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Artificial Intelligence Task

Named Entity Recognition

Identifying and classifying entities in natural language into predefined categories such as names, locations, organizations, and numerical expressions. NER capable models are able to analyze the context and semantic nuances in the corpus to determine the appropriate category for each entity.

Input

Unstructured data, likely Natural Human Language in the form of text or images.

Output

Identification of named entities among different types (persons, organizations, locations)

Goal

To extract structured data from unstructured text to identify entities that may be pre-structured

Learning Strategy

Supervised NLP task training on pre trained models

Evaluation Metric

Accuracy, Reccall, F1 score over gold labels

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