Learning slowly to learn better : curriculum learning for legal ontology population
Ponencia presentada Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference
| Main Authors: | , , , |
|---|---|
| Format: | conferenceObject |
| Language: | eng |
| Published: |
2024
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/11086/552703 |
| _version_ | 1806012321779154944 |
|---|---|
| author | Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena |
| author_facet | Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena |
| author_sort | Cardellino, Cristian |
| collection | Repositorio Digital Universitario |
| description | Ponencia presentada Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference |
| format | conferenceObject |
| id | rdu-unc.552703 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2024 |
| record_format | dspace |
| spelling | rdu-unc.5527032024-07-12T06:33:22Z Learning slowly to learn better : curriculum learning for legal ontology population Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena Ontologías Procesamiento del lenguaje natural Informática legal Deep learning Ponencia presentada Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference Fil: Cardellino, Cristian. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Teruel, Milagro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Alonso Alemany, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Alonso Alemany, Laura. Universite Cote d’Azur; France. In this paper, we present an ontology population approach for legal ontologies. We exploit Wikipedia as a source of manually annotated examples of legal entities. We align YAGO, a Wikipedia-based ontology, and LKIF, an ontology specifically designed for the legal domain. Through this alignment, we can effectively populate the LKIF ontology, with the aim to obtain examples to train a Named Entity Recognizer and Classifier to be used for finding and classifying entities in legal texts. Since examples of annotated data in the legal domain are very few, we apply a machine learning strategy called curriculum learning aimed to overcome problems of overfitting by learning increasingly more complex concepts. We compare the performance of this method to identify Named Entities with respect to batch learning as well as two other baselines. Results are satisfying and foster further research in this direction. https://aaai.org/ocs/index.php/FLAIRS/FLAIRS17/paper/view/15526 Fil: Cardellino, Cristian. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Teruel, Milagro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Alonso Alemany, Laura. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: Alonso Alemany, Laura. Universite Cote d’Azur; France. Otras Ciencias de la Computación e Información 2024-07-11T18:57:49Z 2024-07-11T18:57:49Z 2017 conferenceObject 978-157735787-2 http://hdl.handle.net/11086/552703 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Electrónico y/o Digital |
| spellingShingle | Ontologías Procesamiento del lenguaje natural Informática legal Deep learning Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena Learning slowly to learn better : curriculum learning for legal ontology population |
| title | Learning slowly to learn better : curriculum learning for legal ontology population |
| title_full | Learning slowly to learn better : curriculum learning for legal ontology population |
| title_fullStr | Learning slowly to learn better : curriculum learning for legal ontology population |
| title_full_unstemmed | Learning slowly to learn better : curriculum learning for legal ontology population |
| title_short | Learning slowly to learn better : curriculum learning for legal ontology population |
| title_sort | learning slowly to learn better curriculum learning for legal ontology population |
| topic | Ontologías Procesamiento del lenguaje natural Informática legal Deep learning |
| url | http://hdl.handle.net/11086/552703 |
| work_keys_str_mv | AT cardellinocristian learningslowlytolearnbettercurriculumlearningforlegalontologypopulation AT teruelmilagro learningslowlytolearnbettercurriculumlearningforlegalontologypopulation AT alonsoalemanylaura learningslowlytolearnbettercurriculumlearningforlegalontologypopulation AT villataserena learningslowlytolearnbettercurriculumlearningforlegalontologypopulation |