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Description

Extracting journalistic narratives from text and representing them in a narrative modeling language

This vibrant research line poses many challenging problems in information extraction and automatic production of media content. At this project we want to be able to extract narratives/stories from news articles or collections of related news articles (unstructured data) about the same (or related) subject, representing those narratives in intermediate data structures (structured data) and making this available to subsequent media production processes (semi-automatic generation of slide shows, infographics and other visualizations, video sequences, games, etc.). In summary, our aim in Text2Story project is to develop a conceptual framework and operational pipeline for the extraction of narratives from textual sources. The project focuses on the automatic processing of journalistic text in written Portuguese.

Details

Details

  • Acronym

    Text2Story
  • Start

    14th November 2019
  • Global Budget

    239.736,00 €
  • State

    Completed
  • Effective End

    30th June 2023
  • End

    30th June 2023
  • Responsible

    Alípio Jorge
  • Financing

    219.852,00 €
  • Funded by

Team
news
001

Associated Centres

LIAAD

Centre

Artificial Intelligence and Decision Support