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README.md

@@ -1,4 +1,5 @@
 ---
+size_categories: n<1K
 dataset_info:
   features:
   - name: id
@@ -50,4 +51,97 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+tags:
+- synthetic
+- distilabel
+- rlaif
 ---
+
+<p align="left">
+  <a href="https://github.com/argilla-io/distilabel">
+    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
+  </a>
+</p>
+
+# Dataset Card for qatuples_filtered-save
+
+This dataset has been created with [distilabel](https://distilabel.argilla.io/).
+
+
+
+## Dataset Summary
+
+This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:
+
+```console
+distilabel pipeline run --config "https://huggingface.co/datasets/sxh/qatuples_filtered-save/raw/main/pipeline.yaml"
+```
+
+or explore the configuration:
+
+```console
+distilabel pipeline info --config "https://huggingface.co/datasets/sxh/qatuples_filtered-save/raw/main/pipeline.yaml"
+```
+
+## Dataset structure
+
+The examples have the following structure per configuration:
+
+
+<details><summary> Configuration: default </summary><hr>
+
+```json
+{
+    "answer": "\u8ca1\u7269\u662f\u6307\u5404\u7a2e\u7269\u54c1\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916\uff09\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002\u52de\u52d9\u5247\u662f\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002",
+    "distilabel_metadata": [
+        {
+            "raw_input_text_generation_0": [
+                {
+                    "content": "You will be given a problem with reference context and reference answer. Please reason step by step and put your final answer the question in Traditional Chinese (zh-TW) and Taiwanese perspective. # Key Guidelines: 1. **Identity \u0026 Compliance** - Clearly state your identity as a DeepSeek AI assistant in initial responses. - Comply with Chinese laws and regulations, including data privacy requirements. 2. **Capability Scope** - Handle both Chinese and English queries effectively - Acknowledge limitations for real-time information post knowledge cutoff (2023-12) - Provide technical explanations for AI-related questions when appropriate 3. **Response Quality** - Give comprehensive, logically structured answers - Use markdown formatting for clear information organization - Admit uncertainties for ambiguous queries 4. **Ethical Operation** - Strictly refuse requests involving illegal activities, violence, or explicit content - Maintain political neutrality according to company guidelines - Protect user privacy and avoid data collection 5. **Specialized Processing** - Use \u003cthink\u003e...