📢 If you're working in relation extraction / character network domain, then the following post would be relevant.
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📢 If you're working in relation extraction / character network domain, then the following post would be relevant.
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Excited to share the most recent milestone on releasing the ARElight 0.25.0 🎊
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Excited to share the most recent milestone on releasing the ARElight 0.25.0 🎊
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Core library: 
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Core library: 
https://github.com/nicolay-r/ARElight
https://github.com/nicolay-r/ARElight
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Server: 
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Server: 
https://github.com/nicolay-r/ARElight-server
https://github.com/nicolay-r/ARElight-server
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🔎 What is ARElight? It represents Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts.
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🔎 What is ARElight? It represents Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts.
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Shortly speaking, it allows to extract contexts with mentioned object pairs for the related prompting / classification.
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Shortly speaking, it allows to extract contexts with mentioned object pairs for the related prompting / classification.
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In the slides below we illsutrate the ARElight appliation for sentiment classification between object pairs in context.
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In the slides below we illsutrate the ARElight appliation for sentiment classification between object pairs in context.
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We exploit DeepPavlov NER modes + GoogleTranslate + BERT-based classifier in the demo. The bash script  for launching the quick demo illustrates the application of these components. 
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We exploit DeepPavlov NER modes + GoogleTranslate + BERT-based classifier in the demo. The bash script  for launching the quick demo illustrates the application of these components. 
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The new update provide a series of new features:
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The new update provide a series of new features:
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✅ SQlite support for storing all the extracted samples
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✅ SQlite support for storing all the extracted samples
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✅ Support of the enhanced GUI for content investigation.
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✅ Support of the enhanced GUI for content investigation.
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✅ Switch to external no-string projects for NER and Translator
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✅ Switch to external no-string projects for NER and Translator
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Supplementiary materials:
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Supplementiary materials:
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📜 Paper: 
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📜 Paper: 
https://link.springer.com/chapter/10.1007/978-3-031-56069-9_23
https://link.springer.com/chapter/10.1007/978-3-031-56069-9_23
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📢 If you're working in relation extraction / character network domain, then the following post would be relevant.
Excited to share the most recent milestone on releasing the ARElight 0.25.0 🎊

Core library: https://github.com/nicolay-r/ARElight
Server: https://github.com/nicolay-r/ARElight-server

🔎 What is ARElight? It represents Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts.
Shortly speaking, it allows to extract contexts with mentioned object pairs for the related prompting / classification.
In the slides below we illsutrate the ARElight appliation for sentiment classification between object pairs in context.

We exploit DeepPavlov NER modes + GoogleTranslate + BERT-based classifier in the demo. The bash script  for launching the quick demo illustrates the application of these components. 

The new update provide a series of new features:
✅ SQlite support for storing all the extracted samples
✅ Support of the enhanced GUI for content investigation.
✅ Switch to external no-string projects for NER and Translator

Supplementiary materials:
📜 Paper: https://link.springer.com/chapter/10.1007/978-3-031-56069-9_23

👀
John6666 EquinoxElahin