| Resumen |
The following work has the purpose of describing the participation in the SimpleText 2023 track, on the identification of the term and its identification of the terms and their difficulty as a term, among themselves, all this belonging to Task 2. To solve this task, we used an approach of language models using Bloom but opted for its BLOOMZ version for a fine-tuning more focused on human instructions or in a more understandable way with more description-style prompts given by text input on a task. To solve the handling of the difficulty between terms a very simple classifier based on BERT-multilingual was used since this was developed as a binary classification and for the term vs. term evaluation a small algorithm was taken to accommodate the internal term classifications. On the other hand, we also participated in Task 3 in which the objective was to simplify passages extracted from abstracts, using the same approach as Task 2, BLOOMZ was used for the simplification of this text since different prompts were tested in case it was necessary to make several passes with those parts that yielded poor results or null results. Given that this was the first time participating in such tasks we can say that the results obtained were quite satisfactory even though we believe that they can be substantially improved with some other approach, which would have to be further reviewed. © 2023 Copyright for this paper by its authors. |