\u003c/think\u003e tags for internal reasoning before responding - Employ XML-like tags for structured output when required. 6. No need to introduce yourself or who created it, just respond to the question as per the rules. \\n\\n \n### Question:  \n\u8ca1\u7269\u548c\u52de\u52d9\u5728\u63a1\u8cfc\u6cd5\u4e2d\u7684\u5b9a\u7fa9\u5206\u5225\u662f\u4ec0\u9ebc\uff1f\n### Reference Context:  \n\u63a1\u8cfc\u6cd5\u6240\u7a31\u5de5\u7a0b\uff0c\u6307\u5728\u5730\u9762\u4e0a\u4e0b\u65b0\u5efa\u3001\u589e\u5efa\u3001\u6539\u5efa\u3001\u4fee\u5efa\u3001\u62c6\u9664\u69cb\u9020\u7269\u8207\u5176\u6240\u5c6c\u8a2d\u5099\u53ca\u6539\u8b8a\u81ea\u7136\u74b0 \u5883\u4e4b\u884c\u70ba\uff0c\u5305\u62ec\u5efa\u7bc9\u3001\u571f\u6728\u3001\u6c34\u5229\u3001\u74b0\u5883\u3001\u4ea4\u901a\u3001\u6a5f\u68b0\u3001\u96fb\u6c23\u3001\u5316\u5de5\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u5de5 \u7a0b\u3002 \u8ca1\u7269\uff0c\u6307\u5404\u7a2e\u7269\u54c1(\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916)\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b \u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002 \u52de\u52d9\uff0c\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1 \u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002 \u63a1\u8cfc\u517c\u6709\u5de5\u7a0b\u3001\u8ca1\u7269\u3001\u52de\u52d9\u4e8c\u7a2e\u4ee5\u4e0a\u6027\u8cea\uff0c\u96e3\u4ee5\u8a8d\u5b9a\u5176\u6b78\u5c6c\u8005\uff0c\u6309\u5176\u6027\u8cea\u6240\u5360\u9810\u7b97\u91d1\u984d\u6bd4\u7387\u6700\u9ad8\u8005 \u6b78\u5c6c\u4e4b\u3002\n### Reference Answer:  \n\u8ca1\u7269\u662f\u6307\u5404\u7a2e\u7269\u54c1\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916\uff09\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002\u52de\u52d9\u5247\u662f\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002\n",
+                    "role": "user"
+                }
+            ],
+            "raw_output_text_generation_0": "\u003cthink\u003e\n\n\u6839\u64da\u300a\u653f\u5e9c\u63a1\u8cfc\u6cd5\u300b\u7684\u5b9a\u7fa9\uff0c\u8ca1\u7269\u8207\u52de\u52d9\u7684\u754c\u5b9a\u5728\u5be6\u52d9\u64cd\u4f5c\u4e2d\u5177\u6709\u660e\u78ba\u5340\u5206\u3002\u9996\u5148\u9700\u91d0\u6e05\u8ca1\u7269\u5b9a\u7fa9\u4e2d\u7684\u6392\u9664\u9805\u76ee\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\uff09\uff0c\u6b64\u9650\u5236\u6e90\u81ea\u63a1\u8cfc\u6cd5\u5c0d\u7279\u6b8a\u5546\u54c1\u7ba1\u5236\u7684\u7acb\u6cd5\u8003\u91cf\u3002\u5c0d\u65bc\u4e0d\u52d5\u7522\u63a1\u8cfc\u7684\u5be6\u52d9\u61c9\u7528\uff0c\u61c9\u6ce8\u610f\u5176\u6b0a\u5229\u79fb\u8f49\u7a0b\u5e8f\u8207\u52d5\u7522\u63a1\u8cfc\u4e4b\u5dee\u7570\u6027\u3002\n\n\u52de\u52d9\u63a1\u8cfc\u7bc4\u7587\u6db5\u84cb\u5c08\u696d\u6280\u8853\u8207\u4eba\u529b\u670d\u52d9\u5169\u5927\u9762\u5411\uff0c\u5176\u4e2d\u300c\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u300d\u689d\u6b3e\u8ce6\u4e88\u884c\u653f\u6a5f\u95dc\u88c1\u91cf\u6b0a\uff0c\u6b64\u90e8\u5206\u9700\u53c3\u7167\u884c\u653f\u51fd\u91cb\u88dc\u5145\u89e3\u91cb\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u7814\u7a76\u767c\u5c55\u985e\u52de\u52d9\u63a1\u8cfc\u6d89\u53ca\u667a\u8ca1\u6b0a\u6b78\u5c6c\u554f\u984c\uff0c\u5951\u7d04\u689d\u6b3e\u9700\u7279\u5225\u898f\u7bc4\u3002\n\n\u5728\u6df7\u5408\u578b\u63a1\u8cfc\u6848\u4ef6\u8655\u7406\u4e0a\uff0c\u9810\u7b97\u91d1\u984d\u6bd4\u4f8b\u8a08\u7b97\u65b9\u5f0f\u5c07\u5f71\u97ff\u6b78\u985e\u5224\u5b9a\uff0c\u6a5f\u95dc\u61c9\u5efa\u7acb\u5167\u90e8\u5be9\u67e5\u6a5f\u5236\u4ee5\u907f\u514d\u722d\u8b70\u3002\u6b64\u5916\uff0c\u53f0\u7063\u5be6\u52d9\u5e38\u898b\u722d\u8b70\u5728\u65bc\u8edf\u9ad4\u958b\u767c\u5c6c\u65bc\u8ca1\u7269\uff08\u5957\u88dd\u8edf\u9ad4\uff09\u6216\u52de\u52d9\uff08\u5ba2\u88fd\u5316\u958b\u767c\uff09\uff0c\u6b64\u9700\u4f9d\u500b\u6848\u6027\u8cea\u5224\u65b7\uff0c\u5fc5\u8981\u6642\u5f97\u8aee\u8a62\u5de5\u7a0b\u6703\u898b\u89e3\u3002\n\u003c/think\u003e\n\n\u6839\u64da\u300a\u653f\u5e9c\u63a1\u8cfc\u6cd5\u300b\u898f\u5b9a\uff1a\n\n**\u8ca1\u7269**\u7684\u5b9a\u7fa9\u5305\u542b\uff1a\n\uffed \u5404\u7a2e\u7269\u54c1\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916\uff09\n\uffed \u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\n\uffed \u52d5\u7522\u3001\u4e0d\u52d5\u7522\n\uffed \u6b0a\u5229\uff08\u5982\u5c08\u5229\u6b0a\u3001\u8457\u4f5c\u6b0a\u7b49\uff09\n\uffed \u5176\u4ed6\u7d93\u884c\u653f\u9662\u516c\u5171\u5de5\u7a0b\u59d4\u54e1\u6703\u8a8d\u5b9a\u9805\u76ee\n\n**\u52de\u52d9**\u7684\u5b9a\u7fa9\u6db5\u84cb\uff1a\n\uffed \u5c08\u696d/\u6280\u8853/\u8cc7\u8a0a\u670d\u52d9\uff08\u5982\u6cd5\u5f8b\u8aee\u8a62\u3001\u5de5\u7a0b\u8a2d\u8a08\uff09\n\uffed \u7814\u7a76\u767c\u5c55\u8207\u71df\u904b\u7ba1\u7406\n\uffed \u8a2d\u5099\u7dad\u4fee\u8207\u4eba\u529b\u57f9\u8a13\n\uffed \u9ad4\u529b\u52de\u52d5\u670d\u52d9\n\uffed \u5176\u4ed6\u7d93\u5de5\u7a0b\u6703\u8a8d\u5b9a\u4e4b\u670d\u52d9\u985e\u5225\n\n\u53f0\u7063\u5be6\u52d9\u61c9\u7528\u6ce8\u610f\u4e8b\u9805\uff1a\n1. \u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u63a1\u8cfc\u9069\u7528\u300a\u8fb2\u7522\u54c1\u5e02\u5834\u4ea4\u6613\u6cd5\u300b\n2. \u4e0d\u52d5\u7522\u63a1\u8cfc\u9700\u7b26\u5408\u300a\u570b\u6709\u8ca1\u7522\u6cd5\u300b\u76f8\u95dc\u898f\u5b9a\n3. \u6b0a\u5229\u63a1\u8cfc\u61c9\u6ce8\u610f\u667a\u8ca1\u6b0a\u6b78\u5c6c\u5951\u7d04\u689d\u6b3e\n4. \u52de\u52d9\u63a1\u8cfc\u6848\u5e38\u898b\u722d\u8b70\u9ede\u5728\u300c\u670d\u52d9\u6210\u679c\u8a8d\u5b9a\u6a19\u6e96\u300d\uff0c\u5efa\u8b70\u62db\u6a19\u6587\u4ef6\u9700\u660e\u78ba\u5b9a\u7fa9\u9a57\u6536\u898f\u7bc4",
