MPEP_ARABIC

# Dataset Card for MPEP_ARABIC

This dataset has been created with [Argilla](https://docs.argilla.io).

As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).

## Dataset Description

- **Homepage:** https://argilla.io
- **Repository:** https://github.com/argilla-io/argilla
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

This dataset contains:

* A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla.

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` 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.

### Load 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.FeedbackDataset.from_huggingface("DIBT/MPEP_ARABIC")
```

### Load with `datasets`

To load 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("DIBT/MPEP_ARABIC")
```

### Supported Tasks and Leaderboards

This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure).

There are no leaderboards associated with this dataset.

### Languages

[More Information Needed]

## Dataset Structure

### Data in Argilla

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

The **fields** are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| source | Source | text | True | True |

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 |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| target | Target | text | True | Translate the text. | N/A |

The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".

The **metadata** is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.

| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |

The **guidelines**, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section.

### Data Instances

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

```json
{
"external_id": null,
"fields": {
"source": "If a recipe calls for 2 1/2 cups of sugar and you want to make a half portion of it, calculate the exact amount of sugar needed."
},
"metadata": {
"evolved_from": null,
"kind": "synthetic",
"source": "argilla/distilabel-reasoning-prompts"
},
"responses": [
{
"status": "submitted",
"user_id": "6e3edb87-0ccc-47ef-bd61-3ed0e68b20de",
"values": {
"target": {
"value": "\u0625\u0630\u0627 \u0643\u0627\u0646\u062a \u0627\u0644\u0648\u0635\u0641\u0629 \u062a\u062a\u0637\u0644\u0628 \u0643\u0648\u0628\u064a\u0646 \u0648\u0646\u0635\u0641 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0648\u062a\u0631\u064a\u062f \u062a\u062d\u0636\u064a\u0631 \u0646\u0635\u0641 \u0647\u0630\u0647 \u0627\u0644\u0643\u0645\u064a\u0629\u060c \u0641\u0627\u062d\u0633\u0628 \u0643\u0645\u064a\u0629 \u0627\u0644\u0633\u0643\u0631 \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629 \u0628\u0627\u0644\u0636\u0628\u0637."
}
}
}
],
"suggestions": [
{
"agent": null,
"question_name": "target",
"score": null,
"type": null,
"value": "\u0625\u0630\u0627 \u0643\u0627\u0646\u062a \u0627\u0644\u0648\u0635\u0641\u0629 \u062a\u062a\u0637\u0644\u0628 \u0643\u0648\u0628\u064a\u0646 \u0648\u0646\u0635\u0641 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0648\u062a\u0631\u064a\u062f \u062a\u062d\u0636\u064a\u0631 \u0646\u0635\u0641 \u0627\u0644\u0643\u0645\u064a\u0629\u060c \u0641\u0627\u062d\u0633\u0628 \u0627\u0644\u0643\u0645\u064a\u0629 \u0627\u0644\u062f\u0642\u064a\u0642\u0629 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629."
}
],
"vectors": {}
}
```

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

```json
{
"external_id": null,
"metadata": "{\"source\": \"argilla/distilabel-reasoning-prompts\", \"kind\": \"synthetic\", \"evolved_from\": null}",
"source": "If a recipe calls for 2 1/2 cups of sugar and you want to make a half portion of it, calculate the exact amount of sugar needed.",
"target": [
{
"status": "submitted",
"user_id": "6e3edb87-0ccc-47ef-bd61-3ed0e68b20de",
"value": "\u0625\u0630\u0627 \u0643\u0627\u0646\u062a \u0627\u0644\u0648\u0635\u0641\u0629 \u062a\u062a\u0637\u0644\u0628 \u0643\u0648\u0628\u064a\u0646 \u0648\u0646\u0635\u0641 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0648\u062a\u0631\u064a\u062f \u062a\u062d\u0636\u064a\u0631 \u0646\u0635\u0641 \u0647\u0630\u0647 \u0627\u0644\u0643\u0645\u064a\u0629\u060c \u0641\u0627\u062d\u0633\u0628 \u0643\u0645\u064a\u0629 \u0627\u0644\u0633\u0643\u0631 \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629 \u0628\u0627\u0644\u0636\u0628\u0637."
}
],
"target-suggestion": "\u0625\u0630\u0627 \u0643\u0627\u0646\u062a \u0627\u0644\u0648\u0635\u0641\u0629 \u062a\u062a\u0637\u0644\u0628 \u0643\u0648\u0628\u064a\u0646 \u0648\u0646\u0635\u0641 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0648\u062a\u0631\u064a\u062f \u062a\u062d\u0636\u064a\u0631 \u0646\u0635\u0641 \u0627\u0644\u0643\u0645\u064a\u0629\u060c \u0641\u0627\u062d\u0633\u0628 \u0627\u0644\u0643\u0645\u064a\u0629 \u0627\u0644\u062f\u0642\u064a\u0642\u0629 \u0645\u0646 \u0627\u0644\u0633\u0643\u0631 \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629.",
"target-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
}
}
```

