1. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions that are executed by the at least one processor to specifically configure the at least one processor to implement a question answering system configured with a natural language processing pipeline executing on the at least one processor of the data processing system for class narrowing for answer lookups, the method comprising: receiving, by a question and topic analysis stage of the natural language processing pipeline, an input question; annotating, by the question and topic analysis stage of the natural language processing pipeline, the input question with a verb in the input question and a syntactic relation between the verb and a focus of the question; finding, by a class narrowing component of the natural language processing pipeline, an entry in a verb/type lookup resource corresponding to the verb and the syntactic relation, wherein the entry comprises the verb, the syntactic relation, and a set of classes, wherein each given class in the set of classes has a corresponding frequency value representing a frequency the given class occurs with the syntactic relation to the verb; performing, by the class narrowing component, class-narrowed type-restricted answer lookup from a topology based on the entry in the verb/type lookup resource to generate a set of candidate answers; scoring, by a hypothesis and evidence scoring stage of the natural language processing pipeline, the set of candidate answers to generate for each candidate answer a confidence score; ranking, by an answer ranking stage of the natural language processing pipeline, the set of candidate answers by confidence score to form a ranked set of candidate answers; and outputting, by the natural language processing pipeline, the ranked set of candidate answers.
1. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions that are executed by the at least one processor to specifically configure the at least one processor to implement a question answering system configured with a natural language processing pipeline executing on the at least one processor of the data processing system for class narrowing for answer lookups, the method comprising: receiving, by a question and topic analysis stage of the natural language processing pipeline, an input question; annotating, by the question and topic analysis stage of the natural language processing pipeline, the input question with a verb in the input question and a syntactic relation between the verb and a focus of the question; finding, by a class narrowing component of the natural language processing pipeline, an entry in a verb/type lookup resource corresponding to the verb and the syntactic relation, wherein the entry comprises the verb, the syntactic relation, and a set of classes, wherein each given class in the set of classes has a corresponding frequency value representing a frequency the given class occurs with the syntactic relation to the verb; performing, by the class narrowing component, class-narrowed type-restricted answer lookup from a topology based on the entry in the verb/type lookup resource to generate a set of candidate answers; scoring, by a hypothesis and evidence scoring stage of the natural language processing pipeline, the set of candidate answers to generate for each candidate answer a confidence score; ranking, by an answer ranking stage of the natural language processing pipeline, the set of candidate answers by confidence score to form a ranked set of candidate answers; and outputting, by the natural language processing pipeline, the ranked set of candidate answers. 5. The method of claim 1 further comprising training the verb/type lookup resource using a type database resource and a corpus of information.