International Business Machines Corporation

Amy E Veatch

Scott Robert Carrier

Lee Michael Surprenant

A method, system and computer-usable medium are disclosed for identifying unchecked criteria within a form. Natural Language Processing (NLP) is applied to unstructured data within a target form to identify elements of a form structure. Analytic analysis is then applied to the resulting form structure elements to identify a hierarchical structure and associated element placement. Implicit selections within the form are then identified by applying rules based upon other selections and their orientation to anchor terms to determine the completeness of the form, based upon aggregation of form elements. The form structure elements and the hierarchy metadata are then processed logically reassemble the form's hierarchy in flattened forms for multi-layer, sub-element anaphora resolution.

Method of improving NLP processing of real-world forms via element-level template correlation

NLP processing of real-world forms via element-level template correlation

An approach is provided to correct natural language processing (NLP) annotators. The approach operates by receiving a set of supporting text noted by a user in response to the user identifying an error to a user question in a question answering (QA) system. The set of supporting text includes one or more text passages from which a correct answer should have been generated by the QA system. The QA system generates one or more scored candidate corrections with each of the scored candidate corrections is based on the identified error and the set of supporting text. The user can then select one or more of the scored candidate corrections as a confirmed correction to the error. The confirmed corrections are then applied to a corpus that is utilized by the QA system when answering questions.

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Amy E Veatch