metadata

size_categories: 1K<n<10K
tags:
  - rlfh
  - argilla
  - human-feedback
dataset_info:
  features:
    - name: prompt
      dtype: string
      id: field
    - name: context
      dtype: string
      id: field
    - name: response
      list:
        - name: user_id
          dtype: string
          id: question
        - name: value
          dtype: string
          id: suggestion
        - name: status
          dtype: string
          id: question
    - name: response-suggestion
      dtype: string
      id: suggestion
    - name: response-suggestion-metadata
      struct:
        - name: type
          dtype: string
          id: suggestion-metadata
        - name: score
          dtype: float32
          id: suggestion-metadata
        - name: agent
          dtype: string
          id: suggestion-metadata
    - name: external_id
      dtype: string
      id: external_id
    - name: metadata
      dtype: string
      id: metadata
  splits:
    - name: train
      num_bytes: 3008948
      num_examples: 1030
  download_size: 1725693
  dataset_size: 3008948

Dataset Card for text-descriptives-metadata

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 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 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("argilla/text-descriptives-metadata")

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("argilla/text-descriptives-metadata")

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, 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
prompt	Prompt	FieldTypes.text	True	True
context	Context	FieldTypes.text	False	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
response	Response	QuestionTypes.text	True	N/A	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".

✨ NEW 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.

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": null,
    "fields": {
        "context": null,
        "prompt": "Can brain cells move? By movement I mean long distance migration (preferably within the brain only)."
    },
    "metadata": {
        "entropy": 0.4352176404374839,
        "flesch_reading_ease": 82.39000000000001,
        "n_characters": 85,
        "passed_quality_check": "True"
    },
    "responses": [],
    "suggestions": [
        {
            "agent": null,
            "question_name": "response",
            "score": null,
            "type": null,
            "value": "The question is relatively broad and one should take into account that the brain not only consists of neurons, but also glial cells (supportive cells) and pre-mitotic neuronal stem cells. Furthermore, as critical fellow-scientists have indicated, developmental stage is very important, as the developing embryonic brain is very different from the adult brain.\nHowever, after sifting through various publications, the answer to the question is actually remarkably simple: Yes, brain cells migrate.\nIn  the adult brain glial cells migrate in the brain (Kl\u00e4mbt, 2009). Glial cells are involved in a myriad of functions, but a notable example of migrating glial cells are the oligodendrocytes that migrate relative long distances to find their target axons onto which they wrap themselves to form the insulating myelin sheath (Tsai and Miller, 2002).\nNeuronal stem cells migrate over long distances in response to injury (Imitola et al., 2004) and they migrate from specific stem-cell locations (e.g., hippocampus and subventricular zone) to other regions (Clarke, 2003).\nPost-mitotic, but non-differentiated neurons have been shown to migrate in the adult brain in fish (Scott et al., 2012), and in mammals and non-human primates as well (Sawada et al., 2011).\nNot surprisingly, glial cells, stem cells and neurons also migrate during embryonic development. Most notably, post-mitotic neurons destined to fulfill peripheral functions have to migrate over relatively long distances from the neural crest to their target locations (Neuroscience, 2nd ed, Neuronal Migration)."
        }
    ]
}

While the same record in HuggingFace datasets looks as follows:

{
    "context": null,
    "external_id": null,
    "metadata": "{\"n_characters\": 85, \"passed_quality_check\": \"True\", \"flesch_reading_ease\": 82.39000000000001, \"entropy\": 0.4352176404374839}",
    "prompt": "Can brain cells move? By movement I mean long distance migration (preferably within the brain only).",
    "response": [],
    "response-suggestion": "The question is relatively broad and one should take into account that the brain not only consists of neurons, but also glial cells (supportive cells) and pre-mitotic neuronal stem cells. Furthermore, as critical fellow-scientists have indicated, developmental stage is very important, as the developing embryonic brain is very different from the adult brain.\nHowever, after sifting through various publications, the answer to the question is actually remarkably simple: Yes, brain cells migrate.\nIn  the adult brain glial cells migrate in the brain (Kl\u00e4mbt, 2009). Glial cells are involved in a myriad of functions, but a notable example of migrating glial cells are the oligodendrocytes that migrate relative long distances to find their target axons onto which they wrap themselves to form the insulating myelin sheath (Tsai and Miller, 2002).\nNeuronal stem cells migrate over long distances in response to injury (Imitola et al., 2004) and they migrate from specific stem-cell locations (e.g., hippocampus and subventricular zone) to other regions (Clarke, 2003).\nPost-mitotic, but non-differentiated neurons have been shown to migrate in the adult brain in fish (Scott et al., 2012), and in mammals and non-human primates as well (Sawada et al., 2011).\nNot surprisingly, glial cells, stem cells and neurons also migrate during embryonic development. Most notably, post-mitotic neurons destined to fulfill peripheral functions have to migrate over relatively long distances from the neural crest to their target locations (Neuroscience, 2nd ed, Neuronal Migration).",
    "response-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.
- prompt is of type FieldTypes.text.
- (optional) context is of type FieldTypes.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.
- response is of type QuestionTypes.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) response-suggestion is of type QuestionTypes.text.

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

✨ NEW 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 supervised fine-tuning dataset that contains instructions. Please write the response to the instruction in the response field. Take the context into account when writing the response.

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]

Dataset Card for text-descriptives-metadata

Dataset Description

Dataset Summary

Load with Argilla

Load with datasets

Supported Tasks and Leaderboards

Languages

Dataset Structure

Data in Argilla

Data Instances

Data Fields

Data Splits

Dataset Creation

Curation Rationale

Source Data

Initial Data Collection and Normalization

Who are the source language producers?

Annotations

Annotation guidelines

Annotation process

Who are the annotators?

Personal and Sensitive Information

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

Other Known Limitations

Additional Information

Dataset Curators

Licensing Information

Citation Information

Contributions

Load with `datasets`