README.md

metadata

license: cc-by-3.0
annotations_creators:
  - crowdsourced
language:
  - en
language_creators:
  - crowdsourced
multilinguality:
  - monolingual
paperswithcode_id: wikitext-2
pretty_name: Wikipedia Outline of Academic Disciplines
size_categories:
  - 10K<n<100K
source_datasets:
  - original
tags:
  - hierarchical
  - academic
  - tree
  - dag
  - topics
  - subjects
task_categories:
  - text-classification
task_ids:
  - multi-label-classification

Dataset Card for Wiki Academic Disciplines`

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • 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

Dataset Description

• Homepage:
• Repository:
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

This dataset was created from the English wikipedia dump of January 2022. The main goal was to train a hierarchical classifier of academic subjects using HiAGM.

Supported Tasks and Leaderboard

Text classification - No leaderboard at the moment.

Languages

English

Dataset Structure

The dataset consists of groups of labeled text chunks (tokenized by spaces and with stopwords removed). Labels are organized in a hieararchy (a DAG with a special Root node) of academic subjects. Nodes correspond to entries in the outline of academic disciplines article from Wikipedia.

Data Instances

Data is split in train/test/val each on a separate .jsonl file. Label hierarchy is listed a as TAB separated adjacency list on a .taxonomy file.

Data Fields

JSONL files contain only two fields: a "token" field which holds the text tokens and a "label" field which holds a list of labels for that text.

Data Splits

80/10/10 TRAIN/TEST/VAL schema

Dataset Creation

All texts where extracted following the linked articles on outline of academic disciplines

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

Wiki Dump

Who are the source language producers?

Wikipedia community.

Annotations

Annotation process

Texts where automatically assigned to their linked academic discipline

Who are the annotators?

Wikipedia Community.

Personal and Sensitive Information

All information is public.

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Creative Commons 3.0 (see Wikipedia:Copyrights)

Citation Information

1. Zhou, Jie, et al. "Hierarchy-aware global model for hierarchical text classification." Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.

Contributions

Thanks to @meliascosta for adding this dataset.