International Business Machines Corporation

Christine A Grev

Corville O Allen

Richard Joseph Stevens

Brian John Cragun

Cale T Rath

Kathryn Lamont Whaley

Hoa Thu Tran

Jordi A Albornoz

David Alan Wall

Mechanisms are provided for training and operating a Question and Answer (QA) system pipeline. A corpus of information is received which comprises historical data to which one or more filter criteria are applied to extract filtered historical data relevant to a training objective for training the QA system pipeline. Attribute data, action data, and temporal characteristic data are captured from the filtered historical data. An answer key entry is automatically generated in an automatically generated training answer key data structure based on the attribute data, action data, and temporal characteristic data. The correct answer associated with the answer key entry is an action specified by the action data. The temporal characteristic data provides a historical context for the answer key entry. The QA system pipeline is trained using the automatically generated training answer key data structure.

Automatic generation of training cases and answer key from historical corpus

Mechanisms are provided for implementing training logic for training a Question and Answer (QA) system. A training question, associated with an answer key, is received and processed by the QA system to generate a final answer to the training question and supporting evidence for the final answer based on a corpus of information. The supporting evidence is analyzed to identify one or more evidence attributes and a plurality of correct answer entries in the answer key are searched to identify a matching correct answer entry that matches the final answer. The matching correct answer entry in the answer key is augmented to include the one or more evidence attributes in an augmented answer key and the QA system is trained based on the augmented answer key.

Augmenting answer keys with key characteristics for training question and answer systems

Methods, systems, and articles of manufacture for organizing and selecting structures used to generate forms for capturing information as annotations made for a variety of different type data objects are provided. Some embodiments allow annotation structures to be associated with specific pairings of data object types and user roles via entries in a configuration file. When a user selects a set of one or more data objects for annotation, the configuration file may be accessed to determine a proper annotation structure for use in generating an annotation form based on the selected data objects and a role of the user.

Annotation structure type determination

Methods, systems, and articles of manufacture for proving global annotation services are disclosed. Global annotations are used to annotate a data element independently from the internal representation of a data element employed by a particular software application. Data elements are normalized into a form used by a global annotation system to identify the data element, and corresponding global annotations, independent from the application in which the data element may appear. An annotation cache may be used to store the global annotations that have been created for a particular data source, improving the efficiency of the global annotation system.

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Rochester, MN, United States of America

Christine A Grev