Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones

Autores:: Peña Torres, Jefferson A.
Bucheli, Víctor
Gutiérrez de Piñérez Reyes, Raúl E.

Tipo de recurso:: Article of journal

Fecha de publicación:: 2022

Institución:: Universidad Pedagógica y Tecnológica de Colombia

Repositorio:: RiUPTC: Repositorio Institucional UPTC

Idioma:

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dc.title.spa.fl_str_mv	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
title	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
spellingShingle	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones Lingüística informática Traducción automática Lingüística de corpus Extracción de relaciones Computer linguistics Machine translation Corpus linguistics Relations extraction Linguistique informatique Traduction automatique Linguistique de corpus Prélèvement de relations Linguística computacional Tradução automática Linguística de corpus Extração de relações
title_short	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
title_full	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
title_fullStr	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
title_full_unstemmed	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
title_sort	Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones
dc.creator.fl_str_mv	Peña Torres, Jefferson A. Bucheli, Víctor Gutiérrez de Piñérez Reyes, Raúl E.
dc.contributor.author.eng.fl_str_mv	Peña Torres, Jefferson A. Bucheli, Víctor Gutiérrez de Piñérez Reyes, Raúl E.
dc.subject.none.fl_str_mv	Lingüística informática Traducción automática Lingüística de corpus Extracción de relaciones Computer linguistics Machine translation Corpus linguistics Relations extraction Linguistique informatique Traduction automatique Linguistique de corpus Prélèvement de relations Linguística computacional Tradução automática Linguística de corpus Extração de relações
topic	Lingüística informática Traducción automática Lingüística de corpus Extracción de relaciones Computer linguistics Machine translation Corpus linguistics Relations extraction Linguistique informatique Traduction automatique Linguistique de corpus Prélèvement de relations Linguística computacional Tradução automática Linguística de corpus Extração de relações
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-02-07 00:00:00 2026-04-16T17:17:39Z
dc.date.available.none.fl_str_mv	2022-02-07 00:00:00
dc.date.issued.none.fl_str_mv	2022-02-07
dc.type.spa.fl_str_mv	Artículo de revista
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dc.relation.references.none.fl_str_mv	Ananthram, A., Allaway, E., & McKeown, K. (2020). Event Guided Denoising for Multilingual Relation Learning. arXiv preprint: arXiv:2012.02721. https://doi.org/10.18653/v1/2020.coling-main.131 Anastasopoulos, A. (2019). An Analysis of Source-Side Grammatical Errors in NMT. arXiv preprint: arXiv:1905.10024. Bach, N., & Sameer, B. (2007). A Survey on Relation Extraction. Language Technologies Institute, Carnegie Mellon University 178. https://doi.org/10.1007/978-981-10-7359-5_6 Bahr, R. H., Lebby, S., & Wilkinson, L. C. (2020). Spelling Error Analysis of Written Summaries in an Academic Register by Students with Specific Learning Disabilities: Phonological, Orthographic, and Morphological Influences. Reading and Writing, 33(1), 121-142. https://doi.org/10.1007/s11145-019-09977-0 Belinkov, Y., & Glass, J. (2019). Analysis Methods in Neural Language Processing: A Survey. Transactions of the Association for Computational Linguistics, 7, 49-72. https://doi.org/10.1162/tacl_a_00254 Carrino, C. P., Costa-Jussà, M. R., & Fonollosa, J. A. (2020). Automatic Spanish Translation of SQuAD Dataset for Multilingual Question Answering. In Proceedings of the 12th Language Resources and Evaluation Conference (5515-5523). Castillo, M. N. (2020). Corpus Básico del Español de Chile ©: metodología de procesamiento y análisis. Lexis, 44(2), 483-523. https://doi.org/10.18800/lexis.202002.004 