Improving accuracy in Named Entity Recognition
I currently work with a Fintech start-up and we run into a compliance requirements to remove personal names from a bunch of texts.
We resorted to looking into Azure ML and yes, it appears promising by delivering a c. 80% accuracy in screening out individual names.
Yet - it's not perfect. We have a database of hundreds of thousands of verified names and can contribute if needed.
It would be grateful if we will be approached by a Microsoft person and we can share this database if see fit. trust the wealth of data we have would greatly improve the accuracy
Hello, thank you for your feedback. The Text Analytics team is working to improve the accuracy of our models and our NER API supports the detection of personal names. Please provide examples where these entities are missed by our models so that we can investigate and provide resolutions if needed.
Hi, we can be of your help, let us know if you are still looking out for this.
Drop us a line at email@example.com