A survey on narrative extraction from textual data

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Santana, B (Author) Other; Campos, R (Author) Other; Amorim, E (Author) Other; Jorge, AM (Author) FCUP; Silvano, P (Author) Other; Sérgio Nunes (Author) FEUP

Journal

Title: Artificial Intelligence Review

Vol. 56

Pages: 8393-8435

ISSN: 0269-2821

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 10 Citations

Scopus - 16 Citations

Other information

Authenticus ID: P-00X-RW2

DOI: 10.1007/s10462-022-10338-7

Abstract (EN): Narratives are present in many forms of human expression and can be understood as a fundamental way of communication between people. Computational understanding of the underlying story of a narrative, however, may be a rather complex task for both linguists and computational linguistics. Such task can be approached using natural language processing techniques to automatically extract narratives from texts. In this paper, we present an in depth survey of narrative extraction from text, providing a establishing a basis/framework for the study roadmap to the study of this area as a whole as a means to consolidate a view on this line of research. We aim to fulfill the current gap by identifying important research efforts at the crossroad between linguists and computer scientists. In particular, we highlight the importance and complexity of the annotation process, as a crucial step for the training stage. Next, we detail methods and approaches regarding the identification and extraction of narrative components, their linkage and understanding of likely inherent relationships, before detailing formal narrative representation structures as an intermediate step for visualization and data exploration purposes. We then move into the narrative evaluation task aspects, and conclude this survey by highlighting important open issues under the domain of narratives extraction from texts that are yet to be explored.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 43