Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K<n<10K
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| paperswithcode_id: wnut-2017-emerging-and-rare-entity | |
| pretty_name: WNUT 17 | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': O | |
| '1': B-corporation | |
| '2': I-corporation | |
| '3': B-creative-work | |
| '4': I-creative-work | |
| '5': B-group | |
| '6': I-group | |
| '7': B-location | |
| '8': I-location | |
| '9': B-person | |
| '10': I-person | |
| '11': B-product | |
| '12': I-product | |
| config_name: wnut_17 | |
| splits: | |
| - name: train | |
| num_bytes: 1078379 | |
| num_examples: 3394 | |
| - name: validation | |
| num_bytes: 259383 | |
| num_examples: 1009 | |
| - name: test | |
| num_bytes: 405536 | |
| num_examples: 1287 | |
| download_size: 800955 | |
| dataset_size: 1743298 | |
| # Dataset Card for "wnut_17" | |
| ## 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:** [http://noisy-text.github.io/2017/emerging-rare-entities.html](http://noisy-text.github.io/2017/emerging-rare-entities.html) | |
| - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Size of downloaded dataset files:** 0.80 MB | |
| - **Size of the generated dataset:** 1.74 MB | |
| - **Total amount of disk used:** 2.55 MB | |
| ### Dataset Summary | |
| WNUT 17: Emerging and Rare entity recognition | |
| This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. | |
| Named entities form the basis of many modern approaches to other tasks (like event clustering and summarisation), | |
| but recall on them is a real problem in noisy text - even among annotators. This drop tends to be due to novel entities and surface forms. | |
| Take for example the tweet “so.. kktny in 30 mins?” - even human experts find entity kktny hard to detect and resolve. | |
| This task will evaluate the ability to detect and classify novel, emerging, singleton named entities in noisy text. | |
| The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Languages | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Dataset Structure | |
| ### Data Instances | |
| - **Size of downloaded dataset files:** 0.80 MB | |
| - **Size of the generated dataset:** 1.74 MB | |
| - **Total amount of disk used:** 2.55 MB | |
| An example of 'train' looks as follows. | |
| ``` | |
| { | |
| "id": "0", | |
| "ner_tags": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0], | |
| "tokens": ["@paulwalk", "It", "'s", "the", "view", "from", "where", "I", "'m", "living", "for", "two", "weeks", ".", "Empire", "State", "Building", "=", "ESB", ".", "Pretty", "bad", "storm", "here", "last", "evening", "."] | |
| } | |
| ``` | |
| ### Data Fields | |
| The data fields are the same among all splits: | |
| - `id` (`string`): ID of the example. | |
| - `tokens` (`list` of `string`): Tokens of the example text. | |
| - `ner_tags` (`list` of class labels): NER tags of the tokens (using IOB2 format), with possible values: | |
| - 0: `O` | |
| - 1: `B-corporation` | |
| - 2: `I-corporation` | |
| - 3: `B-creative-work` | |
| - 4: `I-creative-work` | |
| - 5: `B-group` | |
| - 6: `I-group` | |
| - 7: `B-location` | |
| - 8: `I-location` | |
| - 9: `B-person` | |
| - 10: `I-person` | |
| - 11: `B-product` | |
| - 12: `I-product` | |
| ### Data Splits | |
| |train|validation|test| | |
| |----:|---------:|---:| | |
| | 3394| 1009|1287| | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Licensing Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Citation Information | |
| ``` | |
| @inproceedings{derczynski-etal-2017-results, | |
| title = "Results of the {WNUT}2017 Shared Task on Novel and Emerging Entity Recognition", | |
| author = "Derczynski, Leon and | |
| Nichols, Eric and | |
| van Erp, Marieke and | |
| Limsopatham, Nut", | |
| booktitle = "Proceedings of the 3rd Workshop on Noisy User-generated Text", | |
| month = sep, | |
| year = "2017", | |
| address = "Copenhagen, Denmark", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://www.aclweb.org/anthology/W17-4418", | |
| doi = "10.18653/v1/W17-4418", | |
| pages = "140--147", | |
| abstract = "This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. | |
| Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization), | |
| but recall on them is a real problem in noisy text - even among annotators. | |
| This drop tends to be due to novel entities and surface forms. | |
| Take for example the tweet {``}so.. kktny in 30 mins?!{''} {--} even human experts find the entity {`}kktny{'} | |
| hard to detect and resolve. The goal of this task is to provide a definition of emerging and of rare entities, | |
| and based on that, also datasets for detecting these entities. The task as described in this paper evaluated the | |
| ability of participating entries to detect and classify novel and emerging named entities in noisy text.", | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@stefan-it](https://github.com/stefan-it), [@lewtun](https://github.com/lewtun), [@jplu](https://github.com/jplu) for adding this dataset. |