Dataset Card for MPEP_FILIPINO

This dataset has been created with Argilla.

As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.

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 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:

import argilla as rg

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

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:

from datasets import load_dataset

ds = load_dataset("DIBT/MPEP_FILIPINO")

Supported Tasks and Leaderboards

This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.

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 section.

Data Instances

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

{
    "external_id": "1752",
    "fields": {
        "source": "what role does a pass transistor and an op amp play in a regulator"
    },
    "metadata": {
        "evolved_from": null,
        "kind": "human",
        "source": "ewof/sharegpt-instruct-unfiltered-deduped"
    },
    "responses": [
        {
            "status": "submitted",
            "user_id": "7a0edea3-6cb5-44c9-8ecf-fdf7935cf064",
            "values": {
                "target": {
                    "value": "ano ang papel na ginagampanan ng pass transistor at op amp sa isang regulator"
                }
            }
        }
    ],
    "suggestions": [
        {
            "agent": null,
            "question_name": "target",
            "score": null,
            "type": null,
            "value": "Ano ang papel na ginagampanan ng isang pass transistor at op amp sa isang regulator\n\nAng papel ng isang pass transistor sa isang regulator ay upang i-regulate ang output voltage at kung minsan ay ginagamit upang mabawasan ang load ng regulator. Nagbibigay ito ng malalaking daloy ng kuryente na kinakailangan upang mapanatili ang steady output kahit na ang input o ang load ay nagbabago.\n\nSa kabilang banda, ang isang operational amplifier o op amp ay isang uri ng amplifier na maaaring mag-adjust at mag-control ng voltage sa isang circuit. Ginagamit ito sa isang regulator upang mai-maintain ang tamang kahalumigmigan sa loob ng system habang sinisiguro na ang mga komponitente ay hindi mahalata ng sobrang init o lamig. Bukod dito, ginagamit din ito upang mabawasan ang distorsyon at nagsisilbi rin bilang isang voltage follower."
        }
    ],
    "vectors": {}
}

While the same record in HuggingFace datasets looks as follows:

{
    "external_id": "1752",
    "metadata": "{\"evolved_from\": null, \"kind\": \"human\", \"source\": \"ewof/sharegpt-instruct-unfiltered-deduped\"}",
    "source": "what role does a pass transistor and an op amp play in a regulator",
    "target": [
        {
            "status": "submitted",
            "user_id": "7a0edea3-6cb5-44c9-8ecf-fdf7935cf064",
            "value": "ano ang papel na ginagampanan ng pass transistor at op amp sa isang regulator"
        }
    ],
    "target-suggestion": "Ano ang papel na ginagampanan ng isang pass transistor at op amp sa isang regulator\n\nAng papel ng isang pass transistor sa isang regulator ay upang i-regulate ang output voltage at kung minsan ay ginagamit upang mabawasan ang load ng regulator. Nagbibigay ito ng malalaking daloy ng kuryente na kinakailangan upang mapanatili ang steady output kahit na ang input o ang load ay nagbabago.\n\nSa kabilang banda, ang isang operational amplifier o op amp ay isang uri ng amplifier na maaaring mag-adjust at mag-control ng voltage sa isang circuit. Ginagamit ito sa isang regulator upang mai-maintain ang tamang kahalumigmigan sa loob ng system habang sinisiguro na ang mga komponitente ay hindi mahalata ng sobrang init o lamig. Bukod dito, ginagamit din ito upang mabawasan ang distorsyon at nagsisilbi rin bilang isang voltage follower.",
    "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?

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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

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

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Contributions

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