SBIR Phase I: Customizable Question Answering System for Homeland Security and Commercial Applications

这个小型企业创新研究(SBIR)第一阶段项目提出了一种新的问答(QA)技术。拟议活动的智力优点有三个方面：(1)它自动将高级问题分解为逻辑的、信息丰富的事实探求问题集，从而可以自动回答非常复杂的问题。这种新颖的QA方法推进了最先进的技术，目前仅限于简单的事实问题，能够回答复杂的问题，这些问题模拟了在实际客户环境中观察到的场景。(2)通过使用逻辑证明器来提取和证明答案，从根本上提高了当前最先进的QA的准确性。语言计算机公司(LLC)计划开发一种用于问答的推理机制，该机制能够基于语义推理链而不是表面的基于关键字的度量来提取答案。(3)提出了一种新的方法，利用自动获取的本体将开放领域的问答技术应用于领域特定的信息，并与系统的开放领域知识库无缝集成。这种能力为大规模杀伤性武器等不同兴趣领域提供了一种快速高效的定制方法。所提供的技术的广泛影响如下：(1)该方法允许QA技术将其能力从目前仅限于基于简单的事实问题的综合评估扩展到具有复杂问题和场景的实际商业应用。这使有限责任公司能够同时瞄准政府和商业市场，在这两个市场中，检索到的信息的准确性、覆盖面、可靠性和可用性至关重要。这项QA技术的理想应用包括国土防务、客户关系管理(CRM)、教育、医疗和法律。(2)该模型使用了一种逻辑证明机制，该机制将每个提取的答案与对答案正确性的逻辑、易于理解的解释相关联。此外，LLC建议引入一个自动程序，以使开放领域的QA系统快速适应特定于领域的场景。这一组功能使该QA系统成为情报业务的理想工具，在情报业务中，提取的信息的质量至关重要，并且经常在完全不同的感兴趣领域之间切换。

This Small Business Innovation Research (SBIR) Phase I project proposes a novel Question Answering (QA) technology. The intellectual merits of the proposed activity are three fold: (1) it provides automatic decomposition of high level questions into logical, informative sets of fact-seeking questions, such that very complex questions can be automatically answered. This novel QA approach advances the state-of-the-art technology, which is currently limited to simple factual questions, enabling the answering of complex questions that model scenarios observed in actual customer environments. (2) It radically improves the accuracy of current state-of-the-art QA by using a logic prover to extract and justify answers. Language Computer Corporation (LLC) plans to develop an inference mechanism for question answering that is capable of extracting answers based on semantic inference chains, rather than on superficial keyword-based metrics. (3) It introduces a novel approach that adapts open-domain QA technology to domain-specific information using automatically acquired ontologies, seamlessly integrated with the system's open-domain knowledge base. This capability provides a rapid and efficient customization method for various domains of interests, such as weapons of mass destruction.The broader impact of the proffered technology is as follows: (1) the proposed approach allows QA technology to expand its capability, now restricted to synthetic evaluations based on simple, factual questions, to actual commercial applications with complex questions and scenarios. This places LLC in a position to target both government and commercial markets, where the accuracy, coverage, reliability and usability of the retrieved information are crucial. Ideal applications for this QA technology include homeland defense, Customer Relationship Management (CRM), education, medical, and legal. (2) The proposed model uses a logic proving mechanism that associates every extracted answer with a logical, easily understandable explanation of the answer correctness. Furthermore, LLC proposes the introduction of an automatic procedure to quickly adapt an open-domain QA system to domain-specific scenarios. This set of features makes this QA system an ideal tool for the intelligence business, where the quality of the information extracted is paramount, and where switching between completely different domains of interest is frequent.