Cheng, Y. (2019). Neural Machine Translation. In Joint Training for Neural Machine Translation (1-10). Springer. https://doi.org/10.1007/978-981-32-9748-7_1 Collantes, C., Mallo, J., Parra, C., Quiñones, H. & Serrano, R. (2018). Pásate al lado oscuro: ventajas de la traducción automática para el traductor profesional. La Linterna del Traductor, 17, 33-39. Gamallo, P., & García, M. (2017). LinguaKit: Uma ferramenta multilingue para a análise linguística e a extração de informação. Linguamática, 9(1), 19-28. https://doi.org/10.21814/lm.9.1.243 Guan, H., Li, J., Xu, H., & Devarakonda, M. (2020). Robustly Pre-trained Neural Model for Direct Temporal Relation Extraction. arXiv preprint: arXiv:2004.06216. https://doi.org/10.1109/ICHI52183.2021.00090 Gurulingappa, H., Rajput, A. M., Roberts, A., Fluck, J., Hofmann-Apitius, M., & Toldo, L. (2012). Development of a Benchmark Corpus to Support the Automatic Extraction of Drug-Related Adverse Effects from Medical Case Reports. Journal of Biomedical Informatics, 45(5), 885–892. https://doi.org/10.1016/j.jbi.2012.04.008 Hachey, B., Grover, C., & Tobin, R. (2012). Datasets for Generic Relation Extraction. Natural Language Engineering, 18(1), 21–59. http://dx.doi.org/10.1017/S1351324911000106 Haque, R., Hasanuzzaman, M., & Way, A. (2020). Analysing Terminology Translation Errors in Statistical and Neural Machine Translation. Machine Translation, 34(2), 149-195. https://doi.org/10.1007/s10590-02009251-z Hidalgo-Ternero, C. M. (2021). Google Translate vs. DeepL. MonTI. Monografías de Traducción e Interpretación, 154-177. Kramer, O. (2016). Scikit-learn. In Machine learning for evolution strategies. Studies in Big Data, vol 20 (pp. 45-53). Springer, Cham. https://doi.org/10.1007/978-3-319-33383-0_5 Kumar, S. (2017). A Survey of Deep Learning Methods for Relation Extraction. arXiv preprint: arXiv:1705.03645. Lin, Y., Liu, Z., & Sun, M. (2017). Neural Relation Extraction with Multi-Lingual Attention. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 34–43. Association for Computational Linguistics. http://dx.doi.org/10.18653/v1/P17-1004 Mesquita, F., Schmidek, J., & Barbosa, D. (2013). Effectiveness and Efficiency of Open Relation Extraction. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 447-457. Association for Computational Linguistics. Mikelenić, B., & Tadić, M. (2020). Building the Spanish-Croatian Parallel Corpus. In Proceedings of the 12th Language Resources and Evaluation Conference, 3932-3936. European Language Resources Association Mitchell, A., Strassel, S., Huang, S., & Zakhary, R. (2005). Ace 2004 Multilingual Training Corpus. Linguistic Data Consortium, Philadelphia, 1, 1-1. Nasar, Z., Jaffry, S. W., & Malik, M. K. (2021). Named Entity Recognition and Relation Extraction: State-of-the-Art. ACM Computing Surveys (CSUR), 54(1), 1-39. https://doi.org/10.1145/3445965 Ni, J., & Florian, R. (2019). Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping. arXiv preprint: arXiv:1911.00069. https://doi.org/10.18653/v1/D19-1038 Pastor, G. C. (2018). Laughing One’s Head Off in Spanish Subtitles: A Corpus-Based Study on Diatopic Variation and Its Consequences for Translation1. Fraseología, Diatopía y Traducción/Phraseology, Diatopic Variation and Translation, 17, 32. https://doi.org/10.1075/ivitra.17.03co Pawar, S., Palshikar, G. K., & Bhattacharyya, P. (2017). Relation Extraction: A Survey. arXiv preprint: arXiv:1712.05191. Popović, M. (2020). Relations Between Comprehensibility and Adequacy Errors in Machine Translation Output. In Proceedings of the 24th Conference on Computational Natural Language Learning, (pp. 256-264). