Cuestiones de reconocimiento automático de homónimos/homoformas en lingüística aplicada
DOI:
https://doi.org/10.18172/cif.6716Palabras clave:
corpus lingüístico, analizador morfológico, algoritmo, pares homográficos, rasgos formalesResumen
El fenómeno de la homonimia crea dificultades adicionales para los procesos de reconocimiento automático de texto, lo que requiere el uso de algoritmos y métodos de procesamiento más complejos. La investigación busca abordar los problemas del reconocimiento automático de homónimos en kazajo, ruso, inglés, turco y tártaro. El estudio identificó los principales problemas que surgen en la detección e identificación automática de homónimos/homoformas, en particular, la falta de una estructura oracional clara (ruso, turco), la significativa diversidad morfológica de la lengua (presencia de un gran número de categorías gramaticales, alto nivel de afijación), la ambigüedad contextual y el insuficiente desarrollo de las cuestiones teóricas del estudio de la homonimia. Se consideraron los métodos más eficaces para distinguir homónimos en corpus nacionales de ruso (modelo de Markov con máxima entropía), inglés (incrustaciones del modelo lingüístico), turco (método híbrido) y tártaro (método de eliminación de homónimos de un corpus marcado con homónimos). El presente estudio se centra en la solución del problema desde la perspectiva del análisis morfológico y sintáctico, y requiere un estudio más detallado de los aspectos semánticos y contextuales.
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Derechos de autor 2026 Akerke Meirbekova, Anar Fazylzhanova, Aiman Zhanabekova, Aigul Amirbekova, Gulnara Talgatkyzy
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