Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
topic-classification
Languages:
English
Size:
100K - 1M
ArXiv:
License:
| annotations_creators: | |
| - machine-generated | |
| language_creators: | |
| - crowdsourced | |
| language: | |
| - en | |
| license: | |
| - cc-by-sa-3.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 100K<n<1M | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - topic-classification | |
| paperswithcode_id: dbpedia | |
| pretty_name: DBpedia | |
| dataset_info: | |
| features: | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| 0: Company | |
| 1: EducationalInstitution | |
| 2: Artist | |
| 3: Athlete | |
| 4: OfficeHolder | |
| 5: MeanOfTransportation | |
| 6: Building | |
| 7: NaturalPlace | |
| 8: Village | |
| 9: Animal | |
| 10: Plant | |
| 11: Album | |
| 12: Film | |
| 13: WrittenWork | |
| - name: title | |
| dtype: string | |
| - name: content | |
| dtype: string | |
| config_name: dbpedia_14 | |
| splits: | |
| - name: train | |
| num_bytes: 178428970 | |
| num_examples: 560000 | |
| - name: test | |
| num_bytes: 22310285 | |
| num_examples: 70000 | |
| download_size: 68341743 | |
| dataset_size: 200739255 | |
| # Dataset Card for DBpedia14 | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [DBpedia14 homepage](https://wiki.dbpedia.org/develop/datasets) | |
| - **Repository:** [DBpedia14 repository](https://github.com/dbpedia/extraction-framework) | |
| - **Paper:** [DBpedia--a large-scale, multilingual knowledge base extracted from Wikipedia](https://content.iospress.com/articles/semantic-web/sw134) | |
| - **Point of Contact:** [Xiang Zhang](mailto:xiang.zhang@nyu.edu) | |
| ### Dataset Summary | |
| The DBpedia ontology classification dataset is constructed by picking 14 non-overlapping classes | |
| from DBpedia 2014. They are listed in classes.txt. From each of thse 14 ontology classes, we | |
| randomly choose 40,000 training samples and 5,000 testing samples. Therefore, the total size | |
| of the training dataset is 560,000 and testing dataset 70,000. | |
| There are 3 columns in the dataset (same for train and test splits), corresponding to class index | |
| (1 to 14), title and content. The title and content are escaped using double quotes ("), and any | |
| internal double quote is escaped by 2 double quotes (""). There are no new lines in title or content. | |
| ### Supported Tasks and Leaderboards | |
| - `text-classification`, `topic-classification`: The dataset is mainly used for text classification: given the content | |
| and the title, predict the correct topic. | |
| ### Languages | |
| Although DBpedia is a multilingual knowledge base, the DBpedia14 extract contains English data mainly, other languages may appear | |
| (e.g. a film whose title is origanlly not English). | |
| ## Dataset Structure | |
| ### Data Instances | |
| A typical data point, comprises of a title, a content and the corresponding label. | |
| An example from the DBpedia test set looks as follows: | |
| ``` | |
| { | |
| 'title':'', | |
| 'content':" TY KU /taɪkuː/ is an American alcoholic beverage company that specializes in sake and other spirits. The privately-held company was founded in 2004 and is headquartered in New York City New York. While based in New York TY KU's beverages are made in Japan through a joint venture with two sake breweries. Since 2011 TY KU's growth has extended its products into all 50 states.", | |
| 'label':0 | |
| } | |
| ``` | |
| ### Data Fields | |
| - 'title': a string containing the title of the document - escaped using double quotes (") and any internal double quote is escaped by 2 double quotes (""). | |
| - 'content': a string containing the body of the document - escaped using double quotes (") and any internal double quote is escaped by 2 double quotes (""). | |
| - 'label': one of the 14 possible topics. | |
| ### Data Splits | |
| The data is split into a training and test set. | |
| For each of the 14 classes we have 40,000 training samples and 5,000 testing samples. | |
| Therefore, the total size of the training dataset is 560,000 and testing dataset 70,000. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| The DBPedia ontology classification dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu), licensed under the terms of the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### 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 | |
| The DBPedia ontology classification dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu), licensed under the terms of the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). | |
| ### Licensing Information | |
| The DBPedia ontology classification dataset is licensed under the terms of the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. | |
| ### Citation Information | |
| Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015). | |
| Lehmann, Jens, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann et al. "DBpedia–a large-scale, multilingual knowledge base extracted from Wikipedia." Semantic web 6, no. 2 (2015): 167-195. | |
| ### Contributions | |
| Thanks to [@hfawaz](https://github.com/hfawaz) for adding this dataset. |