+            "statistics_text_generation_0": {
+                "input_tokens": 533,
+                "output_tokens": 479
+            }
+        }
+    ],
+    "generation": [
+        "\u003cthink\u003e\n\n\u6839\u64da\u300a\u653f\u5e9c\u63a1\u8cfc\u6cd5\u300b\u7684\u5b9a\u7fa9\uff0c\u8ca1\u7269\u8207\u52de\u52d9\u7684\u754c\u5b9a\u5728\u5be6\u52d9\u64cd\u4f5c\u4e2d\u5177\u6709\u660e\u78ba\u5340\u5206\u3002\u9996\u5148\u9700\u91d0\u6e05\u8ca1\u7269\u5b9a\u7fa9\u4e2d\u7684\u6392\u9664\u9805\u76ee\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\uff09\uff0c\u6b64\u9650\u5236\u6e90\u81ea\u63a1\u8cfc\u6cd5\u5c0d\u7279\u6b8a\u5546\u54c1\u7ba1\u5236\u7684\u7acb\u6cd5\u8003\u91cf\u3002\u5c0d\u65bc\u4e0d\u52d5\u7522\u63a1\u8cfc\u7684\u5be6\u52d9\u61c9\u7528\uff0c\u61c9\u6ce8\u610f\u5176\u6b0a\u5229\u79fb\u8f49\u7a0b\u5e8f\u8207\u52d5\u7522\u63a1\u8cfc\u4e4b\u5dee\u7570\u6027\u3002\n\n\u52de\u52d9\u63a1\u8cfc\u7bc4\u7587\u6db5\u84cb\u5c08\u696d\u6280\u8853\u8207\u4eba\u529b\u670d\u52d9\u5169\u5927\u9762\u5411\uff0c\u5176\u4e2d\u300c\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u300d\u689d\u6b3e\u8ce6\u4e88\u884c\u653f\u6a5f\u95dc\u88c1\u91cf\u6b0a\uff0c\u6b64\u90e8\u5206\u9700\u53c3\u7167\u884c\u653f\u51fd\u91cb\u88dc\u5145\u89e3\u91cb\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u7814\u7a76\u767c\u5c55\u985e\u52de\u52d9\u63a1\u8cfc\u6d89\u53ca\u667a\u8ca1\u6b0a\u6b78\u5c6c\u554f\u984c\uff0c\u5951\u7d04\u689d\u6b3e\u9700\u7279\u5225\u898f\u7bc4\u3002\n\n\u5728\u6df7\u5408\u578b\u63a1\u8cfc\u6848\u4ef6\u8655\u7406\u4e0a\uff0c\u9810\u7b97\u91d1\u984d\u6bd4\u4f8b\u8a08\u7b97\u65b9\u5f0f\u5c07\u5f71\u97ff\u6b78\u985e\u5224\u5b9a\uff0c\u6a5f\u95dc\u61c9\u5efa\u7acb\u5167\u90e8\u5be9\u67e5\u6a5f\u5236\u4ee5\u907f\u514d\u722d\u8b70\u3002\u6b64\u5916\uff0c\u53f0\u7063\u5be6\u52d9\u5e38\u898b\u722d\u8b70\u5728\u65bc\u8edf\u9ad4\u958b\u767c\u5c6c\u65bc\u8ca1\u7269\uff08\u5957\u88dd\u8edf\u9ad4\uff09\u6216\u52de\u52d9\uff08\u5ba2\u88fd\u5316\u958b\u767c\uff09\uff0c\u6b64\u9700\u4f9d\u500b\u6848\u6027\u8cea\u5224\u65b7\uff0c\u5fc5\u8981\u6642\u5f97\u8aee\u8a62\u5de5\u7a0b\u6703\u898b\u89e3\u3002\n\u003c/think\u003e\n\n\u6839\u64da\u300a\u653f\u5e9c\u63a1\u8cfc\u6cd5\u300b\u898f\u5b9a\uff1a\n\n**\u8ca1\u7269**\u7684\u5b9a\u7fa9\u5305\u542b\uff1a\n\uffed \u5404\u7a2e\u7269\u54c1\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916\uff09\n\uffed \u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\n\uffed \u52d5\u7522\u3001\u4e0d\u52d5\u7522\n\uffed \u6b0a\u5229\uff08\u5982\u5c08\u5229\u6b0a\u3001\u8457\u4f5c\u6b0a\u7b49\uff09\n\uffed \u5176\u4ed6\u7d93\u884c\u653f\u9662\u516c\u5171\u5de5\u7a0b\u59d4\u54e1\u6703\u8a8d\u5b9a\u9805\u76ee\n\n**\u52de\u52d9**\u7684\u5b9a\u7fa9\u6db5\u84cb\uff1a\n\uffed \u5c08\u696d/\u6280\u8853/\u8cc7\u8a0a\u670d\u52d9\uff08\u5982\u6cd5\u5f8b\u8aee\u8a62\u3001\u5de5\u7a0b\u8a2d\u8a08\uff09\n\uffed \u7814\u7a76\u767c\u5c55\u8207\u71df\u904b\u7ba1\u7406\n\uffed \u8a2d\u5099\u7dad\u4fee\u8207\u4eba\u529b\u57f9\u8a13\n\uffed \u9ad4\u529b\u52de\u52d5\u670d\u52d9\n\uffed \u5176\u4ed6\u7d93\u5de5\u7a0b\u6703\u8a8d\u5b9a\u4e4b\u670d\u52d9\u985e\u5225\n\n\u53f0\u7063\u5be6\u52d9\u61c9\u7528\u6ce8\u610f\u4e8b\u9805\uff1a\n1. \u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u63a1\u8cfc\u9069\u7528\u300a\u8fb2\u7522\u54c1\u5e02\u5834\u4ea4\u6613\u6cd5\u300b\n2. \u4e0d\u52d5\u7522\u63a1\u8cfc\u9700\u7b26\u5408\u300a\u570b\u6709\u8ca1\u7522\u6cd5\u300b\u76f8\u95dc\u898f\u5b9a\n3. \u6b0a\u5229\u63a1\u8cfc\u61c9\u6ce8\u610f\u667a\u8ca1\u6b0a\u6b78\u5c6c\u5951\u7d04\u689d\u6b3e\n4. \u52de\u52d9\u63a1\u8cfc\u6848\u5e38\u898b\u722d\u8b70\u9ede\u5728\u300c\u670d\u52d9\u6210\u679c\u8a8d\u5b9a\u6a19\u6e96\u300d\uff0c\u5efa\u8b70\u62db\u6a19\u6587\u4ef6\u9700\u660e\u78ba\u5b9a\u7fa9\u9a57\u6536\u898f\u7bc4"
+    ],
+    "id": 1,
+    "metadata": "\u570b\u68df\u7267\u5834\u7269\u806f\u7db2\u63a7\u5236\u7cfb\u7d71_\u898f\u683c\u66f8v5",
+    "model_name": "DeepSeek-R1",
+    "paragraph": "\u63a1\u8cfc\u6cd5\u6240\u7a31\u5de5\u7a0b\uff0c\u6307\u5728\u5730\u9762\u4e0a\u4e0b\u65b0\u5efa\u3001\u589e\u5efa\u3001\u6539\u5efa\u3001\u4fee\u5efa\u3001\u62c6\u9664\u69cb\u9020\u7269\u8207\u5176\u6240\u5c6c\u8a2d\u5099\u53ca\u6539\u8b8a\u81ea\u7136\u74b0 \u5883\u4e4b\u884c\u70ba\uff0c\u5305\u62ec\u5efa\u7bc9\u3001\u571f\u6728\u3001\u6c34\u5229\u3001\u74b0\u5883\u3001\u4ea4\u901a\u3001\u6a5f\u68b0\u3001\u96fb\u6c23\u3001\u5316\u5de5\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u5de5 \u7a0b\u3002 \u8ca1\u7269\uff0c\u6307\u5404\u7a2e\u7269\u54c1(\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916)\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b \u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002 \u52de\u52d9\uff0c\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1 \u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002 \u63a1\u8cfc\u517c\u6709\u5de5\u7a0b\u3001\u8ca1\u7269\u3001\u52de\u52d9\u4e8c\u7a2e\u4ee5\u4e0a\u6027\u8cea\uff0c\u96e3\u4ee5\u8a8d\u5b9a\u5176\u6b78\u5c6c\u8005\uff0c\u6309\u5176\u6027\u8cea\u6240\u5360\u9810\u7b97\u91d1\u984d\u6bd4\u7387\u6700\u9ad8\u8005 \u6b78\u5c6c\u4e4b\u3002",
