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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 existsA specialized Telegram product focused on collecting users and channel content associated with the Russian state, Russian-affiliated propaganda, white nationalist groups, and European far-right organizations.
How Datastreamer works
Quickly apply Tisane Entity Extraction to Open Measures Telegram with a Datstreamer Pipeline.
Enterprise data pipelines are built on the continuous flow of web data, which can originate from partner networks, internal infrastructures, or any external digital source.
To accelerate using your web data, you can apply any number of operations to the data. Enrich, augment, join, structure, filter, storage, search, or more! Datastreamer has hundreds of plug-and-play operations that you can apply.
With Datastreamer it’s never been easier to use web data. You can dynamically expand your Pipelines with more capabilities, and you’ve now been able to solve your operational bottlenecks in working with web data.
Add Datastreamer components to your data stack and explore its full capabilities
