Lightweight tagging for disjoint entities

A system comprising:

• a hardware processor;
• a memory device coupled with the hardware processor;
• the hardware processor configured to:
• receive text data including at least named entities;
• identify from the named entities, continuous entities, overlapping entities and disjoint entities;
• transform the overlapping entities to continuous entities;
• encode the continuous entities, the transformed entities and the disjoint entities;
• input the encoded entities to a machine learning language model to predict candidate entities;
• and
• decode the predicted entities to reconstruct the predicted entities.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to:

• receive text data including at least named entities;
• identify from the named entities, continuous entities, overlapping entities and disjoint entities;
• transform the overlapping entities to continuous entities;
• input the encoded entities to a machine learning language model trained using encoded continuous entities, transformed entities and disjoint entities to predict candidate entities;
• and
• decode the predicted entities to reconstruct the predicted entities.