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The ability to extract causal relationships from textual data can have far-reaching impacts in fields such as healthcare, finance, and environmental science, where understanding cause-and-effect dynamics is critical for decision-making and problem-solving.

Named Entity Recognition (NER) plays a crucial role in information extraction by identifying and classifying entities such as people, organizations, and locations in unstructured text, providing a structured framework for understanding and organizing valuable information.