entitásjelölés

Entitásjelölés is a process in natural language processing (NLP) that identifies and categorizes key information or named entities within a text. These entities can include people, organizations, locations, dates, quantities, and other specific types of information. The goal of entitásjelölés is to extract structured data from unstructured text, making it easier to analyze and understand.

The process typically involves two main steps: identifying the boundaries of the entity within the text and then assigning a predefined category to it. For example, in the sentence "Budapest is the capital of Hungary," entitásjelölés would identify "Budapest" as a location and "Hungary" as a location. The accuracy of entitásjelölés systems depends on the quality of the training data and the sophistication of the algorithms used.

Entitásjelölés has numerous applications. It is crucial for information retrieval systems, allowing them to quickly find relevant documents based on specific entities. It is also used in sentiment analysis to understand opinions expressed about particular entities, in machine translation to ensure correct translation of proper nouns, and in question answering systems to extract answers from text. Furthermore, it plays a role in data anonymization and the creation of knowledge graphs. Different languages present unique challenges for entitásjelölés due to variations in grammar, word order, and the prevalence of ambiguous terms.