Kontextuskiegészítés

Kontextuskiegészítés, often translated as context completion or context augmentation, refers to a process in linguistics and artificial intelligence where additional information or context is provided to clarify or enrich a given piece of text or data. This process aims to resolve ambiguity, enhance understanding, or facilitate further processing by machines or humans. In natural language processing, kontextuskiegészítés can involve adding semantic labels, identifying named entities, or inferring relationships between words and phrases that are not explicitly stated.

The goal is to make the meaning of the text more explicit and accessible. For example, if a sentence contains a pronoun like "he" or "it," kontextuskiegészítés might involve identifying the noun that the pronoun refers to, thereby completing the context. Similarly, in image analysis, kontextuskiegészítés could involve adding descriptive tags or identifying objects within an image to provide a richer understanding of the scene.

This technique is crucial for improving the performance of various AI applications, including machine translation, question answering systems, and chatbots. By providing a more complete understanding of the input, kontextuskiegészítés enables these systems to generate more accurate and relevant outputs. It is a fundamental step in bridging the gap between raw data and meaningful interpretation, allowing for more sophisticated and human-like interactions with technology.