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Enrich The Social Proxy Financial Market Datasets with Tisane Entity Extraction
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About The Social Proxy Financial Market Datasets
Scrape Live Financial Markets Data. From AI-powered algo trading to in-depth market analysis. Gather live data for real-time decision Making.
About Tisane Entity Extraction
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 entity
name - a standard name, if exists; otherwise, the string that was logged
subtypes - more detailed additional types
subtype - the first subtype (for backward compatibility purposes)
mentions - an array of all detected mentions, with:
Quickly enrich The Social Proxy Financial Market Datasets with Tisane Entity Extraction with a Datstreamer Pipeline.
Step 1
Start your Pipeline with The Social Proxy Financial Market Datasets
Web data plays a central role in enterprise data integration, serving as a primary input across pipelines. It can be sourced from partner networks, internal systems, or the open web to support scalable data workflows.
Step 2
Add Tisane Entity Extraction to enrich
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.
Step 3
That's it! You have just connected The Social Proxy Financial Market Datasets and Tisane Entity Extraction
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.