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.conll-1.19 Pyysalo, S., Ginter, F., Heimonen, J., Björne, J., Boberg, J., Järvinen, J., & Salakoski, T. (2007). BioInfer: A Corpus for Information Extraction in the Biomedical Domain. BMC Bioinformatics, 8(1), 50. https://doi.org/10.1186/1471-2105-8-50 Rodrigues, J., & Branco, A. (2020). Argument Identification in a Language Without Labeled Data. In International Conference on Computational Processing of the Portuguese Language, (pp. 335-345). https://doi.org/10.1007/978-3-030-41505-1_32 Sánchez, A. (2010). Traducción automática, corpus lingüísticos y desambiguación automática de los significados de las palabras. En R. Rabadán, M. Fernández & T. Guzmán (coords.), Lengua, traducción, recepción: en honor de Julio César Santoyo, vol. 1 (pp. 555-587). Universidad de León, Área de Publicaciones. Smirnova, A., & Cudré-Mauroux, P. (2018). Relation Extraction Using Distant Supervision: A Survey. ACM Computing Surveys (CSUR), 51(5), 1-35. https://doi.org/10.1145/3241741 Torres, J. P., De Piñérez Reyes, R. G., & Bucheli, V. A. (2018). Support Vector Machines for Semantic Relation Extraction in Spanish Language. Colombian Conference on Computing, 326-337. https://doi.org/10.1007/978-3-319-98998- 3_26 Verga, P., Belanger, D., Strubell, E., Roth, B., & McCallum, A. (2015). Multilingual Relation Extraction Using Compositional Universal Schema. arXiv preprint: arXiv:1511.06396. https://doi.org/10.18653/v1/N16-1103 Virmani, C., Pillai, A., & Juneja, D. (2017). Extracting Information from Social Networks Using NLP. International Journal of Computational Intelligence Research, 13(4), 621-630. Walker, C., Strassel, S., Medero, J., & Maeda, K. (2006). ACE 2005 Multilingual Training Corpus. Linguistic Data Consortium. https://doi.org/10.35111/mwxc-vh88 Wu, Y., Schuster, M., Chen, Z., Le, Q., Norouzi, M., Machery, W., Krikun, M. et al. (2016). Google’s Neural Machine Translation System: Bridging the Gap Between Human and Machine Translation. arXiv preprint: arXiv:1609.08144. Yamada, M. (2019). The Impact of Google Neural Machine Translation on Post-Editing by Student Translators. The Journal of Specialised Translation, 31, 87-106. Zelenko, D., Chinatsu, A., and Anthony, R. (2003, Feb.). Kernel Methods for Relation Extraction. Journal of Machine Learning Research, 3, 1083-1106. https://dl.acm.org/doi/10.3115/1118693.1118703 Zhang, Q., Mengdong C., and Lianzhong, L. (2017). A Review on Entity Relation Extraction. In 2017 Second International Conference on Mechanical, Control and Computer Engineering (ICMCCE). IEEE. https://doi.org/10.1109/ICMCCE.2017.14 Zhila, A., & Gelbukh, A. (2013). Comparison of Open Information Extraction for Spanish and English. Computational Linguistics and Intellectual Technologies, 12(1), 794-802.
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spelling	Peña Torres, Jefferson A.Bucheli, VíctorGutiérrez de Piñérez Reyes, Raúl E.2022-02-07 00:00:002026-04-16T17:17:39Z2022-02-07 00:00:002022-02-070121-053Xhttps://repositorio.uptc.edu.co/handle/001/1922810.19053/0121053X.n39.2022.134362346-1829https://doi.org/10.19053/0121053X.n39.2022.13436text/xmlapplication/pdfUniversidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/linguistica_hispanica/article/view/13436Lingüística informáticaTraducción automáticaLingüística de corpusExtracción de relacionesComputer linguisticsMachine translationCorpus linguisticsRelations extractionLinguistique informatiqueTraduction automatiqueLinguistique de corpusPrélèvement de relationsLinguística computacionalTradução automáticaLinguística de corpusExtração de relaçõesTraducción automática de un conjunto de entrenamiento para extracción semántica de relacionesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85Ananthram, A., Allaway, E., & McKeown, K. (2020). Event Guided Denoising for Multilingual Relation Learning. arXiv preprint: arXiv:2012.02721. https://doi.org/10.18653/v1/2020.coling-main.131Anastasopoulos, A. (2019). An Analysis of Source-Side Grammatical Errors in NMT. arXiv preprint: arXiv:1905.10024.Bach, N., & Sameer, B. (2007). A Survey on Relation Extraction. Language Technologies Institute, Carnegie Mellon University 178. https://doi.org/10.1007/978-981-10-7359-5_6Bahr, R. H., Lebby, S., & Wilkinson, L. C. (2020). Spelling Error Analysis of Written Summaries in