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SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts

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arxiv 2303.14337 v3 pith:DBHC754U submitted 2023-03-25 cs.CL

classification cs.CL
keywords situationreportssmartbookanalystsgenerationintelligencereportcomprehensive
verification ladder T0 review T1 audit T2 compute T3 formal
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Timely and comprehensive understanding of emerging events is crucial for effective decision-making; automating situation report generation can significantly reduce the time, effort, and cost for intelligence analysts. In this work, we identify intelligence analysts' practices and preferences for AI assistance in situation report generation to guide the design strategies for an effective, trust-building interface that aligns with their thought processes and needs. Next, we introduce SmartBook, an automated framework designed to generate situation reports from large volumes of news data, creating structured reports by automatically discovering event-related strategic questions. These reports include multiple hypotheses (claims), summarized and grounded to sources with factual evidence, to promote in-depth situation understanding. Our comprehensive evaluation of SmartBook, encompassing a user study alongside a content review with an editing study, reveals SmartBook's effectiveness in generating accurate and relevant situation reports. Qualitative evaluations indicate over 80% of questions probe for strategic information, and over 90% of summaries produce tactically useful content, being consistently favored over summaries from a large language model integrated with web search. The editing study reveals that minimal information is removed from the generated text (under 2.5%), suggesting that SmartBook provides analysts with a valuable foundation for situation reports

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real World

    cs.CL 2025-06 conditional novelty 7.0 of 10

    LEMONADE is a new 20-language, expert-annotated conflict event dataset for abstractive event extraction, and ZEST, a zero-shot retrieval entity linker, beats prior zero-shot baselines but trails supervised models.

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