Predicting lexical answer types in open domain question and answering (QA) systems
First Claim
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1. A system for predicting a lexical answer types (LAT) in a question comprising:
- a memory storage device including a plurality of syntactic frames;
a processor device operatively connected to said memory storage device and configured to;
receive a question text string;
extract at least one syntactic frame from said question string,designate, in said syntactic frame, a placeholder for an entity corresponding to a potential lexical answer type; and
query a lexical knowledge database to automatically obtain at least one replacement term for said placeholder of said at least one syntactic frame,wherein said entity placeholder is a part of a question focus indicating a LAT of the question.
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Abstract
In an automated Question Answer (QA) system architecture for automatic open-domain Question Answering, a system, method and computer program product for predicting the Lexical Answer Type (LAT) of a question. The approach is completely unsupervised and is based on a large-scale lexical knowledge base automatically extracted from a Web corpus. This approach for predicting the LAT can be implemented as a specific subtask of a QA process, and/or used for general purpose knowledge acquisition tasks such as frame induction from text.
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Citations
9 Claims
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1. A system for predicting a lexical answer types (LAT) in a question comprising:
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a memory storage device including a plurality of syntactic frames; a processor device operatively connected to said memory storage device and configured to; receive a question text string; extract at least one syntactic frame from said question string, designate, in said syntactic frame, a placeholder for an entity corresponding to a potential lexical answer type; and query a lexical knowledge database to automatically obtain at least one replacement term for said placeholder of said at least one syntactic frame, wherein said entity placeholder is a part of a question focus indicating a LAT of the question. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification