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@@ -23,7 +23,7 @@ This dataset aims to improve the representation of underrepresented topics and e
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  - **Curated by:** [Emergent Methods](https://www.emergentmethods.ai/)
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  - **Funded by:** [Emergent Methods](https://www.emergentmethods.ai/)
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  - **Shared by:** [Emergent Methods](https://www.emergentmethods.ai/)
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- - **Language(s) (NLP):** English (en), and translated French, Spanish, German, Swedish, Italian, Arabic, Chinese, Norwegian, Danish, Portuguese, Dutch, Russian, Ukranian
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  - **License:** Apache 2.0
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  ### Dataset Sources
@@ -99,6 +99,7 @@ This dataset was created in an effort to improve the representation of underrepr
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  3. Embed summaries to vectors
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  Present dataset curation:
 
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  4. Cluster embeddings according to topic, for each 4 hour bucket of articles throughout the duration of February 20-March 30 2024.
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  5. Pull samples from clusters, distributing evenly across country of origin.
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  6. Extract entities from each summary using Llama3.
 
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  - **Curated by:** [Emergent Methods](https://www.emergentmethods.ai/)
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  - **Funded by:** [Emergent Methods](https://www.emergentmethods.ai/)
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  - **Shared by:** [Emergent Methods](https://www.emergentmethods.ai/)
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+ - **Language(s) (NLP):** English (en), and translated French, Spanish, German, Swedish, Italian, Arabic, Chinese, Norwegian, Danish, Dutch, Russian, Ukranian
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  - **License:** Apache 2.0
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  ### Dataset Sources
 
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  3. Embed summaries to vectors
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  Present dataset curation:
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+
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  4. Cluster embeddings according to topic, for each 4 hour bucket of articles throughout the duration of February 20-March 30 2024.
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  5. Pull samples from clusters, distributing evenly across country of origin.
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  6. Extract entities from each summary using Llama3.