@data :update

README.md

@@ -11,11 +11,16 @@ size_categories:
 - 1K<n<10K
 viewer: true
 configs:
-- config_name: default
+- config_name: en
   data_files:
   - split: test
     path:
-    - AnesBench.json
+    - anesbench_en.json
+- config_name: zh
+  data_files:
+  - split: test
+    path:
+    - anesbench_zh.json
 license: c-uda
 ---
 
@@ -23,21 +28,46 @@ The AnesBench Datasets Collection comprises three distinct datasets: AnesBench,
 
 # Dataset Description
 
-**AnesBench** is designed to assess anesthesiology-related reasoning capabilities of Large Language Models (LLMs). It contains 4,427 anesthesiology questions in English. Each question is labeled with a three-level categorization of cognitive demands and includes Chinese-English translations, enabling evaluation of LLMs’ knowledge, application, and clinical reasoning abilities across diverse linguistic contexts.
+**AnesBench** is designed to assess anesthesiology-related reasoning capabilities of Large Language Models (LLMs). It provides bilingual (English and Chinese) anesthesiology questions across two separate files. Each question is labeled with a three-level categorization of cognitive demands based on dual-process theory (System 1, System 1.x, and System 2), enabling evaluation of LLMs' knowledge, application, and clinical reasoning abilities across diverse linguistic contexts.
+
+| Subset | File | Total | System 1 | System 1.x | System 2 |
+|--------|------|-------|----------|-------------|----------|
+| English | `anesbench_en.json` | 4,343 | 2,960 | 1,028 | 355 |
+| Chinese | `anesbench_zh.json` | 3,529 | 2,784 | 534 | 211 |
 
 ## JSON Sample
 
+**English** (`anesbench_en.json`):
+
 ```json
-    {
-        "id": "1bb76e22-6dbf-5b17-bbdf-0e6cde9f9440",
-        "choice_num": 4,
-        "answer": "A",
-        "level": 1,
-        "en_question": "english question",
-        "en_X": "option X",
-        "zh_question": "中文问题",
-        "zh_X": "选项X",
-    }
+{
+    "id": "91b5e145-57f2-5307-99e4-eafd75643de4",
+    "question": "The concentration of a specific gas in solution depends on which of the following?",
+    "A": "Temperature of the solution",
+    "B": "Volume of the system",
+    "C": "Solubility of the specific gas in that solution",
+    "D": "Molecular weight of the gas",
+    "choice_num": 4,
+    "target": "C",
+    "category": 1
+}
+```
+
+**Chinese** (`anesbench_zh.json`):
+
+```json
+{
+    "A": "替代治疗",
+    "B": "手术治疗",
+    "C": "对症治疗",
+    "D": "静脉输注糖皮质激素",
+    "E": "补充盐皮质激素",
+    "id": "78587bd9-f3f6-4118-b6eb-95ed7c91a0ec",
+    "question": "Addison病抢救的主要措施是",
+    "choice_num": 5,
+    "target": "D",
+    "category": 1
+}
 ```
 
 ## Field Explanations
@@ -45,15 +75,20 @@ The AnesBench Datasets Collection comprises three distinct datasets: AnesBench,
 | Field         | Type   | Description                                                                 |
 |------------------|----------|-----------------------------------------------------------------------------|
 | `id`             | string   | A randomly generated ID using UUID                                          |
+| `question`       | string   | The question stem                                                           |
+| `A`–`I`          | string   | Answer options (from `A` up to the total number of options)                 |
 | `choice_num`     | int      | The number of options in this question                                      |
-| `answer`         | string   | The correct answer to this question                                         |
-| `level`          | int      | The cognitive demand level of the question (`1`, `2`, and `3` represent `system1`, `system1.x`, and `system2` respectively) |
-| `en_question`    | string   | English description of the question stem                                   |
-| `cn_question`    | string   | Chinese description of the question stem                                   |
-| `en_X`           | string   | English description of the option (X takes values from A until the total number of options is reached)                                         |
-| `cn_X`           | string   | Chinese description of the option (X takes values from A until the total number of options is reached)                                         |
+| `target`         | string   | The correct answer to this question                                         |
+| `category`       | int      | The cognitive demand category of the question (`1` = System 1, `2` = System 1.x, `3` = System 2) |
+
+### Cognitive Demand Categories
 
+| Category | Label | Description |
+|----------|-------|-------------|
+| 1 | **System 1** | Fast, intuitive recall of factual knowledge |
+| 2 | **System 1.x** | Pattern recognition and application of learned rules |
+| 3 | **System 2** | Deliberate, analytical clinical reasoning |
 
 ## Recommended Usage
 
-- **Question Answering**: QA in a zero-shot or few-shot setting, where the question is fed into a QA system. Accuracy should be used as the evaluation metric.
+- **Question Answering**: QA in a zero-shot or few-shot setting, where the question is fed into a QA system. Accuracy should be used as the evaluation metric.