Methods for adaptive information extraction through adaptive learning of human annotators and devices thereof

An information extraction (IE) computing device, comprising memory comprising programmed instructions stored thereon and one or more processors coupled to the memory and configured to be capable of executing the stored programmed instructions to:

• apply one or more named entity (NE) or relationship extraction (RE) classifier models to an obtained semi-structured or unstructured machine-readable input data corpus to extract and output structured data to an interactive graphical user interface (GUI);
• obtain, via the interactive GUI, an annotation of at least one RE missed classification, RE misclassification, or NE misclassification in the structured data;
• automatically determine when the RE missed classification or RE misclassification resulted from the NE misclassification or an NE missed classification based on an analysis of the annotation and one or more merged relationship classes or relation triplet objects;
• and
• retune the NE classifier model based on the NE missed classification or NE misclassification, when the determining indicates that the RE missed classification or RE misclassification resulted from the NE misclassification or NE missed classification.

A non-transitory computer readable medium having stored thereon instructions for improved information extraction (IE) using adaptive learning and statistical and deterministic classifiers comprising executable code which when executed by one or more processors, causes the one or more processors to:

• apply one or more named entity (NE) or relationship extraction (RE) classifier models to an obtained semi-structured or unstructured machine-readable input data corpus to extract and output structured data to an interactive graphical user interface (GUI);
• obtain, via the interactive GUI, an annotation of at least one RE missed classification, RE misclassification, or NE misclassification in the structured data;
• automatically determine when the RE missed classification or RE misclassification resulted from the NE misclassification or an NE missed classification based on an analysis of the annotation and one or more merged relationship classes or relation triplet objects;
• and
• retune the NE classifier model based on the NE missed classification or NE misclassification, when the determining indicates that the RE missed classification or RE misclassification resulted from the NE misclassification or NE missed classification.