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Detalhes

Detalhes

  • Nome

    Evelin Freire Amorim
  • Cargo

    Investigador Auxiliar
  • Desde

    21 setembro 2020
002
Publicações

2023

Annotation and Visualisation of Reporting Events in Textual Narratives

Autores
Silvano, P; Amorim, E; Leal, A; Cantante, I; Silva, F; Jorge, A; Campos, R; Nunes, S;

Publicação
Proceedings of Text2Story - Sixth Workshop on Narrative Extraction From Texts held in conjunction with the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2, 2023.

Abstract
News articles typically include reporting events to inform on what happened. These reporting events are not part of the story being told but are nonetheless a relevant part of the news and can pose a challenge to the computational processing of news narratives. They compose a reporting narrative, which is the present study's focus. This paper aims to demonstrate through selected use cases how a comprehensive annotation scheme with suitable tags and links can properly represent the reporting events and the way they relate to the events that make the story. In addition, we put forward a proposal for their visual representation that enables a systematic and detailed analysis of the importance of reporting events in the news structure. Finally, we describe some lexico-grammatical features of reporting events, which can contribute to their automatic detection. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

2023

A survey on narrative extraction from textual data

Autores
Santana, B; Campos, R; Amorim, E; Jorge, A; Silvano, P; Nunes, S;

Publicação
ARTIFICIAL INTELLIGENCE REVIEW

Abstract
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.

2023

Mapeamento do Perfil das Mulheres Brasileiras em Processamento de Linguagem Natural

Autores
Caseli, H; Amorim, E; Schneider, ETR; Freitas, LIA; Rodrigues, J; Nunes, MdGV;

Publicação
Anais do XVII Women in Information Technology (WIT 2023)

Abstract
Conhecer o perfil das mulheres brasileiras que atuam em Processamento de Linguagem Natural (PLN) é um importante passo para o desenvolvimento de políticas e programas que visem aumentar a inclusão e a diversidade nessa área. Este é o primeiro trabalho realizado no Brasil com este fim. A partir de dados coletados via consulta pública, Lattes e Linkedin, notou-se que o perfil é de uma formação em computação ou linguística, atuando em empresas ou universidades, mas com pouca diversidade étnica e aparente dificuldade em conciliar vida profissional e maternidade. Analisando mais especificamente o grupo “Brasileiras em PLN” constatou-se uma expressiva capacidade de publicação e orientação, mas ainda uma baixa colaboração entre nossas integrantes.

2021

Brat2Viz: a Tool and Pipeline for Visualizing Narratives from Annotated Texts

Autores
Amorim, E; Ribeiro, A; Santana, BS; Cantante, I; Jorge, A; Nunes, S; Silvano, P; Leal, A; Campos, R;

Publicação
Proceedings of Text2Story - Fourth Workshop on Narrative Extraction From Texts held in conjunction with the 43rd European Conference on Information Retrieval (ECIR 2021), Lucca, Italy, April 1, 2021 (online event due to Covid-19 outbreak).

Abstract
Narrative Extraction from text is a complex task that starts by identifying a set of narrative elements (actors, events, times), and the semantic links between them (temporal, referential, semantic roles). The outcome is a structure or set of structures which can then be represented graphically, thus opening room for further and alternative exploration of the plot. Such visualization can also be useful during the on-going annotation process. Manual annotation of narratives can be a complex effort and the possibility offered by the Brat annotation tool of annotating directly on the text does not seem sufficiently helpful. In this paper, we propose Brat2Viz, a tool and a pipeline that displays visualization of narrative information annotated in Brat. Brat2Viz reads the annotation file of Brat, produces an intermediate representation in the declarative language DRS (Discourse Representation Structure), and from this obtains the visualization. Currently, we make available two visualization schemes: MSC (Message Sequence Chart) and Knowledge Graphs. The modularity of the pipeline enables the future extension to new annotation sources, different annotation schemes, and alternative visualizations or representations. We illustrate the pipeline using examples from an European Portuguese news corpus. Copyright © by the paper's authors.