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Enrich Open Measures Poal with Datastreamer Entity Recognition
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Open Measures Poal
Collect and extract comments, video metadata and user profiles on Poal.
About Datastreamer Entity Recognition
This Named Entity Recognition classifier helps reduce the noise in the query results. It extracts the named entity from a short-form English content. The output would cover three classes of entities: Persons, Organization, and Location.
Quickly enrich Open Measures Poal with Datastreamer Entity Recognition with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Open Measures Poal
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 Datastreamer Entity Recognition to enrich
Supercharge your data pipeline! Apply operations like enrichment, structuring, joining, and filtering—Datastreamer gives you instant access to hundreds of plug-and-play data tools.
Step 3
That's it! You have just connected Open Measures Poal and Datastreamer Entity Recognition
Say goodbye to bottlenecks. Datastreamer lets you unlock the full power of web data by giving you the tools to dynamically grow your Pipelines.