Abstract:
A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.
Abstract:
A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, identifying a plurality of candidate answers to the query; and for at least one of these candidate answers, identifying at least one proof of the answer. This proof includes a series of premises, and a multitude of documents are identified that include references to the premises. A set of these documents is selected that include references to all of the premises. This set of documents is used to generate one or more scores for the one of the candidate answers. A defined procedure is applied to the candidate answers to determine a ranking for the answers, and this includes using the one or more scores for the at least one of the candidate answers in the defined procedure to determine the ranking for this one candidate answer.
Abstract:
Methods/systems receive a question and automatically search sources of data containing passages to produce candidate answers to the question. The searching identifies passages that support each of the candidate answers based on scoring features that indicate whether the candidate answers are correct answers to the question. These methods/systems automatically create a scoring feature- specific matrix for each scoring feature. Each scoring feature-specific matrix has a score field for each different combination of text passage and question term (vector), and each score field holds a score value (vector value) indicating how each different combination of text passage and question term supports the candidate answers as being a correct answer to the question. Next, such methods/systems automatically combine multiple such vectors to produce a combined vector score for each of the candidate answers, and then rank the candidate answers based on the combined scores.