Fénix: a flexible information exchange data model for natural language processing

In this paper we describe Fénix, a data model for exchanging information between Natural Language Processing applications. The format proposed is intended to be flexible enough to cover both current and future data structures employed in the field of Computational Linguistics. The Fénix architecture is divided into four separate layers: conceptual, logical, persistence and physical. This division provides a simple interface to abstract the users from low-level implementation details, such as programming languages and data storage employed, allowing them to focus in the concepts and processes to be modelled. The Fénix architecture is accompanied by a set of programming libraries to facilitate the access and manipulation of the structures created in this framework. We will also show how this architecture has been already successfully applied in different research projects.

A proposal for teaching with authentic texts in order to develop social awareness in a language subject in tertiary education

The University of the 21st century has to establish links with society and prepare students for the demands of the working world. Therefore, this article is a contribution to the integral preparation of university students by proposing the use of authentic texts with social content in English lessons so that students acquire emotional and social competencies while still learning content. This article will explain how the choice of texts on global issues such as racism and gender helps students to develop skills such as social awareness and critical thinking to deepen their understanding of discrimination, injustice or gender differences in both oral and written activities. A proposal will be presented which involves using the inauguration speech from Mandela's presidency and texts with photographs of women so that students analyse them whilst utilising linguistic tools that allow them to explore a text's social dimension.