Nicole Moldovan
Director, Lymba
Nicole helps companies turn data into answers through actionable AI programs. Utilizing NLP technologies, Nicole assists clients in extracting value from their structured and unstructured data (documents, contracts, chat logs, reports, emails, text repositories, relational and graph databases) for the purpose of regulatory reporting, question-answering, chat, search, email classification, and other applications. At Lymba, she oversees new client engagements and has a ridiculously smart team of computational linguists and developers ready to tackle your next project. She holds a Bachelor of Science in Business and Technology from Stevens and an MBA from Columbia.

2021 Talk: NLP - A Cornerstone for a Successful Graph -- A look at handling unstructured data through a medical case study

We’ll explore how unstructured and structured data can come together to tell a complete story through the lens of a pharma clinical trial and subsequent events in the field. We’ll weave through the patient history and other documents using an ontology and several NLP tools, then use natural language querying to ask plain English questions of the graph to make sense of our data. Attendees will walk away with a better understanding of how to use NLP to make the most of their graph databases and incorporate text-heavy data sources.

2020 Product Demo: Boost Your Graph with Semantic NLP

Knowledge Graphs offer speedier performance, dynamic mapping, and insightful data connections. However, accessible data is either already structured and the tools are limited for extracting data from text. Lymba solves this problem with its proprietary K-Extractor™ NLP pipeline which extracts knowledge from any text source and converts the data in semantic RDF triples. This demo will cover extracting information from natural language in M&A text, using an ontology to configure the NLP pipeline, resulting in the population of a graph store, and subsequent natural language querying. The additional layer of semantic analysis of text data enriches the graph with many more connections than exist in existing structured sources. View the 2020 product demo in the KGC media library.