The Stanford CoreNLP toolkit is an extensible pipeline for core natural language processing tasks, widely used in both academic and commercial settings. The toolkit's success is attributed to its simple, approachable design, straightforward interfaces, robust and high-quality analysis components, and minimal required setup. Initially developed for internal use, it was later released as open-source software in 2010. CoreNLP provides a uniform interface for Annotators, which add analysis information to text through Annotation objects. The system supports various languages and offers a range of features, including tokenization, sentence splitting, part-of-speech tagging, named entity recognition, dependency parsing, and sentiment analysis. Users can easily customize the pipeline by adding custom Annotators, making it highly flexible and adaptable to different needs. The toolkit's accessibility and ease of use have contributed to its widespread adoption, making it a central tool in the NLP community.The Stanford CoreNLP toolkit is an extensible pipeline for core natural language processing tasks, widely used in both academic and commercial settings. The toolkit's success is attributed to its simple, approachable design, straightforward interfaces, robust and high-quality analysis components, and minimal required setup. Initially developed for internal use, it was later released as open-source software in 2010. CoreNLP provides a uniform interface for Annotators, which add analysis information to text through Annotation objects. The system supports various languages and offers a range of features, including tokenization, sentence splitting, part-of-speech tagging, named entity recognition, dependency parsing, and sentiment analysis. Users can easily customize the pipeline by adding custom Annotators, making it highly flexible and adaptable to different needs. The toolkit's accessibility and ease of use have contributed to its widespread adoption, making it a central tool in the NLP community.