### Data Fields

Among the dataset fields, we differentiate between the following:

* **Fields:** These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.

* **source** is of type `text`.

* **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.

* **target** is of type `text`, and description "Translate the text.".

* **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.

* (optional) **target-suggestion** is of type `text`.

Additionally, we also have two more fields that are optional and are the following:

* **metadata:** This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
* **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.

### 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

This is a translation dataset that contains texts. Please translate the text in the text field.

#### 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]

# MPEP_ARABIC 数据集卡片
本数据集基于 [Argilla](https://docs.argilla.io) 构建。

如下文所述，本数据集可按照[通过 Argilla 加载](#load-with-argilla)中的说明加载至 Argilla，或直接通过 [通过 `datasets` 库加载](#load-with-datasets)中提及的 `datasets` 库直接使用。

## 数据集描述
- **主页：** https://argilla.io
- **仓库：** https://github.com/argilla-io/argilla
- **论文：**
- **排行榜：**
- **联系方式：**

### 数据集概览
本数据集包含以下内容：
* 符合 Argilla 数据集格式的数据集配置文件，名为 `argilla.yaml`。在 Argilla 中使用 `FeedbackDataset.from_huggingface` 方法时，将使用该配置文件对数据集进行配置。
* 兼容 Hugging Face `datasets` 库格式的数据集记录。使用 `FeedbackDataset.from_huggingface` 时，这些记录将自动加载；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）。

### 通过 Argilla 加载
如需通过 Argilla 加载本数据集，只需通过 `pip install argilla --upgrade` 升级安装 Argilla，然后运行以下代码：
python
import argilla as rg

ds = rg.FeedbackDataset.from_huggingface("DIBT/MPEP_ARABIC")

### 通过 `datasets` 库加载
如需通过 `datasets` 库加载本数据集，只需通过 `pip install datasets --upgrade` 升级安装 `datasets` 库，然后运行以下代码：
python
from datasets import load_dataset

ds = load_dataset("DIBT/MPEP_ARABIC")

### 支持任务与排行榜
本数据集包含[多个字段、问题与回复](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset)，因此可根据配置用于不同的自然语言处理（NLP）任务。数据集结构详见[数据集结构章节](#dataset-structure)。
本数据集暂无关联排行榜。

### 语言
[需补充更多信息]

## 数据集结构
### Argilla 中的数据
本数据集在 Argilla 中通过以下元素构建：**字段（fields）**、**问题（questions）**、**建议（suggestions）**、**元数据（metadata）**、**向量（vectors）** 与 **指南（guidelines）**。

**字段** 即数据集记录本身，目前仅支持文本字段。这些字段将用于接收针对问题的回复。

| 字段名 | 标题 | 类型 | 必填 | 支持Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| source | 源文本 | text | 是 | 是 |

**问题** 即向标注者提出的问题，支持多种类型，如评分、文本、标签选择、多标签选择或排序。

| 问题名称 | 标题 | 类型 | 必填 | 描述 | 取值/标签 |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| target | 目标文本 | text | 是 | 翻译该文本。 | 无适用值 |

**建议** 即针对每个问题由人工或机器生成的推荐内容，用于在标注流程中协助标注者。建议始终与现有问题关联，命名时会分别追加 `-suggestion` 与 `-suggestion-metadata` 后缀，分别存储建议值及其元数据。可能的取值与上表一致，但列名需追加 `-suggestion` 后缀，元数据则追加 `-suggestion-metadata` 后缀。

