El endpoint del Analizador de Profanidades devuelve un objeto JSON que contiene los resultados del análisis, incluyendo las profanidades identificadas, toxicidades y otros tipos de lenguaje dañino presentes en el texto de entrada.

Los campos clave en los datos de respuesta típicamente incluyen "análisis_semántico," que proporciona información detallada sobre los tipos de lenguaje dañino detectado, como blasfemias, insultos y amenazas.

Los datos de respuesta están organizados en un formato JSON estructurado. Incluye objetos anidados que categorizan el lenguaje dañino identificado, lo que permite a los usuarios analizar y utilizar la información fácilmente.

El endpoint del Analizador de Groserías acepta parámetros como "texto" (el contenido de entrada a analizar) y configuraciones opcionales para niveles de sensibilidad o filtros de idioma específicos para personalizar el análisis.

Los datos para la detección de profanidades se obtienen de una combinación de bases de datos lingüísticas, contenido generado por usuarios y modelos de aprendizaje automático entrenados en conjuntos de datos diversos para garantizar una cobertura completa del lenguaje ofensivo.

La precisión de los datos se mantiene a través del entrenamiento continuo del modelo, la validación contra ejemplos del mundo real y actualizaciones regulares de los modelos de lenguaje subyacentes para adaptarse al uso del lenguaje y la jerga en evolución.

Los casos de uso típicos incluyen moderar contenido generado por usuarios en redes sociales, filtrar lenguaje ofensivo en chatbots y asegurar una comunicación respetuosa en comunidades de juegos e interacciones de servicio al cliente.

Los usuarios pueden utilizar los datos devueltos implementando acciones de moderación basadas en el lenguaje dañino identificado, como marcar contenido para revisión, censurar automáticamente términos ofensivos o ajustar interacciones de los usuarios en tiempo real.

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