Dia Trambitas is a computer scientist with a rich background in Natural Language Processing. She has a Ph.D. in Semantic Web from the University of Grenoble, France, where she worked on ways of describing spatial and temporal data using OWL ontologies and reasoning based on semantic annotations. She then changed her interest to text processing and data extraction from unstructured documents, a subject she has been working on for the last 10 years. She has a rich experience working with different annotation tools and leading document classification and NER extraction projects in verticals such as Finance, Investment, Banking, and Healthcare.
Recognize over 18 entities such as Countries, People, Organizations, Products, Events, etc. using an out of the box pre-trained NerDLApproach trained on the OntoNotes corpus.
Recognize Persons, Locations, Organizations, and Misc entities using out of the box pre-trained Deep Learning models based on GloVe (glove_100d) and BERT (ner_dl_bert) word embeddings.
Demos
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