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Show HN: ARElight – A Mass-Media Processing Application for Relation Extraction

28 points by nicolay-r 4y ago

encryptluks2 4y ago
It would be a lot more helpful since the site and documentation is in English, to have the screenshots in English. I actually find that despite the information available it still fails to describe what it is and does.
- rapnie 4y ago
  I agree. A short summary and use cases might help. One can't quickly determine what this does, and how they may benefit.
  - T-A 4y ago
    This would probably be a better link: https://github.com/nicolay-r/AREkit https://github.com/nicolay-r/AREkit
    - ianai 4y ago
      I read it, but this seems like the author went very terse instead of explanatory and linked a white paper. Seems maybe useful for someone already in the know but a little self limited by verbiage.
    - nicolay-r 4y ago
      It was decided not to provide this link since the its demo become a separated project, i.e. ARElight. Maybe it might be better to refer the particular demo from AREkit as well, so I will think about it.
ethanwillis 4y ago
After looking at the BERT paper linked here https://github.com/nicolay-r/awesome-sentiment-attitude-extraction https://github.com/nicolay-r/awesome-sentiment-attitude-extr... and at https://github.com/nicolay-r/AREkit 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.
- nicolay-r 4y ago
  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/contrib/networks/context/architectures https://github.com/nicolay-r/AREkit/tree/0.22.0-rc/arekit/co...
  - ethanwillis 4y ago
    Got it! Thanks for the explanation/clarification.
ninjin 4y ago
Nice to see that you are finding a use for the brat [1] frontend for the UI! Less nice that we did not get a cite in the paper [2]. '^^ [1]: http://brat.nlplab.org http://brat.nlplab.org [2]: https://nicolay-r.github.io/website/data/rusnachenko2021language.pdf https://nicolay-r.github.io/website/data/rusnachenko2021lang...
- nicolay-r 4y ago
  The paper [2] covers and related to experiments only, organized within a separate repository (without any visualization): https://github.com/nicolay-r/neural-networks-for-attitude-extraction/tree/0.20.5 https://github.com/nicolay-r/neural-networks-for-attitude-ex... Among all the other personal projects, we adopt BRAT only in ARElight. For now, there is no paper specifically devoted to ARElight only.

28 points by nicolay-r 4y ago

It would be a lot more helpful since the site and documentation is in English, to have the screenshots in English. I actually find that despite the information available it still fails to describe what it is and does.

rapnie 4y ago
I agree. A short summary and use cases might help. One can't quickly determine what this does, and how they may benefit.
- T-A 4y ago
  This would probably be a better link: https://github.com/nicolay-r/AREkit https://github.com/nicolay-r/AREkit
  - ianai 4y ago
    I read it, but this seems like the author went very terse instead of explanatory and linked a white paper. Seems maybe useful for someone already in the know but a little self limited by verbiage.
  - nicolay-r 4y ago
    It was decided not to provide this link since the its demo become a separated project, i.e. ARElight. Maybe it might be better to refer the particular demo from AREkit as well, so I will think about it.

ethanwillis 4y ago

After looking at the BERT paper linked here https://github.com/nicolay-r/awesome-sentiment-attitude-extraction https://github.com/nicolay-r/awesome-sentiment-attitude-extr... and at https://github.com/nicolay-r/AREkit 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.

nicolay-r 4y ago
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/contrib/networks/context/architectures https://github.com/nicolay-r/AREkit/tree/0.22.0-rc/arekit/co...
- ethanwillis 4y ago
  Got it! Thanks for the explanation/clarification.

ninjin 4y ago

Nice to see that you are finding a use for the brat [1] frontend for the UI! Less nice that we did not get a cite in the paper [2]. '^^ [1]: http://brat.nlplab.org http://brat.nlplab.org [2]: https://nicolay-r.github.io/website/data/rusnachenko2021language.pdf https://nicolay-r.github.io/website/data/rusnachenko2021lang...

nicolay-r 4y ago
The paper [2] covers and related to experiments only, organized within a separate repository (without any visualization): https://github.com/nicolay-r/neural-networks-for-attitude-extraction/tree/0.20.5 https://github.com/nicolay-r/neural-networks-for-attitude-ex... Among all the other personal projects, we adopt BRAT only in ARElight. For now, there is no paper specifically devoted to ARElight only.