Extract sentiment, identify topics/entities/sentiment, analyze large datasets with scalability.
Stanford CoreNLP
Access POS Tagging, extract information, and utilize an intuitive interface for text analysis.
Stanford CoreNLP provides a comprehensive suite of natural language processing capabilities implemented within the Java programming environment for developers and researchers. Users can access various functional modules including tokenization, sentence splitting, parts-of-speech tagging, named entity recognition, and dependency parsing through command line interfaces or interactive modes. The software also supports custom annotators and works across multiple human languages while integrating seamlessly with other programming packages and applications. This resource is intended for technical teams requiring robust linguistic analysis tools rather than general business productivity features.
Similar tools
Same job, different trade-offs.
Automate text processing, generate summaries, extract sentiment, identify patterns with ease.
Automate data processing, reduce ML complexity, and perform tasks like language translation, image recognition, etc.
Develop low-power AI applications with NLP, image recognition, and ML for embedded, mobile, and low-power devices.