The Question Answering component answers a question based on a given context (e.g, a paragraph of text), where the answer to the question is a segment of the context.
Named Entity Recognition (NER) classifies tokens in text into predefined categories (tags), such as person names, quantity expressions, percentage expressions, names of locations, organizations, as well as expression of time, currency and others. We can recognize up to 19 entities. NER Beslogic also features a multilingual model that is available for 104 languages. NER Beslogic can be used as a knowledge extractor when you are interested in a piece of certain information in your text.
With the Classification endpoint, you can automatically classify large numbers of documents into a different category.