Rúben Almeida

Also published as: Ruben Almeida


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text2story: A Python Toolkit to Extract and Visualize Story Components of Narrative Text
Evelin Amorim | Ricardo Campos | Alipio Jorge | Pedro Mota | Rúben Almeida
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Story components, namely, events, time, participants, and their relations are present in narrative texts from different domains such as journalism, medicine, finance, and law. The automatic extraction of narrative elements encompasses several NLP tasks such as Named Entity Recognition, Semantic Role Labeling, Event Extraction, Coreference resolution, and Temporal Inference. The text2story python, an easy-to-use modular library, supports the narrative extraction and visualization pipeline. The package contains an array of narrative extraction tools that can be used separately or in sequence. With this toolkit, end users can process free text in English or Portuguese and obtain formal representations, like standard annotation files or a formal logical representation. The toolkit also enables narrative visualization as Message Sequence Charts (MSC), Knowledge Graphs, and Bubble Diagrams, making it useful to visualize and transform human-annotated narratives. The package combines the use of off-the-shelf and custom tools and is easily patched (replacing existing components) and extended (e.g. with new visualizations). It includes an experimental module for narrative element effectiveness assessment and being is therefore also a valuable asset for researchers developing solutions for narrative extraction. To evaluate the baseline components, we present some results of the main annotators embedded in our packages for datasets in English and Portuguese. We also compare the results with the extraction of narrative elements by GPT-3, a robust LLM model.

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Indexing Portuguese NLP Resources with PT-Pump-Up
Rúben Almeida | Ricardo Campos | Alípio Jorge | Sérgio Nunes
Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 2

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A Legal Framework for Natural Language Model Training in Portugal
Ruben Almeida | Evelin Amorim
Proceedings of the Workshop on Legal and Ethical Issues in Human Language Technologies @ LREC-COLING 2024