METHODS FOR ADAPTIVE INFORMATION EXTRACTION THROUGH ADAPTIVE LEARNING OF HUMAN ANNOTATORS AND DEVICES THEREOF

摘要

Methods, non-transitory computer readable media, and information extraction computing devices that 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). An annotation of at least one RE missed classification, RE misclassification, or NE misclassification in the structured data is obtained via the interactive GUI. A determination is made 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. The NE classifier model is retuned 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.