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USER. Questions. Cyc KB Server. Clarifications. KRAKEN-UIA. Cyc Knowledge Base. Answers. Clarif. Questions. RDBMs Server. Questions. QUIRK light. Cyc Inference Engine. NIMA, USGS. Answers. GuruQA IR Agent. SDBC Proxy. SKSI Layer. IR / Text Analysis Server.
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USER Questions Cyc KB Server Clarifications KRAKEN-UIA Cyc Knowledge Base Answers Clarif. Questions RDBMs Server Questions QUIRK light Cyc InferenceEngine NIMA, USGS Answers GuruQA IR Agent SDBC Proxy SKSI Layer IR / Text Analysis Server IR / Text Analysis Server Zope Web Application Server HTTP Server (Apache) Resporator GuruQA Wordnet Glimpse Lemur Depend. Parser Charniak Parser Components:CycorpIBMOpen Source Talent QUIRK: QUestion answering (QU) =Information Retrieval (IR) +Knowledge (K)Cycorp / IBM T. J. Watson Research Center • OBJECTIVES • Share infrastructure, IR, KR & NLP • components and information sources • with parallel IBM / Cycorp project • Focus on “Deeper” Knowledge-Centered • approach to QA; Apply semantic coverage • & inference-based reasoning power of Cyc • Develop interactive question understanding • and refinement dialog capability • Decompose questions into individual queries for structured, semi-structured and • unstructured data sources PLAN • Build on Cyc Knowledge Base and Knowledge Server; Combine Cyc and IBM NLP components • Use Cyc KB interface to Structured Data Sources; IBM IR interface to Unstructured Data Sources • Integrate other open-domain NLP and IR tools Topic Area: Total System Data Dimension: Structured / Unstructured Principal Investigators: Stefano Bertolo, Cycorp/ David Ferrucci, IBM