Abstract: Mechanisms are provided, in association with a question and answer system, for generating answers to an input question. An input question is received and processed to generate at least one query. The at least one query is applied to the corpus to generate a set of candidate answers and corresponding selections of evidence portions of the corpus of information providing evidence in support of the at least one candidate answer being a correct answer for the input question. A graphical user interface (GUI) is output comprising a first GUI sub-section comprising the set of candidate answers, and a second GUI sub-section comprising the evidence portions of the corpus. User input modifying at least one of set of candidate answers or the evidence portions of the corpus of information is received via the GUI and an operation of the data processing system is adjusted based on the user input.

Abstract: Disclosed aspects include managing data for a Question and Answering (QA) system. Aspects include a set of questions being received by the QA system. In response to receiving the set of questions, a first confidence score for a first answer to a first question of the set of questions is determined. Aspects include determining the first confidence score meets a threshold confidence score. In response to the first confidence score meeting the threshold confidence score, the QA system stores the first question and the first answer for future presentation use as an aid in formulating a second query.

Abstract: Disclosed aspects include managing data for a Question and Answering (QA) system. Aspects include a set of questions being received by the QA system. In response to receiving the set of questions, a first confidence score for a first answer to a first question of the set of questions is determined. Aspects include determining the first confidence score meets a threshold confidence score. In response to the first confidence score meeting the threshold confidence score, the QA system stores the first question and the first answer for future presentation use as an aid in formulating a second query.

Abstract: Mechanisms are provided for modifying an operation of a question answering (QA) system. An input question is received and processed to generate at least one query to be applied to a corpus of information. The at least one query is applied to the corpus of information to generate candidate answers to the input question from which a final answer is selected for output. A training engine modifies, using a machine learning technique that compares the final answer to a known correct answer for the input question, at least one of logic or configuration parameters of the QA system for at least one of the processing of the input question to generate the at least one query, applying of the at least one query to the corpus of information to generate the candidate answers, or the selecting of the final answer from the candidate answers.

Abstract: Mechanisms are provided for answering questions about at least one previous execution of a question answering (QA) system on a previous input question. An input question is received that is directed to a previous execution of a QA system with regard to a previous input question. The input question is processed to generate at least one query for application to a corpus of information, which comprises information about the QA system and the previous execution of the QA system on the previous input question. The at least one query is applied to the corpus of information to generate candidate answers to the input question which are ranked according to confidence measure values associated with the candidate answers. A final answer for the input question is output based on the ranking of the candidate answers.

Abstract: Mechanisms are provided, in association with a question and answer system, for generating answers to an input question. An input question is received and processed to generate at least one query. The at least one query is applied to the corpus to generate a set of candidate answers and corresponding selections of evidence portions of the corpus of information providing evidence in support of the at least one candidate answer being a correct answer for the input question. A graphical user interface (GUI) is output comprising a first GUI sub-section comprising the set of candidate answers, and a second GUI sub-section comprising the evidence portions of the corpus. User input modifying at least one of set of candidate answers or the evidence portions of the corpus of information is received via the GUI and an operation of the data processing system is adjusted based on the user input.

Abstract: Mechanisms are provided for modifying an operation of a question answering (QA) system. An input question is received and processed to generate at least one query to be applied to a corpus of information. The at least one query is applied to the corpus of information to generate candidate answers to the input question from which a final answer is selected for output. A training engine modifies, using a machine learning technique that compares the final answer to a known correct answer for the input question, at least one of logic or configuration parameters of the QA system for at least one of the processing of the input question to generate the at least one query, applying of the at least one query to the corpus of information to generate the candidate answers, or the selecting of the final answer from the candidate answers.

Abstract: Mechanisms are provided for answering questions about at least one previous execution of a question answering (QA) system on a previous input question. An input question is received that is directed to a previous execution of a QA system with regard to a previous input question. The input question is processed to generate at least one query for application to a corpus of information, which comprises information about the QA system and the previous execution of the QA system on the previous input question. The at least one query is applied to the corpus of information to generate candidate answers to the input question which are ranked according to confidence measure values associated with the candidate answers. A final answer for the input question is output based on the ranking of the candidate answers.

Abstract: A system, method and program product for creating a UML model of a user interface environment, such as a website. A UML design system is disclosed that includes: a system for defining use cases within the UML model; a system for associating an affinity representing a user-perceived relationship between use cases within the UML model; and a system for assigning a weight to the affinity within the UML model.

Abstract: A system, method and program product for creating a UML model of a user interface environment, such as a website. A UML design system is disclosed that includes: a system for defining use cases within the UML model; a system for associating an affinity representing a user-perceived relationship between use cases within the UML model; and a system for assigning a weight to the affinity within the UML model.