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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
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Components of Language01:24

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Frustration occurs when people are obstructed or prevented from achieving a desired goal or fulfilling a perceived need. For example, when someone's input is ignored in a discussion, it can lead to feelings of frustration. Conflict, however, arises from opposing interests, goals, or actions. Conflicts can take various forms based on the nature of these opposing desires or goals.
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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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Video Experimental Relacionado

Updated: Jan 23, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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HealthContradict: Evaluación de conflictos de conocimiento biomédico en modelos de lenguaje

Boya Zhang1, Alban Bornet2, Rui Yang3

  • 1Faculty of Medicine, University of Geneva, Geneva, Switzerland. boya.zhang@unige.ch.

NPJ digital medicine
|January 21, 2026
PubMed
Resumen

Los modelos de lenguaje pueden responder preguntas de salud utilizando el contexto, pero la información conflictiva afecta las respuestas. Los modelos biomédicos ajustados se destacan en el uso del contexto correcto y en la resistencia a la información incorrecta.

Palabras clave:
modelos de lenguajeconocimiento biomédicoconflicto de informaciónrazonamiento contextualmodelos biomédicos

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Área de la Ciencia:

  • Inteligencia Artificial
  • Informática Biomédica
  • Procesamiento del Lenguaje Natural

Sus antecedentes:

  • Los modelos de lenguaje (LM) se utilizan cada vez más para la recuperación de información de salud.
  • Es crucial evaluar el rendimiento de los LM con información biomédica compleja y contradictoria.

Objetivo del estudio:

  • Evaluar cómo los LM razonan sobre contextos biomédicos largos y contradictorios.
  • Evaluar el impacto de diferentes configuraciones contextuales en las respuestas de los LM a preguntas de salud.

Principales métodos:

  • Se utilizó HealthContradict, un conjunto de datos verificado por expertos de 920 instancias con preguntas de salud, respuestas fácticas y documentos contradictorios.
  • Se probaron varias configuraciones de indicaciones, incluidos contextos correctos, incorrectos y contradictorios.
  • Se midió el impacto del contexto en las salidas de los LM.

Principales resultados:

  • El conjunto de datos HealthContradict diferencia las capacidades de razonamiento contextual de los LM de manera más efectiva que los puntos de referencia existentes.
  • Los LM biomédicos ajustados demuestran la capacidad de aprovechar el contexto correcto.
  • Los modelos mostraron resiliencia contra información contextual incorrecta o contradictoria.

Conclusiones:

  • La fortaleza de los LM biomédicos proviene tanto del conocimiento de preentrenamiento como del razonamiento contextual.
  • Los LM pueden utilizar eficazmente información de salud precisa y al mismo tiempo mitigar la influencia de la desinformación.