Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
Extract data about articles, categories, and contributors from en.wikipedia.org.
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 Bright Data Wikipedia with Tisane Entity Extraction with a Datstreamer Pipeline.
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.
Transform your web data at scale with Datastreamer. Whether you're enriching, storing, joining, or filtering, you'll find hundreds of ready-made operations to help you move fast.
Datastreamer transforms how you use web data. Grow your Pipelines without disruption and finally streamline the operational side of your workflow.
Add Datastreamer components to your data stack and explore its full capabilities
