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Enrich Socialgist News with Datastreamer Cultural Reference Recognition Model
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About Socialgist News
Drawing from over 1,000 Chinese news sources and over 25,000 English news sources, Socialgist provides a comprehensive overview of current events, editorial opinions, and journalistic analysis. This dataset is invaluable for understanding media narratives, tracking news cycles, and analyzing the impact of current events on public discourse and sentiment across various regions and topics.
About Datastreamer Cultural Reference Recognition Model
Movies, songs, memes, books, and other cultural references can be detected with this LLM-powered model in over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
Quickly enrich Socialgist News with Datastreamer Cultural Reference Recognition Model with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Socialgist News
To support enterprise-scale data integration, pipelines must ingest web data from varied origins, including trusted partners, internal databases, and external web-based assets.
Step 2
Add Datastreamer Cultural Reference Recognition Model to enrich
Accelerate your web data workflows with Datastreamer. Whether it's enriching, joining, filtering, or storing your data, choose from hundreds of pre-built operations ready to deploy instantly.
Step 3
That's it! You have just connected Socialgist News and Datastreamer Cultural Reference Recognition Model
Using web data has never been this easy—thanks to Datastreamer. Expand your Pipelines on the fly and overcome the workflow challenges that once slowed you down.