In this paper, we motivate the need for a publicly available, generic software framework for question-answering (QA) systems. We present an open-source QA framework QANUS which researchers can leverage on to build new QA systems easily and rapidly. The framework implements much of the code that will otherwise have been repeated across different QA systems. To demonstrate the utility and practicality of the framework, we further present a fully functioning factoid QA system QA-SYS built on top of QANUS.
Though few in numbers, some QA systems have previously been made available to the community. One such system is Available for download at http: www.umiacs.umd.edu @math jimmylin downloads index.html @cite_1 . is a factoid QA system which seeks to exploit the redundancy of data on the web and has achieved credible performances at past TREC evaluations. is not designed however as a generic QA platform. We argue that a framework such as which is designed from the start with extensibility and flexibility in mind will greatly reduce the effort needed for any such customisation.
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The so-called “redundancy-based” approach to question answering represents a successful strategy for mining answers to factoid questions such as “Who shot Abraham Lincolnq” from the World Wide Web. Through contrastive and ablation experiments with Aranea, a system that has performed well in several TREC QA evaluations, this work examines the underlying assumptions and principles behind redundancy-based techniques. Specifically, we develop two theses: that stable characteristics of data redundancy allow factoid systems to rely on external “black box” components, and that despite embodying a data-driven approach, redundancy-based methods encode a substantial amount of knowledge in the form of heuristics. Overall, this work attempts to address the broader question of “what really matters” and to provide guidance for future researchers.