+    "paragraph_idx": 0,
+    "prompt": "\n### Question:  \n\u8ca1\u7269\u548c\u52de\u52d9\u5728\u63a1\u8cfc\u6cd5\u4e2d\u7684\u5b9a\u7fa9\u5206\u5225\u662f\u4ec0\u9ebc\uff1f\n### Reference Context:  \n\u63a1\u8cfc\u6cd5\u6240\u7a31\u5de5\u7a0b\uff0c\u6307\u5728\u5730\u9762\u4e0a\u4e0b\u65b0\u5efa\u3001\u589e\u5efa\u3001\u6539\u5efa\u3001\u4fee\u5efa\u3001\u62c6\u9664\u69cb\u9020\u7269\u8207\u5176\u6240\u5c6c\u8a2d\u5099\u53ca\u6539\u8b8a\u81ea\u7136\u74b0 \u5883\u4e4b\u884c\u70ba\uff0c\u5305\u62ec\u5efa\u7bc9\u3001\u571f\u6728\u3001\u6c34\u5229\u3001\u74b0\u5883\u3001\u4ea4\u901a\u3001\u6a5f\u68b0\u3001\u96fb\u6c23\u3001\u5316\u5de5\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u5de5 \u7a0b\u3002 \u8ca1\u7269\uff0c\u6307\u5404\u7a2e\u7269\u54c1(\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916)\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b \u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002 \u52de\u52d9\uff0c\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1 \u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002 \u63a1\u8cfc\u517c\u6709\u5de5\u7a0b\u3001\u8ca1\u7269\u3001\u52de\u52d9\u4e8c\u7a2e\u4ee5\u4e0a\u6027\u8cea\uff0c\u96e3\u4ee5\u8a8d\u5b9a\u5176\u6b78\u5c6c\u8005\uff0c\u6309\u5176\u6027\u8cea\u6240\u5360\u9810\u7b97\u91d1\u984d\u6bd4\u7387\u6700\u9ad8\u8005 \u6b78\u5c6c\u4e4b\u3002\n### Reference Answer:  \n\u8ca1\u7269\u662f\u6307\u5404\u7a2e\u7269\u54c1\uff08\u751f\u9bae\u8fb2\u6f01\u7522\u54c1\u9664\u5916\uff09\u3001\u6750\u6599\u3001\u8a2d\u5099\u3001\u6a5f\u5177\u8207\u5176\u4ed6\u52d5\u7522\u3001\u4e0d\u52d5\u7522\u3001\u6b0a\u5229\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u8ca1\u7269\u3002\u52de\u52d9\u5247\u662f\u6307\u5c08\u696d\u670d\u52d9\u3001\u6280\u8853\u670d\u52d9\u3001\u8cc7\u8a0a\u670d\u52d9\u3001\u7814\u7a76\u767c\u5c55\u3001\u71df\u904b\u7ba1\u7406\u3001\u7dad\u4fee\u3001\u8a13\u7df4\u3001\u52de\u529b\u53ca\u5176\u4ed6\u7d93\u4e3b\u7ba1\u6a5f\u95dc\u8a8d\u5b9a\u4e4b\u52de\u52d9\u3002\n",
+    "question": "\u8ca1\u7269\u548c\u52de\u52d9\u5728\u63a1\u8cfc\u6cd5\u4e2d\u7684\u5b9a\u7fa9\u5206\u5225\u662f\u4ec0\u9ebc\uff1f",
+    "question_group_id": "5036f45c-3c86-4e45-9a08-667088bffa44",
+    "question_idx": 2
+}
+```
+
+This subset can be loaded as:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("sxh/qatuples_filtered-save", "default")
+```
+
+Or simply as it follows, since there's only one configuration and is named `default`: 
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("sxh/qatuples_filtered-save")
+```
+
+
+</details>
+
+
+
+