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Launch HN: Datasaur (YC W20) – data labeling interface for NLP

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Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#53
post #41

Congrats. Do you guys use AllenNLP, by any chance?

We've looked into it! So far we've chosen to integrate with spaCy. Can I ask what you like about AllenNLP?

Hi there, great product! I'm with a nonprofit edtech writing tool that uses both spaCy and AllenNLP, and we've found AllenNLP's models to be more accurate for tasks like co-reference resolution. AllenNLP's models are built on top of spaCy and tools like neural coref. It'd be great if we could harness things like AllenNLP's semantic role labeling.

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#54
In the spreadsheet view, do users need to upload labels as a text file to then assign them to items? I work with Quill.org, a nonprofit edtech tool that helps students improve their writing skills, and we do a lot of labeling work now where we may need to assign say one of 20 labels to 1,000 responses at a time. I uploaded some sample data, but didn't understand how I could quickly assign labels to my content. Please let me know if I'm missing something here.

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#55

In the spreadsheet view, do users need to upload labels as a text file to then assign them to items? I work with Quill.org, a nonprofit edtech tool that helps students improve their writing skills, and we do a lot of labeling work now where we may need to assign say one of 20 labels to 1,000 responses at a time. I uploaded some sample data, but didn't understand how I could quickly assign labels to my content. Please…

Hi there - you may choose to upload labels as a text file or create your own. I'd be curious to hear more about your use case in batch-applying labels. I'll follow up offline (well, via email).

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#56
It resembles an open source annotation tool that has existed for years. https://brat.nlplab.org/

It doesn't include a ML assistant though.

We have built a semi-automated annotation tool for our internal use too. ML models help classify documents and extract named entities by making suggestions. Sometimes I'm thinking of spinning it off as a standalone product but not sure how big the market would be.

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#58
post #56

It resembles an open source annotation tool that has existed for years. https://brat.nlplab.org/ It doesn't include a ML assistant though. We have built a semi-automated annotation tool for our internal use too. ML models help classify documents and extract named entities by making suggestions. Sometimes I'm thinking of spinning it off as a standalone product but not sure how big the market would be.

I think the semi-automated annotation tool is quite the same with prodigy

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#59
post #58
post #56

It resembles an open source annotation tool that has existed for years. https://brat.nlplab.org/ It doesn't include a ML assistant though. We have built a semi-automated annotation tool for our internal use too. ML models help classify documents and extract named entities by making suggestions. Sometimes I'm thinking of spinning it off as a standalone product but not sure how big the market would be.

I think the semi-automated annotation tool is quite the same with prodigy

Both can be described as semi-automated annotation, but we use different approaches! Datasaur allows you to plug in any pre-existing model to pre-label or validate your labels. One such model we integrate with is spaCy, so we're certainly fans of the Prodigy/Explosion team.

Re: Launch HN: Datasaur (YC W20) – data labeling interface for NLP

#60
post #56

It resembles an open source annotation tool that has existed for years. https://brat.nlplab.org/ It doesn't include a ML assistant though. We have built a semi-automated annotation tool for our internal use too. ML models help classify documents and extract named entities by making suggestions. Sometimes I'm thinking of spinning it off as a standalone product but not sure how big the market would be.

We're fans of brat and are hoping to take it to the next level. We devoted many hours to ensuring a highly performant web app on the latest modern tech stack. Additionally we're expanding beyond a labeling interface to include semi-automated annotation, as well as team management capabilities.
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