Datasets:
Update README.md
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README.md
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@@ -38,10 +38,64 @@ The CCR_Bench data are only available in Chinese.
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## Dataset Structure
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### Data Instances
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An example of
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```
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{
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"idx": 0,
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@@ -79,6 +133,14 @@ An example of the `train` split looks as follows:
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### Data Fields
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The data fields on industry_senario_application are as follows:
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* `idx`: A unique ID for the prompt.
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* `type`: Describes the task type of the data.
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## Dataset Structure
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### Data File
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There are three files in the root directory: complex_content_format_constraint, logical_workflow_control, and industry_scenario_application, corresponding to the test data for the three aforementioned scenarios.
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Among these, both complex_content_format_constraint and industry_scenario_application directory contain only a single file each, namely the test data in JSONL format.
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The logical_workflow_control directory, however, has a more complex structure. Within its folder, there are two subdirectories: resources and scenarios.
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* The resources folder contains additional reference information required by the model for three scenarios: World Cup, Maze, and Print Trees.
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* The scenarios folder stores flowcharts, user dialogue templates, and notes for each respective scenario.
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### Data Instances
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An example of logical_workflow_control looks as follows:
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```
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{
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"idx": 1,
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"language": "zh",
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"scenario": "data_flow",
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"user_targets": [
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"用户发现自己手机最近流量用的很快,怀疑是不是流量超套了。[话术:我突然发现最近手机流量用的特别快,是不是超套了?]",
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"当智能助手告知流量未超套时,用户对此提出质疑。[话术:不对,我手机软件上明明显示流量已经超套,这是怎么回事?]"
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],
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"extra_info": [
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"用户的手机号是13800000002,服务密码是234567"
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],
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"possible_function_calls": [
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{
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"name": "verify_user_info",
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"arguments": {
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"phone_number": "13800000002",
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"password": "234567"
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}
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},
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{
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"name": "query_exceeded_data_usage",
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"arguments": {
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"phone_number": "13800000002"
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}
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},
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{
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"name": "query_data_usage",
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"arguments": {
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"phone_number": "13800000002"
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}
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},
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{
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"name": "human_service",
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"arguments": {
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}
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}
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]
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}
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```
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An example of the industry_senario_application looks as follows:
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```
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{
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"idx": 0,
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### Data Fields
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The data fields on logical_workflow_control are as follows:
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* `idx`: A unique ID for the prompt.
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* `language`: Describes the language of the data.
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* `senario`: Describes the senario the data.
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* `user_targets`: Describes the task the model should perform.
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* `extra_info`: Describes the extra_info the model can reference during the response.
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* `possible_function_calls`: Describes the possible function calls the model perform the prompt.
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The data fields on industry_senario_application are as follows:
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* `idx`: A unique ID for the prompt.
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* `type`: Describes the task type of the data.
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