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Covering over 50 Chinese review platforms and over 250 English review platforms, this dataset offers insights into customer satisfaction, product feedback, and consumer trends. Whether it’s understanding how products are received, tracking competitor performance, or identifying areas for improvement, Socialgist Reviews dataset provides the real-world voice of the customer, crucial for market analysis, product development, and brand management.
Detect mentions of people, organizations, locations, filenames, phone numbers, crypto addresses, and more.
Entities are elements of relevance or interest in the text. Tisane extracts both standard entities and those relevant to trust & safety/law enforcement applications.
Standard entities are names of people, their social roles, organizations, places, and so on. We also extract cryptocurrency addresses, bank accounts, credit card numbers, phone numbers, software package names, and more.
Every entity entry is an object made of:
type - the type of the entityname - a standard name, if exists; otherwise, the string that was loggedsubtypes - more detailed additional typessubtype - the first subtype (for backward compatibility purposes)mentions - an array of all detected mentions, with:
offsetlengthsentence_indextextwikidata - a Wikidata ID, if existsHow Datastreamer works
Quickly enrich Socialgist Reviews with Tisane Entity Extraction with a Datstreamer Pipeline.
In modern enterprise architecture, web data fuels integration pipelines by bridging internal systems with external data sources such as partner networks and publicly accessible web content.
Make your web data work harder. With Datastreamer, you can enrich, filter, join, structure, store, or search data effortlessly using hundreds of out-of-the-box operations.
Web data, unlocked. Datastreamer empowers you to expand your Pipelines as needed while removing friction from your operations.
Add Datastreamer components to your data stack and explore its full capabilities
