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Parent(s):
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Browse files- .argilla/dataset.json +16 -0
- .argilla/settings.json +70 -0
- .argilla/version.json +3 -0
- README.md +143 -44
.argilla/dataset.json
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{
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"id": "f3ce3309-7f92-446b-8234-75d37c2e4816",
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"name": "emojis",
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"guidelines": null,
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"allow_extra_metadata": false,
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"status": "ready",
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"distribution": {
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"strategy": "overlap",
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"min_submitted": 1
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},
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"metadata": null,
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"workspace_id": "3930233b-f754-480b-b2e8-d290d8bcb518",
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"last_activity_at": "2024-12-16T15:05:35.226853",
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"inserted_at": "2024-12-16T08:19:08.318262",
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"updated_at": "2024-12-16T08:19:08.769259"
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}
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.argilla/settings.json
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{
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"guidelines": null,
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"allow_extra_metadata": false,
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"distribution": {
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"strategy": "overlap",
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"min_submitted": 1
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},
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"fields": [
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{
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"id": "e5b483ae-dc35-4a59-8ff3-396d8cf67a1a",
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"name": "text",
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"title": "text",
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "f3ce3309-7f92-446b-8234-75d37c2e4816",
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"inserted_at": "2024-12-16T08:19:08.529321",
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"updated_at": "2024-12-16T08:19:08.529321"
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}
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],
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"questions": [
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{
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"id": "97fd601f-18a1-4de3-ab23-1ba69e43c332",
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"name": "text_question",
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"title": "text_question",
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"description": null,
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"required": true,
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"settings": {
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"type": "text",
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"use_markdown": false
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},
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"dataset_id": "f3ce3309-7f92-446b-8234-75d37c2e4816",
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"inserted_at": "2024-12-16T08:19:08.582181",
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"updated_at": "2024-12-16T08:19:08.582181"
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},
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{
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"id": "9a316cb1-ef30-4b13-8c70-dbfa52545a82",
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"name": "span_question",
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"title": "span_question",
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"description": null,
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"required": true,
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"settings": {
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"type": "span",
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"field": "text",
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"options": [
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{
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"value": "PERSON",
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"text": "PERSON",
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"description": null
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},
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{
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"value": "ORG",
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"text": "ORG",
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"description": null
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}
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],
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"visible_options": null,
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"allow_overlapping": false,
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"allow_character_annotation": true
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},
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"dataset_id": "f3ce3309-7f92-446b-8234-75d37c2e4816",
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"inserted_at": "2024-12-16T08:19:08.681902",
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"updated_at": "2024-12-16T08:19:08.681902"
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}
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],
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"metadata": [],
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"vectors": []
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}
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.argilla/version.json
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{
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"argilla": "2.6.0dev0"
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}
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README.md
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---
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-
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- name: status
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dtype: string
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- name: inserted_at
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dtype: timestamp[us]
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- name: updated_at
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dtype: timestamp[us]
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- name: _server_id
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dtype: string
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- name: text
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dtype: string
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- name: text_question.responses
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sequence: string
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- name: text_question.responses.users
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sequence: string
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- name: text_question.responses.status
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sequence: string
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- name: span_question.responses
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list:
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list:
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- name: end
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dtype: int64
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- name: label
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dtype: string
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- name: start
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dtype: int64
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- name: span_question.responses.users
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sequence: string
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- name: span_question.responses.status
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sequence: string
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splits:
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- name: train
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num_bytes: 655
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num_examples: 3
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download_size: 8529
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dataset_size: 655
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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---
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tags:
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- rlfh
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- argilla
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- human-feedback
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---
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# Dataset Card for emojis
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This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
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## Using this dataset with Argilla
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To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
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```python
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import argilla as rg
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ds = rg.Dataset.from_hub("dvilasuero/emojis", settings="auto")
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```
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This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
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## Using this dataset with `datasets`
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To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
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```python
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from datasets import load_dataset
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ds = load_dataset("dvilasuero/emojis")
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```
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This will only load the records of the dataset, but not the Argilla settings.
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## Dataset Structure
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This dataset repo contains:
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* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
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* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
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* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
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The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
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### Fields
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The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
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| Field Name | Title | Type | Required |
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| ---------- | ----- | ---- | -------- |
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| text | text | text | True |
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### Questions
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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.
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| Question Name | Title | Type | Required | Description | Values/Labels |
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| ------------- | ----- | ---- | -------- | ----------- | ------------- |
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| text_question | text_question | text | True | N/A | N/A |
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| span_question | span_question | span | True | N/A | ['PERSON', 'ORG'] |
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<!-- check length of metadata properties -->
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### Data Splits
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The dataset contains a single split, which is `train`.
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation guidelines
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[More Information Needed]
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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### Contributions
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[More Information Needed]
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