[HN Gopher] Show HN: ARElight - A Mass-Media Processing Applicat...
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       Show HN: ARElight - A Mass-Media Processing Application for
       Relation Extraction
        
       Author : nicolay-r
       Score  : 28 points
       Date   : 2022-06-18 12:59 UTC (1 days ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | ethanwillis wrote:
       | 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 SShA 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 wrote:
         | 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...
        
           | ethanwillis wrote:
           | Got it! Thanks for the explanation/clarification.
        
       | encryptluks2 wrote:
       | 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 wrote:
         | 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 wrote:
           | This would probably be a better link:
           | 
           | https://github.com/nicolay-r/AREkit
        
             | ianai wrote:
             | 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 wrote:
             | 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.
        
       | ninjin wrote:
       | 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
       | 
       | [2]:
       | https://nicolay-r.github.io/website/data/rusnachenko2021lang...
        
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       (page generated 2022-06-19 23:02 UTC)