Sepideh Ghanavati


2022

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Proceedings of the Fourth Workshop on Privacy in Natural Language Processing
Oluwaseyi Feyisetan | Sepideh Ghanavati | Patricia Thaine | Ivan Habernal | Fatemehsadat Mireshghallah
Proceedings of the Fourth Workshop on Privacy in Natural Language Processing

2021

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Proceedings of the Third Workshop on Privacy in Natural Language Processing
Oluwaseyi Feyisetan | Sepideh Ghanavati | Shervin Malmasi | Patricia Thaine
Proceedings of the Third Workshop on Privacy in Natural Language Processing

2020

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Proceedings of the Second Workshop on Privacy in NLP
Oluwaseyi Feyisetan | Sepideh Ghanavati | Shervin Malmasi | Patricia Thaine
Proceedings of the Second Workshop on Privacy in NLP

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Populating Legal Ontologies using Semantic Role Labeling
Llio Humphreys | Guido Boella | Luigi Di Caro | Livio Robaldo | Leon van der Torre | Sepideh Ghanavati | Robert Muthuri
Proceedings of the 12th Language Resources and Evaluation Conference

This paper is concerned with the goal of maintaining legal information and compliance systems: the ‘resource consumption bottleneck’ of creating semantic technologies manually. The use of automated information extraction techniques could significantly reduce this bottleneck. The research question of this paper is: How to address the resource bottleneck problem of creating specialist knowledge management systems? In particular, how to semi-automate the extraction of norms and their elements to populate legal ontologies? This paper shows that the acquisition paradox can be addressed by combining state-of-the-art general-purpose NLP modules with pre- and post-processing using rules based on domain knowledge. It describes a Semantic Role Labeling based information extraction system to extract norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in legal document management systems such as Eunomos (Boella et al., 2016).