Building a Smart Safety Data Sheet Parser Using NLP Lab
At the “Building a Smart Safety Data Sheet Parser Using NLP Lab” session we dive into the Chemical Safety Data Sheet parsing techniques that help derive meaningful insights, filter out irrelevant information, and transform data into a more understandable format for downstream tasks.
The ever-expanding realm of unstructured data sources presents significant challenges when extracting valuable insights. In this talk, we will walk you through the main challenges that you may face and how the new SmarterParser solution is revolutionizing Data parsing.
First, we will walk through main challenges including: Complicated Entity Extraction, Noisy Data Resulting in Inaccurately Parsed Outcome and Lack of Context. We also provide an overview of the Key Components of Wisecube’s SmartParser. Finally, we will present the BluePallet case study, a promising start-up that wanted to extract all relevant data from millions of Safety Data Sheets (SDS) and how wisecube resolved this using ML Model for Automatic Extraction and a Human in the Loop Validation process.
Alin Blidisel
Technical Team lead at Wisecube
Technical Team lead at Wisecube AI, Master Degree in AI with more than 10 years of experience in Big Data and Cloud Infrastructure.
Patrick Salomé
Co-Founder and Chief Product Officer at BluePallet
Co-Founder and Chief Product Officer at BluePallet whose mission is to connect the world of chemical commerce and make its companies and individuals more successful