Automated ESG Knowledge Extraction from News

Presentation discusses technology used to automate Knowledge extraction from Text. This novel technology in the form of TextDistil, the pipeline software (from Lead Semantics) blends neural language models, semantic tech, rule systems, linguistic theory to achieve reliable fact extraction performance. Specifically, the dicussion will focus on the extraction of facts buried in news articles, news letters, reports, etc. about the subject area of ESG (Environmental..) through the application of ESG taxonomy and ontology. Extracted facts are output as RDF triples and ingested into a Semantic Graph stored in a triple store which supports graph search, BI & reporting over these facts through standard graph queries