In his recent article in Towards Data Science, “How to Cover Up in Multiple Languages”, Slimmer AI machine learning engineer Borach Jansema follows-up on his previous NER article, “Unlocking Inclusivity Possibilities with Polyglot-NER”.

In his article, Borach measures how well a polyglot (multilingual) NER model can switch to other domain types by taking a polyglot model trained on a general domain and applying it to a legal domain.

The English bias prevalent in NER effectively leaves out a considerable part of the world from this important technological advancement, polyglot models offer the possibility of a bridge between languages.

Read the full article.

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