AREkit

Texts were mentioned as-it-is since for now we are lack of training data to reproduce the same model for English language. In terms of understanding list: 1. Yes it is. 2. Entity tagging model, based on DeepPavlov, is a part of ARElight, not AREkit. 3. AREkit implements and provides tools for BERT data preparation only; BERT-related service is a part of the ARElight. Overall idea and understanding is correct. In terms of the AREkit, the latter proposed as a data-preparation toolkit. However, at present, it additionally provides a Tensorflow-based neural networks zoo in, adopted for sentiment relation extraction task https://github.com/nicolay-r/AREkit/tree/0.22.0-rc/arekit/co...

After looking at the BERT paper linked here https://github.com/nicolay-r/awesome-sentiment-attitude-extr... and at https://github.com/nicolay-r/AREkit I was able to fully understand the purpose. I can read enough of the language in the screenshots to get a basic idea before reading those, but most English speakers probably aren't even going to know what США is :). Here's what this project is from my understanding: 1. This is a web application/ui for the AREkit backend. 2. AREkit uses the DeepPavlov library to do entity tagging 3. AREkit also implements the "BERT" model which is a way to get sentiment relationships between two entities in some text. So overall the idea is being able to data mine not just overall sentiment in some text, but to get more granular and look at sentiment between entities within some text.

This would probably be a better link: https://github.com/nicolay-r/AREkit