等）
+  4. 标点规范检测（全角混入、`～`、`!!!`）
+  5. 题型-阶段匹配校验（20 种题型对应的 L1/L2 阶段映射）
+  6. 台词质量分析（句子长度、负面评价）
+  7. 知识点曝光度
+  8. 句型合规检测
+- 接入方式：`<script src="l1_pedagogy_rules.js"></script>` + 调用 `PedagogyRules.validate(summary, level)`
+- 数据源：L1 词库 147 词（过滤 enabled=true）、L2 词库 52 词、L1 句型 8 个、L2 句型（从 437MB bitable 导出中提取唯一结构）
+- 技术注意：L2_pattern_list.json 体积 437MB（1,082,450 条记录），直接嵌入前端不可行，已提取唯一句型结构后嵌入
+- 所有 6 个测试用例通过
+- 用户后续想尝试其他对接方式（API 模式 / 飞书 Bot 联动 / CI 集成）

output/sample_questions/01_reading_pic_makeWord.json

@@ -1,7 +1,7 @@
 {
   "category": "reading",
   "type": "reading_pic_makeWord",
-  "questionSetID": "020301",
+  "questionSetID": "110199",
   "textTitle": "Look at the pictures. Look at the letters. Write the word.",
   "questionSet": [
     {

output/sample_questions/02_reading_word_definition.json

@@ -1,7 +1,7 @@
 {
   "category": "reading",
   "type": "reading_word_definition",
-  "questionSetID": "030501",
+  "questionSetID": "110199",
   "textTitle": "Look and read. Choose the correct words and write them on the lines.",
   "questionSet": [
     {

output/sample_questions/03_writing_pic_faq.json

@@ -1,7 +1,7 @@
 {
   "category": "writing",
   "type": "writing_pic_faq",
-  "questionSetID": "021601",
+  "questionSetID": "110199",
   "textDesc": "Look and write.",
   "textImage": "021601.png",
   "imageDesc": "A park scene: a boy is riding a bike, a girl in a black skirt is reading a book under a tree, a dog is running near the flowers, and there is a red ball on the grass.",

output/sample_questions/04_listening_listenWrite.json

@@ -1,33 +1,43 @@
 {
   "category": "listening",
   "type": "listening_listenWrite",
-  "questionSetID": "110901",
+  "questionSetID": "110199",
   "textTitle": "Read the question. Listen and write a name or a number.",
-  "textAudio": "110901.mp3",
-  "textImage": "110901.png",
+  "textAudio": "110199.mp3",
+  "textImage": "110199.png",
   "textDesc": "There are two examples. Listen and write.",
   "questionSet": [
     {
       "question": "What is the girl's name?",
-      "answerText": "Lucy"
+      "answerText": "Lucy",
+      "ability": ["显性细节理解｜数字/时间/地点"],
+      "explanation": "音频中介绍女孩时说 'My name is Lucy'，直接抓取姓名的关键词即可。注意人名首字母大写。"
     },
     {
       "question": "How old is she?",
-      "answerText": "8"
+      "answerText": "8",
+      "ability": ["显性细节理解｜数字/时间/地点"],
+      "explanation": "音频中女孩提到 'I am eight years old'，直接抓取年龄数字即可。注意用阿拉伯数字作答。"
     },
     {
       "question": "What is the name of her dog?",
-      "questionDesc": "Her dog is called (4).",
-      "answerText": "Max"
+      "questionDesc": "Her dog is called (3).",
+      "answerText": "Max",
+      "ability": ["显性细节理解｜数字/时间/地点"],
+      "explanation": "音频中提到 'My dog is called Max'，从对话中抓取狗的名字。注意人名首字母大写。"
     },
     {
       "question": "Where does she live?",
       "questionDesc": "She lives in (5) Street.",
-      "answerText": "Green"
+      "answerText": "Green",
+      "ability": ["显性细节理解｜数字/时间/地点"],
+      "explanation": "音频中提到 'I live in Green Street'，抓取街道名称。注意首字母大写。"
     },
     {
       "question": "What number is her house?",
-      "answerText": "12"
+      "answerText": "12",
+      "ability": ["显性细节理解｜数字/时间/地点"],
+      "explanation": "音频中提到 'My house number is twelve'，抓取门牌号即可。注意用阿拉伯数字作答。"
     }
   ]
 }

output/sample_questions/05_reading_select_cloze_noPic.json

@@ -1,42 +1,43 @@
 {
   "category": "reading",
   "type": "reading_select_cloze",
-  "questionSetID": "050401",
+  "questionSetID": "110199",
   "textTitle": "Look and read. Choose the correct words and write them on the lines.",
+  "textImage": "110199.png",
   "questionSet": [
     {
       "question": "Michael: Hi Sally, I didn't see you at school yesterday. Where were you?",
       "questionDesc": "Sally: (0).",
       "answer": [1],
-      "ability": ["上下文理解", "对话逻辑", "语义推断"],
+      "ability": ["对话理解｜问答匹配"],
       "explanation": "Michael问Sally昨天为什么没来学校，Sally的回答应该解释原因。'I was feeling sick so I stayed in bed'恰好解释了缺席原因，符合对话逻辑。"
     },
     {
       "question": "Michael: Oh no! What was the matter? Did you have a sore head?",
       "questionDesc": "Sally: (0).",
       "answer": [4],
-      "ability": ["上下文理解", "对话逻辑", "语义推断"],
+      "ability": ["对话理解｜问答匹配"],
       "explanation": "Michael问Sally是不是头疼，Sally的回答应该是否定头疼并说明实际情况。'No. I had a terrible cold but it's better now'符合这个对话逻辑。"
     },
     {
       "question": "Michael: I hate being ill.",
       "questionDesc": "Sally: (0).",
       "answer": [0],
-      "ability": ["上下文理解", "对话逻辑", "语义推断"],
+      "ability": ["对话理解｜问答匹配"],
       "explanation": "Michael说讨厌生病，Sally表示同感。'So do I! It's horrible!'表达相同的感受，符合上下文。"
     },
     {
       "question": "Michael: In our English lesson, we had to answer some questions about a story.",
       "questionDesc": "Sally: (0).",
       "answer": [2],
-      "ability": ["上下文理解", "对话逻辑", "语义推断"],
+      "ability": ["对话理解｜问答匹配"],
       "explanation": "Michael说英语课上回答了问题，Sally回应自己的情况。'Did you? I just watched TV all day'使用反问+自述的方式，符合对话自然过渡。"
     },
     {
       "question": "Sally: Do you have a lot of homework?",
       "questionDesc": "Michael: (0).",
       "answer": [5],
-      "ability": ["上下文理解", "对话逻辑", "语义推断"],
+      "ability": ["对话理解｜问答匹配"],
       "explanation": "Sally问作业多不多，Michael回答关于作业的数量。'A few, I hope you'll enjoy them'带有幽默感，符合小学生对话风格。"
     }
   ],

output/sample_questions/06_reading_select_cloze_withPic.json

@@ -1,7 +1,7 @@
 {
   "category": "reading",
   "type": "reading_select_cloze",
-  "questionSetID": "050402",
+  "questionSetID": "110199",
   "textTitle": "Look and read. Choose the correct words and write them on the lines.",
   "textImage": "050402.png",
   "imageDesc": "A park scene with children playing: one boy is flying a kite, a girl is sitting on a blanket eating a sandwich, and a dog is running after a ball.",