COMPUTER-BASED SYSTEMS CONFIGURED TO PRE-TRAIN LANGUAGE MODELS FOR ENTITY RESOLUTION AND METHODS OF USE THEREOF

Abstract: in some embodiments, the present disclosure provides an exemplary method that may include steps of receiving a dataset of entity records, identifying, a candidate entity record of the plurality of entity records, utilizing a set of predefined rules to generate a first augmented record, and a second augmented record, utilizing, at least one contrastive loss optimization functions to train parameters of an unsupervised self-contrastive machine learning language model to distinguish between similar entity records representing a same entity and dissimilar entity records.

Inventor(s): Samuel Sharpe, Daniele Rosa, Adam Badawy

CPC Classification: G06F16/215 (Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors)

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