Named Entity Recognition

Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify elements in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.Most research on NER systems has been structured as taking an unannotated block of text, such as this one:Jim bought 300 shares of Acme Corp. in 2006.And producing an annotated block of text that highlights the names of entities:[Jim]Person bought 300 shares of [Acme Corp.]Organization in [2006]Time.
Posts about Named Entity Recognition
  • Patterns Among Templates Lead to Clues About Entities

    … Extraction with Factzor 2.1.1 Mention Extraction via lists 2.1.2 Mention Extraction Via Templates 2.2 Training Set Extension 2.3 Non-Entities 2.4 Feature Generator 3 Machine Learning 3.1 Feature Screening 3.2 Perceptron Algorithm 3.3 Use of Class Hierarchy 3.4 Error Correcting Output Codes 3.5 Prediction Resolution 4. Results 4.1 Feature Benefit 5…

    Bill Slawski/ SEO by the Seain Google- 6 readers -
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