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sulasok1.ner Telegram contact with @sulasoktv @sulasoktv Named Entity Recognition (NER) is a Natural Language Processing (NLP) technique used to identify and extract named entities from text. Named entities are words or phrases that refer to specific. NER, or Named Entity Recognition, consists of identifying the labels to which each word of a sentence belongs. For example, in the sentence "Last week Gandalf visited the Shire", we can consider entities to be "Gandalf" with label "Person" and "Shire" with label "Location". To build a model that'll perform this task, first of all we need a dataset.The named entity recognition (NER) module recognizes mention spans of a particular entity type (e.g., Person or Organization) in the input sentence. NER is widely used in many NLP applications such as information extraction or question answering systems.
Blog title. In the world of Natural Language Processing (NLP), extracting valuable information from text data is a fundamental task. Named Entity Recognition (NER) is the secret sauce behind many .
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