Published February 8, 2018
| Version v1
Dataset
Open
Dataset for generating TL;DR
- 1. Bauhaus-Universität Weimar
Description
This is the dataset for the TL;DR challenge containing posts from the Reddit corpus, suitable for abstractive summarization using deep learning. The format is a json file where each line is a JSON object representing a post. The schema of each post is shown below:
- author: string (nullable = true)
- body: string (nullable = true)
- normalizedBody: string (nullable = true)
- content: string (nullable = true)
- content_len: long (nullable = true)
- summary: string (nullable = true)
- summary_len: long (nullable = true)
- id: string (nullable = true)
- subreddit: string (nullable = true)
- subreddit_id: string (nullable = true)
- title: string (nullable = true)
Specifically, the content and summary fields can be directly used as inputs to a deep learning model (e.g. Sequence to Sequence model ). The dataset consists of 3,084,410 posts with an average length of 211 words for content, and 25 words for the summary.
Note : As this is the complete dataset for the challenge, it is up to the participants to split it into training and validation sets accordingly.
Files
tldr-challenge-dataset.zip
Files
(2.2 GB)
Name | Size | Download all |
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md5:28951b6f3d5c6fd6f97e1f6314be3661
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2.2 GB | Preview Download |
Additional details
Related works
- Cites
- 10.5281/zenodo.1043504 (DOI)