MPEP_CZECH

# Dataset Card for MPEP_CZECH

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_CZECH")
```

### 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_CZECH")
```

### 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": "1804",
"fields": {
"source": "What is the effect of climate change on the polar ice caps and how is it impacting global sea levels?"
},
"metadata": {
"evolved_from": null,
"kind": "human",
"source": "OpenAssistant/oasst2"
},
"responses": [
{
"status": "submitted",
"user_id": "818c9e76-9b4f-40c6-8efb-2dcd6d5d5ddb",
"values": {
"target": {
"value": "Jak\u00fd je vliv zm\u011bny klimatu na pol\u00e1rn\u00ed ledov\u00e9 \u010depice a jak ovliv\u0148uje glob\u00e1ln\u00ed hladinu mo\u0159\u00ed?"
}
}
}
],
"suggestions": [
{
"agent": null,
"question_name": "target",
"score": null,
"type": null,
"value": "Jak\u00fd je vliv zm\u011bny klimatu na pol\u00e1rn\u00ed ledov\u00e9 \u010depice a jak ovliv\u0148uje glob\u00e1ln\u00ed hladinu mo\u0159\u00ed?"
}
],
"vectors": {}
}
```

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

```json
{
"external_id": "1804",
"metadata": "{\"evolved_from\": null, \"kind\": \"human\", \"source\": \"OpenAssistant/oasst2\"}",
"source": "What is the effect of climate change on the polar ice caps and how is it impacting global sea levels?",
"target": [
{
"status": "submitted",
"user_id": "818c9e76-9b4f-40c6-8efb-2dcd6d5d5ddb",
"value": "Jak\u00fd je vliv zm\u011bny klimatu na pol\u00e1rn\u00ed ledov\u00e9 \u010depice a jak ovliv\u0148uje glob\u00e1ln\u00ed hladinu mo\u0159\u00ed?"
}
],
"target-suggestion": "Jak\u00fd je vliv zm\u011bny klimatu na pol\u00e1rn\u00ed ledov\u00e9 \u010depice a jak ovliv\u0148uje glob\u00e1ln\u00ed hladinu mo\u0159\u00ed?",
"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_CZECH 数据集卡片

本数据集基于 [Argilla](https://docs.argilla.io) 构建。如下文各章节所述，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`库使用。

## 数据集描述

- **主页：** https://argilla.io
- **代码仓库：** https://github.com/argilla-io/argilla
- **论文：**
- **排行榜：**
- **联系方式：**

### 数据集概述

本数据集包含以下内容：

1. 符合Argilla数据集格式的配置文件`argilla.yaml`。当在Argilla中使用`FeedbackDataset.from_huggingface`方法时，将通过该配置文件完成数据集的配置。
2. 兼容Hugging Face `datasets`库格式的数据集记录。在使用`FeedbackDataset.from_huggingface`时，这些记录将自动加载；也可通过`datasets`库的`load_dataset`方法独立加载。
3. 若在Argilla中已定义，则包含用于数据集构建与整理的[标注指南](#annotation-guidelines)。

### 通过Argilla加载

通过Argilla加载数据集时，仅需执行`pip install argilla --upgrade`安装Argilla，随后运行以下代码：

python
import argilla as rg

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

### 通过`datasets`库加载

若通过`datasets`库加载本数据集，仅需执行`pip install datasets --upgrade`安装依赖，随后运行以下代码：

python
from datasets import load_dataset

ds = load_dataset("DIBT/MPEP_CZECH")

### 支持任务与排行榜

本数据集包含[多字段、多问题与多回复](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset)，因此可根据配置适配多种自然语言处理（NLP）任务。数据集结构详见[数据集结构章节](#dataset-structure)。本数据集暂无关联的排行榜。

### 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，用于接收针对问题的回复。

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

**问题**即向标注人员提出的查询，支持多种类型，包括评分（rating）、文本回答（text）、标签选择（label_selection）、多标签选择（multi_label_selection）与排序（ranking）。

| 问题名 | 标题 | 类型 | 是否必填 | 描述 | 取值/标签 |
| ------ | ---- | ---- | -------- | ---- | --------- |
| target | 目标文本 | 文本 | 是 | 请翻译该文本。 | 无（N/A） |

