dev-ner-ontonotes

Validation set of NER dataset OntoNotes5 created with Argilla for a Argilla Meetup talk.

Usage

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("louisguitton/dev-ner-ontonotes")

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("louisguitton/dev-ner-ontonotes")

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
text	Text	text	True	False

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
entities	Highlight the entities in the text:	span	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".

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": null,
    "fields": {
        "text": "A Russian diver has found the bodies of three of the 118 sailors who were killed when the nuclear submarine Kursk sank in the Barents Sea ."
    },
    "metadata": {},
    "responses": [],
    "suggestions": [
        {
            "agent": "gold_labels",
            "question_name": "entities",
            "score": null,
            "type": null,
            "value": [
                {
                    "end": 9,
                    "label": "NORP",
                    "score": 1.0,
                    "start": 2
                },
                {
                    "end": 45,
                    "label": "CARDINAL",
                    "score": 1.0,
                    "start": 40
                },
                {
                    "end": 56,
                    "label": "CARDINAL",
                    "score": 1.0,
                    "start": 53
                },
                {
                    "end": 113,
                    "label": "PRODUCT",
                    "score": 1.0,
                    "start": 108
                },
                {
                    "end": 137,
                    "label": "LOC",
                    "score": 1.0,
                    "start": 122
                }
            ]
        }
    ],
    "vectors": {}
}

While the same record in HuggingFace datasets looks as follows:

{
    "entities": [],
    "entities-suggestion": {
        "end": [
            9,
            45,
            56,
            113,
            137
        ],
        "label": [
            "NORP",
            "CARDINAL",
            "CARDINAL",
            "PRODUCT",
            "LOC"
        ],
        "score": [
            1.0,
            1.0,
            1.0,
            1.0,
            1.0
        ],
        "start": [
            2,
            40,
            53,
            108,
            122
        ],
        "text": [
            "Russian",
            "three",
            "118",
            "Kursk",
            "the Barents Sea"
        ]
    },
    "entities-suggestion-metadata": {
        "agent": "gold_labels",
        "score": null,
        "type": null
    },
    "external_id": null,
    "metadata": "{}",
    "text": "A Russian diver has found the bodies of three of the 118 sailors who were killed when the nuclear submarine Kursk sank in the Barents Sea ."
}

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.

  • text 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.

  • entities is of type span.

• 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) entities-suggestion is of type span.

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 validation.