Dataset for Query-based Multi-Document Summarization

This repository contains versions of automatically generated datasets for abstractive and extractive query-based multi-document summarization as described in AQuaMuSe paper.

High-level Notes:

• Dependencies: Documents URLs references the Common Crawl June 2017 Archive.
• Data Format:
  • Directory structure:
    • Each dataset release with have two top-level folders: abstractive and extractive.
    • Each top-level folder contains three sub-folders for train, dev and test examples.
  • File format: TFrecords.
  • Fields:
    • query: input query to be used as summarization context. This is a single valued byte_list feature, derived from Natural Questions user queries.
    • input_urls: List of URLs to input documents pointing to Common Crawl to be summarized. Each URL is separated with a special token separator <EOD>.
    • target: Summarization target, derived from Natural Questions long answers.

Disclaimer

This is not an official Google product.