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

Jefferson A. Peña Torres; Victor  Bucheli; Raúl  Gutiérrez de Piñerez Reyes

doi:10.19053/0121053X.n39.2022.13436

Authors

Jefferson A. Peña Torres Universidad del Valle https://orcid.org/0000-0002-3879-3320
Victor Bucheli Universidad del Valle https://orcid.org/0000-0002-0885-8699
Raúl Gutiérrez de Piñerez Reyes Universidad del Valle https://orcid.org/0000-0001-9941-6206

DOI:

https://doi.org/10.19053/0121053X.n39.2022.13436

Keywords:

computer linguistics, machine translation, corpus linguistics, relations extraction

Abstract

Machine translation (MT) is used to obtain annotated corpus of English corpus which can be applicable to different natural language processing (NLP) tasks. Considering that there are more resources or data sets for training NLP models in
English language, this paper explores the application of MT to automate NLP tasks in
Spanish. Thus, the article describes a dataset for the extraction of generic relations (reACE) and the construction of a semantic extraction model of relations in Spanish (ER), based on the set of samples translated from English to Spanish. The results show that for the MT task it is necessary to implement a corpus preediting process in English to avoid translation and post-editing errors and maintain the original corpus annotations. The ER models in Spanish achieve measures of accuracy, completeness, and F-value comparable to those obtained by the model in the English language, which suggests that machine translation is a useful tool to perform NLP tasks in the Spanish language.

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