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--- |
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annotations_creators: |
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- other |
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language_creators: |
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- other |
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language: |
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- en |
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multilinguality: |
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- monolingual |
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pretty_name: tldr_news |
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size_categories: |
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- 1K<n<10K |
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source_datasets: |
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- original |
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task_categories: |
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- summarization |
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- text2text-generation |
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- text-generation |
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task_ids: |
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- news-articles-headline-generation |
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- text-simplification |
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- language-modeling |
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--- |
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# Dataset Card for `tldr_news` |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-instances) |
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- [Data Splits](#data-instances) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Homepage:** https://tldr.tech/newsletter |
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### Dataset Summary |
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The `tldr_news` dataset was constructed by collecting a daily tech newsletter (available |
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[here](https://tldr.tech/newsletter)). Then, for every piece of news, the `headline` and its corresponding ` |
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content` were extracted. |
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Also, the newsletter contain different sections. We add this extra information to every piece of news. |
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Such a dataset can be used to train a model to generate a headline from a input piece of text. |
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### Supported Tasks and Leaderboards |
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There is no official supported tasks nor leaderboard for this dataset. However, it could be used for the following |
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tasks: |
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- summarization |
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- headline generation |
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### Languages |
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en |
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## Dataset Structure |
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### Data Instances |
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A data point comprises a "headline" and its corresponding "content". |
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An example is as follows: |
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``` |
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{ |
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"headline": "Cana Unveils Molecular Beverage Printer, a ‘Netflix for Drinks’ That Can Make Nearly Any Type of Beverage ", |
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"content": "Cana has unveiled a drink machine that can synthesize almost any drink. The machine uses a cartridge that contains flavor compounds that can be combined to create the flavor of nearly any type of drink. It is about the size of a toaster and could potentially save people from throwing hundreds of containers away every month by allowing people to create whatever drinks they want at home. Around $30 million was spent building Cana’s proprietary hardware platform and chemistry system. Cana plans to start full production of the device and will release pricing by the end of February.", |
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"category": "Science and Futuristic Technology" |
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} |
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``` |
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### Data Fields |
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- `headline (str)`: the piece of news' headline |
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- `content (str)`: the piece of news |
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- `category (str)`: newsletter section |
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### Data Splits |
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- `all`: all existing daily newsletters available [here](https://tldr.tech/newsletter). |
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## Dataset Creation |
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### Curation Rationale |
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This dataset was obtained by scrapping the collecting all the existing newsletter |
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available [here](https://tldr.tech/newsletter). |
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Every single newsletter was then processed to extract all the different pieces of news. Then for every collected piece |
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of news the headline and the news content were extracted. |
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### Source Data |
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#### Initial Data Collection and Normalization |
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The dataset was has been collected from https://tldr.tech/newsletter. |
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In order to clean up the samples and to construct a dataset better suited for headline generation we have applied a |
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couple of normalization steps: |
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1. The headlines initially contain an estimated read time in parentheses; we stripped this information from the |
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headline. |
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2. Some news are sponsored and thus do not belong to any newsletter section. We create an additional category "Sponsor" |
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for such samples. |
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#### Who are the source language producers? |
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The people (or person) behind the https://tldr.tech/ newsletter. |
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### Annotations |
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#### Annotation process |
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Disclaimers: The dataset was generated from a daily newsletter. The author had no intention for those newsletters to be |
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used as such. |
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#### Who are the annotators? |
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The newsletters were written by the people behind *TLDR tech*. |
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### Personal and Sensitive Information |
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[Needs More Information] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[Needs More Information] |
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### Discussion of Biases |
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This dataset only contains tech news. A model trained on such a dataset might not be able to generalize to other domain. |
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### Other Known Limitations |
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[Needs More Information] |
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## Additional Information |
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### Dataset Curators |
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The dataset was obtained by collecting newsletters from this website: https://tldr.tech/newsletter |
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### Contributions |
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Thanks to [@JulesBelveze](https://github.com/JulesBelveze) for adding this dataset. |
