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--- |
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annotations_creators: |
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- found |
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language: |
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- en |
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language_creators: |
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- found |
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license: |
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- unknown |
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multilinguality: |
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- monolingual |
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pretty_name: English haiku dataset scraped from Reddit's /r/haiku with topics extracted |
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using KeyBERT |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- extended|other |
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tags: |
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- haiku |
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- poem |
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- poetry |
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- reddit |
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- keybert |
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- generation |
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task_categories: |
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- text-generation |
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task_ids: |
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- language-modeling |
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--- |
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# Dataset Card for "Reddit Haiku" |
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This dataset contains haikus from the subreddit [/r/haiku](https://www.reddit.com/r/haiku/) scraped and filtered between October 19th and 10th 2022, combined with a [previous dump](https://zissou.infosci.cornell.edu/convokit/datasets/subreddit-corpus/corpus-zipped/hackintosh_ja~-~hamsters/) of that same subreddit packaged by [ConvoKit](https://convokit.cornell.edu/documentation/subreddit.html) as part of the Subreddit Corpus, which is itself a subset of [pushshift.io](https://pushshift.io/)'s big dump. |
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A main motivation for this dataset was to collect an alternative haiku dataset for evaluation, in particular for evaluating Fabian Mueller's Deep Haiku [model](fabianmmueller/deep-haiku-gpt-j-6b-8bit) which was trained on the Haiku datasets of [hjhalani30](https://www.kaggle.com/datasets/hjhalani30/haiku-dataset) and [bfbarry](https://www.kaggle.com/datasets/bfbarry/haiku-dataset), which are also available on [huggingface hub](https://huggingface.co/datasets/statworx/haiku). |
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## Fields |
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The fields are post id (`id`), the content of the haiku (`processed_title`), upvotes (`ups`), and topic keywords (`keywords`). Topic keywords for each haiku have been extracted with the [KeyBERT library](https://maartengr.github.io/KeyBERT/guides/quickstart.html) and truncated to top-5 keywords. |
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## Usage |
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This dataset is intended for evaluation, hence there is only one split which is `test`. |
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```python |
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from datasets import load_dataset |
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d=load_dataset('huanggab/reddit_haiku', data_files='test':'merged_with_keywords.csv'}) # use data_files or it will result in error |
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>>> print(d['train'][0]) |
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#{'Unnamed: 0': 0, 'id': '1020ac', 'processed_title': "There's nothing inside/There is nothing outside me/I search on in hope.", 'ups': 5, 'keywords': "[('inside', 0.5268), ('outside', 0.3751), ('search', 0.3367), ('hope', 0.272)]"} |
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``` |
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There is code for scraping and processing in `processing_code`, and a subset of the data with more fields such as author Karma, downvotes and posting time at `processing_code/reddit-2022-10-20-dump.csv`. |
