Information object extraction using combination of classifiers

Abstract

Systems and methods for information extraction from natural language texts using a combination of classifier models. An example method may comprise: producing, by performing syntactico-semantic analysis of a natural language text, a plurality of syntactico-semantic structures representing the natural language text; identifying, using a first classifier model to process a first plurality of classification attributes derived from the syntactico-semantic structures, a plurality of core constituents, such that each core constituent of the plurality of core constituents is associated with a span of a plurality of spans, wherein each span represents an attribute of an information object of a specified ontology class; identifying, using a second classifier model to process a second plurality of classification attributes derived from the syntactico-semantic structures, child constituents of each of the plurality of core constituents; and determining, using a third classifier model to process a third plurality of classification attributes derived from the syntactico-semantic structures, whether a first span of the plurality of spans and a second span of the plurality of spans represent information object attributes that are associated with a same information object.