Text analysis from the point of view of text grammars
ANALYSIS OF REFERENCE This function of the programme allows you to find, classify and label references in a given text. These labels are differentiated by colour, visual markers such as underlining and bolding, and their respective categorization in brackets to the right of the reference found.
About references
The main characteristic of a genuine text is coherence, and one of the manifestations of this is the repetition of a specific set of names designated as the references of the text, that is, the main objects or themes of the text (De Beaugrande and Dressler, 1997; Calsamiglia and Tusón, 1999; Cuenca, 2010). The senders constantly refers to previously mentioned concepts but also introduces new ones as they progress, a phenomenon known as semantic isotopy (Lozano, Peña-Marín & Abril, 1989).
Classification
As mentioned above, this TEXT·A·GRAM function seeks to label the referents found in a given text. Currently, referents are identified based on their repetition throughout the text.
In the case of proper names, the system classifies them as people, places or organizations. In the case of common names, it attempts to classify them according to the Kind taxonomy project (http://www.tecling.com/kind).
References
Calsamiglia, H. & Tusón, A. (1999). Las cosas del decir. Barcelona: Editorial Ariel.
Cuenca, M. J. (2010). Gramática del texto. Madrid: Arco libros.
De Beaugrande, R. A. & Dressler, W. U. (1997). Introducción a la lingüística del texto. Barcelona: Editorial Ariel.
Lozano, J., Peña-Marín, C. & Abril, G. (1989). Análisis del discurso: Hacia una semiótica de la interacción textual. Madrid: Cátedra.
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This is another product of Group Tecling.com
There will soon be a paper describing the new version semantic tagger (the one we have not yet installed here but will soon):
• Nazar, R.; Renau, I. (In press). Wikipedia used as a semantic tagger: some preliminary results in Spanish.
Procesamiento del Lenguaje Natural, n. 76.
These other papers describe the rest of the text analyses performed by the software:
• Nazar, R. (2024). Statistical modeling of discourse genres: the case of the opinion column in Spanish. SN Computer Science 5(959):1-11.
• Nazar, R.; Renau, I.; Robledo, H. (2024). Dismark and Text·a·Gram: Automatic identification and categorization of discourse markers in texts. In: Cecilia-Mihaela Popescu & Oana-Adriana Dut,ă (eds.), Discourse Markers in Romance Languages. Crosslinguistic Approaches in Romance and Beyond. Berlin: Peter Lang.
Concept and development: Rogelio Nazar
Collaborators: Javier Obreque, Diego Sánchez, Hernán Robledo, Paolo Caballería, Nicolás Acosta, Scarlette Gatica, Andrea Alcaíno, Ignacio Lobos and Irene Renau.
Documentation: Andrea Alcaíno & Rogelio Nazar