Legal NERC with ontologies, Wikipedia and curriculum learning
Ponencia presentada en la 15th European Chapter of the Association for Computational Linguistics (EACL 2017), 2017, Valencia, Spain. pp.254 - 259, 2017.
| Main Authors: | , , , |
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| Format: | conferenceObject |
| Language: | eng |
| Published: |
2024
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| Online Access: | http://hdl.handle.net/11086/552665 |
| _version_ | 1806012190335959040 |
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| 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 en la 15th European Chapter of the Association for Computational Linguistics (EACL 2017), 2017, Valencia, Spain. pp.254 - 259, 2017. |
| format | conferenceObject |
| id | rdu-unc.552665 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2024 |
| record_format | dspace |
| spelling | rdu-unc.5526652024-07-11T19:12:38Z Legal NERC with ontologies, Wikipedia and curriculum learning Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena Ontologies Natural language processing Legal informatics Information extraction Ponencia presentada en la 15th European Chapter of the Association for Computational Linguistics (EACL 2017), 2017, Valencia, Spain. pp.254 - 259, 2017. 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 a Wikipediabased approach to develop resources for the legal domain. We establish a mapping between a legal domain ontology, LKIF (Hoekstra et al., 2007), and a Wikipediabased ontology, YAGO (Suchanek et al., 2007), and through that we populate LKIF. Moreover, we use the mentions of those entities in Wikipedia text to train a specific Named Entity Recognizer and Classifier. We find that this classifier works well in the Wikipedia, but, as could be expected, performance decreases in a corpus of judgments of the European Court of Human Rights. However, this tool will be used as a preprocess for human annotation. We resort to a technique called curriculum learning aimed to overcome problems of overfitting by learning increasingly more complex concepts. However, we find that in this particular setting, the method works best by learning from most specific to most general concepts, not the other way round. http://aclanthology.info/papers/E17-2041/legal-nerc-with-ontologies-wikipedia-and-curriculum-learning 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 2024-07-10T18:42:23Z 2024-07-10T18:42:23Z 2017 conferenceObject http://hdl.handle.net/11086/552665 eng https://hal.science/hal-01572444 Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Electrónico y/o Digital |
| spellingShingle | Ontologies Natural language processing Legal informatics Information extraction Cardellino, Cristian Teruel, Milagro Alonso Alemany, Laura Villata, Serena Legal NERC with ontologies, Wikipedia and curriculum learning |
| title | Legal NERC with ontologies, Wikipedia and curriculum learning |
| title_full | Legal NERC with ontologies, Wikipedia and curriculum learning |
| title_fullStr | Legal NERC with ontologies, Wikipedia and curriculum learning |
| title_full_unstemmed | Legal NERC with ontologies, Wikipedia and curriculum learning |
| title_short | Legal NERC with ontologies, Wikipedia and curriculum learning |
| title_sort | legal nerc with ontologies wikipedia and curriculum learning |
| topic | Ontologies Natural language processing Legal informatics Information extraction |
| url | http://hdl.handle.net/11086/552665 |
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