Hierarchical named entity recognition with multi-task setup

A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• for a text portion provided as input to a hierarchical named entity recognition (“HNER”) system comprising a plurality of hierarchical level models corresponding to different hierarchical levels of a hierarchy, the plurality of hierarchical level models including a first hierarchical level model corresponding to a first hierarchical level and a second hierarchical level model corresponding to a second hierarchical level:
• identifying, using the first hierarchical level model, a first category for the first hierarchical level for a first named entity extracted from the text portion, wherein the first category is selected from a first plurality of categories that the first hierarchical level model is trained to predict, the first plurality of categories corresponding to the first hierarchical level;
• and
• identifying, using the second hierarchical level model, a second category for the second hierarchical level for a second named entity extracted from the text portion, wherein the second category is selected from a second plurality of categories that the second hierarchical level is trained to predict, the second plurality of categories corresponding to the second hierarchical level;
• wherein identifying the first category using the first hierarchical level model is performed independently of and in parallel with identifying the second category using the second hierarchical level model.

A system, comprising:

• one or more processors;
• and
• one or more memories storing computer-executable instructions that, when executed by the one or more processors, cause the system to perform:
• for a text portion provided as input to a hierarchical named entity recognition (“HNER”) system comprising a plurality of hierarchical level models corresponding to different hierarchical levels of a hierarchy, the plurality of hierarchical level models including a first hierarchical level model corresponding to a first hierarchical level and a second hierarchical level model corresponding to a second hierarchical level:
• identifying, using the first hierarchical level model, a first category for the first hierarchical level for a first named entity extracted from the text portion, wherein the first category is selected from a first plurality of categories that the first hierarchical level model is trained to predict, the first plurality of categories corresponding to the first hierarchical level;
• and
• identifying, using the second hierarchical level model, a second category for the second hierarchical level for a second named entity extracted from the text portion, wherein the second category is selected from a second plurality of categories that the second hierarchical level is trained to predict, the second plurality of categories corresponding to the second hierarchical level;
• wherein identifying the first category using the first hierarchical level model is performed independently of and in parallel with identifying the second category using the second hierarchical level model.