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Disambiguation – Linking Data Science and Engineering

Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores. 

Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job. 

We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity. 

Visualize BERT Attention for Natural Language Understanding (NLU) Use Cases using Amazon SageMaker

BERT is a revolutionary AI/ML model for Natural Language Understanding (NLP) and Natural Language Understanding (NLU). In this talk, I describe how...