1 code implementation • LREC 2022 • Igor Nascimento, Rinaldo Lima, Adrian-Gabriel Chifu, Bernard Espinasse, Sébastien Fournier
There are many studies in this subarea of NLP that continue to be explored, such as SemEval campaigns (2010 to 2018), or DDI Extraction (2013). For more than ten years, different RE systems using mainly statistical models have been proposed as well as the frameworks to develop them.
no code implementations • LREC 2020 • Francisco Rodrigues, Rinaldo Lima, William Domingues, Robson Fidalgo, Adrian Chifu, Bernard Espinasse, S{\'e}bastien Fournier
Natural Language Processing (NLP) of textual data is usually broken down into a sequence of several subtasks, where the output of one the subtasks becomes the input to the following one, which constitutes an NLP pipeline.
no code implementations • 13 Jan 2020 • Rinaldo Lima, Bernard Espinasse, Fred Freitas
In this work, we present OntoILPER, a logic-based relational learning approach to Relation Extraction that uses Inductive Logic Programming for generating extraction models in the form of symbolic extraction rules.
no code implementations • RANLP 2019 • Rinaldo Lima, Bernard Espinasse, Frederico Freitas
Relation Extraction (RE) consists in detecting and classifying semantic relations between entities in a sentence.