Human Language Technologies: Key Issues for Representing Knowledge from Textual Information

Ontologies are appropriate structures for capturing and representing the knowledge about a domain or task. However, the design and further population of them are both difficult tasks, normally addressed in a manual or in a semi-automatic manner. The goal of this article is to de_ne and extend a task-oriented ontology schema that semantically represents the information contained in texts. This information can be extracted using Human Language Technologies, and throughout this work, the whole process to design such ontology schema is described. Then, we also describe an algorithm to automatically populate ontologies based our Human Language Technology oriented schema, avoiding the unnecessary duplication of instances, and having as a result the required information in a more compact and useful format ready to exploit. Tangible results are provided, such as permanent online access points to the ontology schema, an example bucket (i.e. ontology instance repository) based on a real scenario, and a documentation Web page.This research work has been partially funded by the University of Alicante, Generalitat Valenciana, Spanish Government, Ministerio de Educación, Cultura y Deporte and Ayudas Fundación BBVA a equipos de investigación científica 2016 through the projects TIN2015-65100-R, TIN2015-65136-C2-2-R, PROMETEU/2018/089,“Plataforma inteligente para recuperación, análisis y representación de la información generada por usuarios en Internet” (GRE16-01) and “Análisis de Sentimientos Aplicado a la Prevención del Suicidio en las Redes Sociales” (ASAP)