A Community-Driven Data-to-Text Platform for Football Match Summaries

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Fernandes, P (Author) Other; Sérgio Nunes (Author) FEUP; Santos, L (Author) Other

Conference proceedings International

Title: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Pages: 164-173

Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Torino, 2024

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-010-FY9

Abstract (EN): Data-to-text systems offer a transformative approach to generating textual content in data-rich environments. This paper describes the architecture and deployment of Prosebot, a community-driven data-to-text platform tailored for generating textual summaries of football matches derived from match statistics. The system enhances the visibility of lower-tier matches, traditionally accessible only through data tables. Prosebot uses a template-based Natural Language Generation (NLG) module to generate initial drafts, which are subsequently refined by the reading community. Comprehensive evaluations, encompassing both human-mediated and automated assessments, were conducted to assess the system's efficacy. Analysis of the community-edited texts reveals that significant segments of the initial automated drafts are retained, suggesting their high quality and acceptance by the collaborators. Preliminary surveys conducted among platform users highlight a predominantly positive reception within the community.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9