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Data is sourced from national business registries in 140 jurisdictions, and presented in a standardised form. Collected data comprises the name of the entity, date of incorporation, registered addresses, and the names of directors. Some data, such as the ownership structure, is contributed by users. [5] [6]
In natural language processing, Entity Linking, also referred to as named-entity disambiguation (NED), named-entity recognition and disambiguation (NERD), named-entity normalization (NEN), [1] or Concept Recognition, is the task of assigning a unique identity to entities (such as famous individuals, locations, or companies) mentioned in text.
Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.
IGDB (Internet Games Database) IMDb (Internet Movie Database) INDUCKS; IndexMaster; Informit (database) Inorganic Crystal Structure Database; Interment.net; Internet Adult Film Database; Internet Archive; Internet Broadway Database; Internet Movie Cars Database; Internet Movie Firearms Database; Internet Off-Broadway Database; Internet Public ...
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
Add context and color to your emails for a more professional, impactful, or fun presentation whether you're sending a fun pick-me-up message or a professional resume, adding Stationery to your email is the perfect way to brighten up any message.
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