**元数据** 是可用于提供数据集记录额外信息的字典，可用于向标注者提供额外上下文，或补充数据集记录本身的信息。例如，可用于提供数据集记录的原始来源链接，或补充记录的作者、日期、来源等信息。元数据始终为可选字段，可与 `argilla.yaml` 中数据集配置文件定义的 `metadata_properties` 关联。

| 元数据名称 | 标题 | 类型 | 取值 | 对标注者可见 |
| ------------- | ----- | ---- | ------ | ---------------------- |

**指南** 同样为可选字段，是可用于向标注者提供说明的纯文本字符串。详见[标注指南](#annotation-guidelines)章节。

### 数据实例
Argilla 中的数据集示例如以下格式所示：
json
{
"external_id": null,
"fields": {
"source": "If a recipe calls for 2 1/2 cups of sugar and you want to make a half portion of it, calculate the exact amount of sugar needed."
},
"metadata": {
"evolved_from": null,
"kind": "synthetic",
"source": "argilla/distilabel-reasoning-prompts"
},
"responses": [
{
"status": "submitted",
"user_id": "6e3edb87-0ccc-47ef-bd61-3ed0e68b20de",
"values": {
"target": {
"value": "إذا كانت الوصفة تتطلب كوبين ونصف من السكر وتريد تحضير نصف هذه الكمية، فاحسب كمية السكر المطلوبة بالضبط."
}
}
}
],
"suggestions": [
{
"agent": null,
"question_name": "target",
"score": null,
"type": null,
"value": "إذا كانت الو南فة تتطلب كوبين ونصف من السكر وتريد تحضير نصف الكمية، فاحسب الكمية الدقيقة من السكر المطلوبة."
}
],
"vectors": {}
}

而该记录在 Hugging Face `datasets` 库中的格式如下：
json
{
"external_id": null,
"metadata": "{"source": "argilla/distilabel-reasoning-prompts", "kind": "synthetic", "evolved_from": null}",
"source": "If a recipe calls for 2 1/2 cups of sugar and you want to make a half portion of it, calculate the exact amount of sugar needed.",
"target": [
{
"status": "submitted",
"user_id": "6e3edb87-0ccc-47ef-bd61-3ed0e68b20de",
"value": "إذا كانت الو南فة تتطلب كوبين ونصف من السكر وتريد تحضير نصف الكمية، فاحسب الكمية الدقيقة من السكر المطلوبة."
}
],
"target-suggestion": "إذا كانت الو535نفة تتطلب كوبين ونصف من السكر وتريد تحضير نصف الكمية، فاحسب الكمية الدقيقة من السكر المطلوبة.",
"target-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
}
}

### 数据字段
在数据集字段中，我们可分为以下几类：
* **字段：** 即数据集记录本身，目前仅支持文本字段。这些字段将用于接收针对问题的回复。
* **source** 类型为 `text`。
* **问题：** 即向标注者提出的问题，支持多种类型，如 `RatingQuestion`、`TextQuestion`、`LabelQuestion`、`MultiLabelQuestion` 与 `RankingQuestion`。
* **target** 类型为 `text`，描述为“翻译该文本。”。
* **建议：** 自 Argilla 1.13.0 起，新增建议功能，用于向标注者提供辅助以简化标注流程。建议与现有问题关联，始终为可选字段，不仅包含建议内容本身，还可包含关联的元数据（若有）。
* （可选）**target-suggestion** 类型为 `text`。

此外，还有两个可选字段：
* **元数据：** 该可选字段可用于提供数据集记录的额外信息，可向标注者提供额外上下文，或补充记录本身的信息。例如，可用于提供记录的原始来源链接，或补充记录的作者、日期、来源等信息。元数据始终为可选字段，可与 `argilla.yaml` 中数据集配置文件定义的 `metadata_properties` 关联。
* **external_id：** 该可选字段可用于为数据集记录提供外部ID，便于将记录与外部资源（如数据库或文件）关联。

### 数据划分
本数据集仅包含一个划分：`train`（训练集）。

## 数据集构建
### 构建缘由
[需补充更多信息]

### 源数据
#### 初始数据收集与归一化
[需补充更多信息]

#### 源语言生产者是谁？
[需补充更多信息]

### 标注
#### 标注指南
本数据集为文本翻译数据集，请翻译文本字段中的内容。

#### 标注流程
[需补充更多信息]

#### 标注者是谁？
[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]

### 其他已知局限性
[需补充更多信息]

## 附加信息
### 数据集策展人
[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
[需补充更多信息]