**建议**指为辅助标注人员完成标注流程，针对每个问题生成的人工或机器推荐结果。建议始终与对应问题关联，命名方式为在问题名后追加`-suggestion`与`-suggestion-metadata`，分别存储建议内容与对应元数据。其可选取值与上述表格一致，但列名需追加`-suggestion`后缀，元数据列则追加`-suggestion-metadata`后缀。

**元数据**为用于存储数据集记录额外信息的字典结构，可用于向标注人员提供补充上下文，或记录数据集记录本身的附加信息。例如，可用于存储数据集记录的原始来源链接，或是作者、发布日期、来源等信息。元数据始终为可选字段，可与`argilla.yaml`数据集配置文件中定义的`metadata_properties`关联。

| 元数据名称 | 标题 | 类型 | 取值 | 对标注人员可见 |
| ---------- | ---- | ---- | ---- | -------------- |

**标注指南**同样为可选字段，为用于向标注人员提供操作说明的纯文本字符串，详见[标注指南章节](#annotation-guidelines)。

### 数据实例

Argilla中的数据集实例示例如下：

json
{
"external_id": "1804",
"fields": {
"source": "What is the effect of climate change on the polar ice caps and how is it impacting global sea levels?"
},
"metadata": {
"evolved_from": null,
"kind": "human",
"source": "OpenAssistant/oasst2"
},
"responses": [
{
"status": "submitted",
"user_id": "818c9e76-9b4f-40c6-8efb-2dcd6d5d5ddb",
"values": {
"target": {
"value": "Jaký je vliv změny klimatu na polární ledové čepice a jak ovlivňuje globální hladinu moří?"
}
}
}
],
"suggestions": [
{
"agent": null,
"question_name": "target",
"score": null,
"type": null,
"value": "Jaký je vliv změny klimatu na polární ledové čepice a jak ovlivňuje globální hladinu moří?"
}
],
"vectors": {}
}

而该记录在Hugging Face `datasets`库中的格式示例如下：

json
{
"external_id": "1804",
"metadata": "{"evolved_from": null, "kind": "human", "source": "OpenAssistant/oasst2"}",
"source": "What is the effect of climate change on the polar ice caps and how is it impacting global sea levels?",
"target": [
{
"status": "submitted",
"user_id": "818c9e76-9b4f-40c6-8efb-2dcd6d5d5ddb",
"value": "Jaký je vliv změny klimatu na polární ledové čepice a jak ovlivňuje globální hladinu moří?"
}
],
"target-suggestion": "Jaký je vliv změny klimatu na polární ledové čepice a jak ovlivňuje globální hladinu moří?",
"target-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
}
}

### 数据字段

本数据集的字段可分为以下几类：

1. **字段（Fields）**：即数据集记录本身，目前仅支持文本字段，用于接收针对问题的回复。其中**source**为`text`类型。
2. **问题（Questions）**：即向标注人员提出的查询，支持`RatingQuestion`、`TextQuestion`、`LabelQuestion`、`MultiLabelQuestion`与`RankingQuestion`等类型。其中**target**为`text`类型，描述为「请翻译该文本」。
3. **建议（Suggestions）**：自Argilla 1.13.0版本起，新增建议字段用于在标注流程中为标注人员提供辅助。建议与对应问题关联，为可选字段，不仅包含建议内容，还可附带对应元数据（若有）。其中（可选）**target-suggestion**为`text`类型。

此外，本数据集还包含两个可选字段：

* **metadata（元数据）**：可选字段，用于存储数据集记录的额外信息，可向标注人员提供补充上下文，或是记录记录本身的附加信息（如作者、日期、来源等），也可用于存储记录的原始来源链接。元数据可与`argilla.yaml`配置文件中定义的`metadata_properties`关联。
* **external_id（外部ID）**：可选字段，用于为数据集记录分配外部ID，可用于将数据集记录与外部资源（如数据库或文件）进行关联。

### 数据划分

本数据集仅包含一个划分，即`train`（训练集）。

## 数据集构建

### 标注依据

[需补充更多信息]

### 源数据

#### 初始数据收集与标准化

[需补充更多信息]

#### 原始文本创作者身份

[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，请对文本字段中的内容执行翻译操作。

#### 标注流程

[需补充更多信息]

#### 标注人员身份

[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]

### 贡献者

[需补充更多信息]