Question: Can you recommend a text analytics tool that can extract entities like people, companies, and locations from large datasets?

If you need a heavy-duty text analytics tool to pull entities like people, companies and locations out of a big data set, NetOwl is a good option. It offers scalable and accurate entity extraction, sentiment analysis and identity resolution tools in many languages. Its technology is geared for big unstructured data challenges in areas like finance, law enforcement and national security.

Another contender is NuMind, a no-code machine learning platform for training text processing models. It's multilingual and has a range of features, including entity recognition, sentiment analysis and text classification. NuMind is designed to be data efficient and economical, so it could be useful for a variety of business needs.

If you want a platform that marries Large Language Models with symbolic AI, Lettria is a no-code tool for processing and extracting insights from text. Its features include text preprocessing, mining and classification, so it's good for turning unstructured text into knowledge graphs and enriching data with ontology integration.

You could also look at MonkeyLearn, a no-code text analytics tool good for cleaning, labeling and visualizing customer feedback. It offers customizable dashboards and pre-trained models for sentiment analysis, entity extraction and topic classification, and it integrates with popular apps like Zendesk and Google Sheets.