an Academic Register by Students with Specific Learning Disabilities: Phonological, Orthographic, and Morphological Influences. Reading and Writing, 33(1), 121-142. https://doi.org/10.1007/s11145-019-09977-0Belinkov, Y., & Glass, J. (2019). Analysis Methods in Neural Language Processing: A Survey. Transactions of the Association for Computational Linguistics, 7, 49-72. https://doi.org/10.1162/tacl_a_00254Carrino, C. P., Costa-Jussà, M. R., & Fonollosa, J. A. (2020). Automatic Spanish Translation of SQuAD Dataset for Multilingual Question Answering. In Proceedings of the 12th Language Resources and Evaluation Conference (5515-5523).Castillo, M. N. (2020). Corpus Básico del Español de Chile ©: metodología de procesamiento y análisis. Lexis, 44(2), 483-523. https://doi.org/10.18800/lexis.202002.004Cheng, Y. (2019). Neural Machine Translation. In Joint Training for Neural Machine Translation (1-10). Springer. https://doi.org/10.1007/978-981-32-9748-7_1Collantes, C., Mallo, J., Parra, C., Quiñones, H. & Serrano, R. (2018). Pásate al lado oscuro: ventajas de la traducción automática para el traductor profesional. La Linterna del Traductor, 17, 33-39.Gamallo, P., & García, M. (2017). LinguaKit: Uma ferramenta multilingue para a análise linguística e a extração de informação. Linguamática, 9(1), 19-28. https://doi.org/10.21814/lm.9.1.243Guan, H., Li, J., Xu, H., & Devarakonda, M. (2020). Robustly Pre-trained Neural Model for Direct Temporal Relation Extraction. arXiv preprint: arXiv:2004.06216. https://doi.org/10.1109/ICHI52183.2021.00090Gurulingappa, H., Rajput, A. M., Roberts, A., Fluck, J., Hofmann-Apitius, M., & Toldo, L. (2012). Development of a Benchmark Corpus to Support the Automatic Extraction of Drug-Related Adverse Effects from Medical Case Reports. Journal of Biomedical Informatics, 45(5), 885–892. https://doi.org/10.1016/j.jbi.2012.04.008Hachey, B., Grover, C., & Tobin, R. (2012). Datasets for Generic Relation Extraction. Natural Language Engineering, 18(1), 21–59. http://dx.doi.org/10.1017/S1351324911000106Haque, R., Hasanuzzaman, M., & Way, A. (2020). Analysing Terminology Translation Errors in Statistical and Neural Machine Translation. Machine Translation, 34(2), 149-195. https://doi.org/10.1007/s10590-02009251-zHidalgo-Ternero, C. M. (2021). Google Translate vs. DeepL. MonTI. Monografías de Traducción e Interpretación, 154-177.Kramer, O. (2016). Scikit-learn. In Machine learning for evolution strategies. Studies in Big Data, vol 20 (pp. 45-53). Springer, Cham. https://doi.org/10.1007/978-3-319-33383-0_5Kumar, S. (2017). A Survey of Deep Learning Methods for Relation Extraction. arXiv preprint: arXiv:1705.03645.Lin, Y., Liu, Z., & Sun, M. (2017). Neural Relation Extraction with Multi-Lingual Attention. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 34–43. Association for Computational Linguistics. http://dx.doi.org/10.18653/v1/P17-1004Mesquita, F., Schmidek, J., & Barbosa, D. (2013). Effectiveness and Efficiency of Open Relation Extraction. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 447-457. Association for Computational Linguistics.Mikelenić, B., & Tadić, M. (2020). Building the Spanish-Croatian Parallel Corpus. In Proceedings of the 12th Language Resources and Evaluation Conference, 3932-3936. European Language Resources AssociationMitchell, A., Strassel, S., Huang, S., & Zakhary, R. (2005). Ace 2004 Multilingual Training Corpus. Linguistic Data Consortium, Philadelphia, 1, 1-1.Nasar, Z., Jaffry, S. W., & Malik, M. K. (2021). Named Entity Recognition and Relation Extraction: State-of-the-Art. ACM Computing Surveys (CSUR), 54(1), 1-39. https://doi.org/10.1145/3445965Ni, J., & Florian, R. (2019). Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping. arXiv preprint: arXiv:1911.00069. https://doi.org/10.18653/v1/D19-1038Pastor, G. C. (2018). Laughing One’s Head Off in Spanish Subtitles: A Corpus-Based Study on Diatopic Variation and Its Consequences for Translation1. Fraseología, Diatopía y Traducción/Phraseology, Diatopic Variation and Translation, 17, 32. https://doi.org/10.1075/ivitra.17.03coPawar, S., Palshikar, G. K., & Bhattacharyya, P. (2017). Relation Extraction: A Survey. arXiv preprint: arXiv:1712.05191.Popović, M. (2020). Relations Between Comprehensibility and Adequacy Errors in Machine Translation Output. In Proceedings of the 24th Conference on Computational Natural Language Learning, (pp. 256-264). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.conll-1.19Pyysalo, S., Ginter, F., Heimonen, J., Björne, J., Boberg, J., Järvinen, J., & Salakoski, T. (2007). BioInfer: A Corpus for Information Extraction in the Biomedical Domain. BMC Bioinformatics, 8(1), 50. https://doi.org/10.1186/1471-2105-8-50Rodrigues, J., & Branco, A. (2020). Argument Identification in a Language Without Labeled Data. In International Conference on Computational Processing of the Portuguese Language, (pp. 335-345). https://doi.org/10.1007/978-3-030-41505-1_32Sánchez, A. (2010). Traducción automática, corpus lingüísticos y desambiguación automática de los significados de las palabras. En R. Rabadán, M. Fernández & T. Guzmán (coords.), Lengua, traducción, recepción: en honor de Julio César Santoyo, vol. 1 (pp. 555-587). Universidad de León, Área de Publicaciones.Smirnova, A., & Cudré-Mauroux, P. (2018). Relation Extraction Using Distant Supervision: A Survey. ACM Computing Surveys (CSUR), 51(5), 1-35. https://doi.org/10.1145/3241741Torres, J. P., De Piñérez Reyes, R. G., & Bucheli, V. A. (2018). Support Vector Machines for Semantic Relation Extraction in Spanish Language. Colombian Conference on Computing, 326-337. https://doi.org/10.1007/978-3-319-98998- 3_26Verga, P., Belanger, D., Strubell, E., Roth, B., & McCallum, A. (2015). Multilingual Relation Extraction Using Compositional Universal Schema. arXiv preprint: arXiv:1511.06396. https://doi.org/10.18653/v1/N16-1103Virmani, C., Pillai, A., & Juneja, D. (2017). Extracting Information from Social Networks Using NLP. International Journal of Computational Intelligence Research, 13(4), 621-630.Walker, C., Strassel, S., Medero, J., & Maeda, K. (2006). ACE 2005 Multilingual Training Corpus. Linguistic Data Consortium. https://doi.org/10.35111/mwxc-vh88Wu, Y., Schuster, M., Chen, Z., Le, Q., Norouzi, M., Machery, W., Krikun, M. et al. (2016). Google’s Neural Machine Translation System: Bridging the Gap Between Human and Machine Translation. arXiv preprint: arXiv:1609.08144.Yamada, M. (2019). The Impact of Google Neural Machine Translation on Post-Editing by Student Translators. The Journal of Specialised Translation, 31, 87-106.Zelenko, D., Chinatsu, A., and Anthony, R. (2003, Feb.). Kernel Methods for Relation Extraction. Journal of Machine Learning Research, 3, 1083-1106. https://dl.acm.org/doi/10.3115/1118693.1118703Zhang, Q., Mengdong C., and Lianzhong, L. (2017). A Review on Entity Relation Extraction. In 2017 Second International Conference on Mechanical, Control and Computer Engineering (ICMCCE). IEEE. https://doi.org/10.1109/ICMCCE.2017.14Zhila, A., & Gelbukh, A. (2013). Comparison of Open Information Extraction for Spanish and English. Computational Linguistics and Intellectual Technologies, 12(1), 794-802.16391Cuadernos de Lingüística Hispánicahttps://revistas.uptc.edu.co/index.php/linguistica_hispanica/article/download/13436/12999https://revistas.uptc.edu.co/index.php/linguistica_hispanica/article/download/13436/11480Núm. 39 , Año 2022 : Continuous publicationPublicationOREORE.xmltext/xml2755https://repositorio.uptc.edu.co/bitstreams/5df13512-890c-4c5e-806e-4ee954b970d3/downloadc1bf6c9d98c1ba122180b9ffe590c615MD51falseAnonymousREAD001/19228oai:repositorio.uptc.edu.co:001/192282026-09-24 16:18:22.311https://creativecommons.org/licenses/by-nc-nd/4.0/metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com

Traducción automática de un conjunto de entrenamiento para extracción semántica de relaciones

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