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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.

 

How Datastreamer works

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.

Experience Seamless Data Integration Yourself

Add Datastreamer components to your data stack and explore its full capabilities

Try it Now

Questions?

We’re always happy with any other questions you might have. Send us an email at [email protected]

We look forward to connecting with you.

Let us know if you're an existing customer or a new user, so we can help you get started!