Information Extraction NLP
Information extraction (IE) in Natural Language Processing (NLP) is the task of automatically extracting structured information from unstructured text. It involves identifying and extracting specific entities, relationships, or events mentioned in the text and representing them in a structured format. Output: Steps in Information Extraction: Entity Recognition: Entity recognition is the task of identifying and classifying named entities in a text. Named entities are typically proper nouns that represent specific entities such as people, organizations, locations, dates, or other domain-specific entities. Entity recognition techniques use various approaches, including rule-based methods, statistical models, and machine learning algorithms, to detect and classify entities in a document. Output: Sentence Boundary Detection: Sentence boundary detection involves segmenting a text document into individual sentences. This step is crucial for many NLP tasks, including relation extraction. Sente