metadata

task_categories:
  - summarization
  - text-generation
language:
  - en
pretty_name: BookSum Summarization Dataset Clean
size_categories:
  - 1K<n<10K
configs:
  - config_name: books
    data_files:
      - split: train
        path: books/train.jsonl
      - split: test
        path: books/test.jsonl
      - split: validation
        path: books/val.jsonl
  - config_name: chapters
    data_files:
      - split: train
        path: chapters/train.jsonl
      - split: test
        path: chapters/test.jsonl
      - split: validation
        path: chapters/val.jsonl

Description
Usage
Distribution
- Chapters Dataset
- Books Dataset
Structure
Results and Comparison with kmfoda/booksum

Description:

This repository contains the Booksum dataset introduced in the paper BookSum: A Collection of Datasets for Long-form Narrative Summarization .

This dataset includes both book and chapter summaries from the BookSum dataset (unlike the kmfoda/booksum one which only contains the chapter dataset). Some mismatched summaries have been corrected. Uneccessary columns have been discarded. Contains minimal text-to-summary rows. As there are multiple summaries for a given text, each row contains an array of summaries.

Usage

Note: Make sure you have >2.14.0 version of "datasets" library installed to load the dataset successfully.

from datasets import load_dataset

book_data = load_dataset("ubaada/booksum-complete-cleaned", "books")
chapter_data = load_dataset("ubaada/booksum-complete-cleaned", "chapters")


# Print the 1st book
print(book_data["train"][0]['text'])

# Print the summary of the 1st book 
print(book_data["train"][0]['summary'][0]['text'])

Distribution

Chapters Dataset

Split	Total Sum.	Missing Sum.	Successfully Processed	Chapters
Train	9712	178	9534 (98.17%)	5653
Test	1432	0	1432 (100.0%)	950
Val	1485	0	1485 (100.0%)	854

Books Dataset

Split	Total Sum.	Successfully Processed	Books
Train	314	314 (100.0%)	151
Test	46	46 (100.0%)	17
Val	45	45 (100.0%)	19

Structure:

Chapters Dataset
  0 - bid (book id) 
  1 - book_title
  2 - chapter_id
  3 - text (raw chapter text)
  4 - summary (list of summaries from different sources)
      - {source, text (summary), analysis}
      ...
  5 - is_aggregate (bool) (if true, then the text contains more than one chapter)

Books Dataset:
  0 - bid (book id)
  1 - title
  2 - text (raw text)
  4 - summary (list of summaries from different sources)
      - {source, text (summary), analysis}
      ...

Reults and Comparison with kmfoda/booksum

Tested on the 'test' split of chapter sub-dataset. There are slight improvement on R1/R2 scores compared to another BookSum repo likely due to the work done on cleaning the misalignments in the alignment file. In the plot for this dataset, first summary [0] is chosen for each chapter. If best reference summary is chosen from the list for each chapter, theere are further improvements but are not shown here for fairness.

Datasets:

ubaada
/

booksum-complete-cleaned

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