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Natural Language Processing (NLP) is an area of research and application that explores how to use computers to “understand” and manipulate natural language, such as text or speech. Most NLP techniques rely on machine learning to derive meaning from human languages. One of NLP’s methodologies for processing natural language is text classification, a method that leverages deep learning to categorize sequences of unstructured text.

Named Entity Recognition (NER) is a subtask of information extraction whereby entities in unstructured text are classified into pre-determined categories. You can use the Labelbox Text editor to label characters in a text asset for your Named Entity Recognition (NER) model. You can also create global classifications on a text asset.

Annotation type

Import format

Export format

Entity (NER)

See JSON

See JSON

Radio classification

N/A

See JSON

Checklist classification

N/A

See JSON

Dropdown classification

N/A

See JSON

Free-form text classification

N/A

See JSON