Named-Entity Recognition (NER)

Targets the identification and categorization of named entities within text into predefined groups such as locations, persons, or organizations. This extraction method excels in straightforward tasks, like pinpointing references to “New York City.” However, its ability to recognize and associate various nicknames or colloquial terms, like “the Big Apple,” with the same entity can be limited. NER’s effectiveness lies in its precision for direct mentions, though it may require additional contextual or semantic analysis tools to fully capture the breadth of language used to refer to specific entities.