play_chat_field

# Dataset Card for play_chat_field

This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).

## Using this dataset with Argilla

To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.Dataset.from_hub("burtenshaw/play_chat_field")
```

This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.

## Using this dataset with `datasets`

To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

ds = load_dataset("burtenshaw/play_chat_field")
```

This will only load the records of the dataset, but not the Argilla settings.

## Dataset Structure

This dataset repo contains:

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.

The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.

### Fields

The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| chat | chat | chat | True | |

### Questions

The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.

| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| comment | comment | text | True | N/A | N/A |

<!-- check length of metadata properties -->

### Data Instances

An example of a dataset instance in Argilla looks as follows:

```json
{
"_server_id": "85243d10-5950-4bf3-8a02-622072d21036",
"fields": {
"chat": [
{
"content": "Hello World, how are you?",
"role": "user"
},
{
"content": "I\u0027m doing great, thank you!",
"role": "bot"
}
]
},
"id": "e76eca54-567b-46d3-84fb-970c3213bae3",
"metadata": {},
"responses": {},
"status": "pending",
"suggestions": {},
"vectors": {}
}
```

While the same record in HuggingFace `datasets` looks as follows:

```json
{
"_server_id": "85243d10-5950-4bf3-8a02-622072d21036",
"chat": [
{
"content": "Hello World, how are you?",
"role": "user"
},
{
"content": "I\u0027m doing great, thank you!",
"role": "bot"
}
],
"id": "e76eca54-567b-46d3-84fb-970c3213bae3",
"status": "pending"
}
```

### Data Splits

The dataset contains a single split, which is `train`.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation guidelines

[More Information Needed]

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]

# play_chat_field 数据集卡片

本数据集由 [Argilla (Argilla)](https://github.com/argilla-io/argilla) 开发构建。如下文所述，该数据集既可按照[通过Argilla加载](#load-with-argilla)的步骤导入至你的Argilla服务器，也可通过`datasets`库直接使用，详见[通过datasets加载](#load-with-datasets)。

## 使用Argilla加载本数据集
要通过Argilla加载，只需先执行`pip install argilla --upgrade`升级安装Argilla，随后运行如下代码：
python
import argilla as rg

ds = rg.Dataset.from_hub("burtenshaw/play_chat_field")

该操作会从数据集仓库加载配置与数据集记录，并推送至你的Argilla服务器，以供探索与标注。

## 使用datasets加载本数据集
若要通过`datasets`库加载本数据集的记录，只需先执行`pip install datasets --upgrade`升级安装`datasets`库，随后运行如下代码：
python
from datasets import load_dataset

ds = load_dataset("burtenshaw/play_chat_field")

该操作仅会加载数据集的记录，不会加载Argilla相关配置。

## 数据集结构
本数据集仓库包含以下内容：
* 兼容Hugging Face`datasets`库格式的数据集记录。使用`rg.Dataset.from_hub`时会自动加载此类记录，也可通过`datasets`库的`load_dataset`函数独立加载。
* 用于构建与整理数据集的[标注指南](#annotation-guidelines)（若已在Argilla中定义）。
* 符合Argilla数据集格式的`.argilla`数据集配置文件夹。

本数据集在Argilla中通过**字段（fields）**、**问题（questions）**、**建议（suggestions）**、**元数据（metadata）**、**向量（vectors）**以及**指南（guidelines）**构建。

### 字段（Fields）
**字段**即数据集记录的特征或文本内容。例如文本分类数据集的`text`列，或指令跟随数据集的`prompt`列。

| 字段名 | 标题 | 类型 | 是否必填 | 是否支持Markdown |
| ------ | ---- | ---- | -------- | ---------------- |
| chat | chat | chat | 是 | 否 |

### 问题（Questions）
**问题**即向标注人员提出的查询内容，支持多种类型，包括评分、文本、标签选择、多标签选择以及排序。

| 问题名 | 标题 | 类型 | 是否必填 | 描述 | 可选值/标签 |
| ------ | ---- | ---- | -------- | ---- | ----------- |
| comment | comment | text | 是 | 无 | 无 |

### 数据实例
Argilla中的数据集记录示例如下：
json
{
"_server_id": "85243d10-5950-4bf3-8a02-622072d21036",
"fields": {
"chat": [
{
"content": "Hello World, how are you?",
"role": "user"
},
{
"content": "I'm doing great, thank you!",
"role": "bot"
}
]
},
"id": "e76eca54-567b-46d3-84fb-970c3213bae3",
"metadata": {},
"responses": {},
"status": "pending",
"suggestions": {},
"vectors": {}
}

而在Hugging Face`datasets`库中的同一记录格式如下：
json
{
"_server_id": "85243d10-5950-4bf3-8a02-622072d21036",
"chat": [
{
"content": "Hello World, how are you?",
"role": "user"
},
{
"content": "I'm doing great, thank you!",
"role": "bot"
}
],
"id": "e76eca54-567b-46d3-84fb-970c3213bae3",
"status": "pending"
}

### 数据划分
本数据集仅包含一个划分，即`train`（训练集）。

## 数据集创建
### 整理初衷
[需补充更多信息]
### 源数据
#### 初始数据收集与标准化处理
[需补充更多信息]
#### 源语言生成者
[需补充更多信息]
### 标注信息
#### 标注指南
[需补充更多信息]
#### 标注流程
[需补充更多信息]
#### 标注人员
[需补充更多信息]
### 个人与敏感信息
[需补充更多信息]

## 数据使用注意事项
### 数据集的社会影响
[需补充更多信息]
### 偏差讨论
[需补充更多信息]
### 其他已知局限
[需补充更多信息]

## 附加信息
### 数据集整理者
[需补充更多信息]
### 许可信息
[需补充更多信息]
### 引用信息
[需补充更多信息]
### 贡献内容
[需补充更多信息]