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• W2578080060 abstract "We present a novel approach to automated question generation that improves upon prior work both from a technology perspective and from an assessment perspective. Our system is aimed at engaging language learners by generating multiple-choice questions which utilize specific inference steps over multiple sentences, namely coreference resolution and paraphrase detection. The system also generates correct answers and semantically-motivated phrase-level distractors as answer choices. Evaluation by human annotators indicates that our approach requires a larger number of inference steps, which necessitate deeper semantic understanding of texts than a traditional single-sentence approach." @default.
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• W2578080060 date "2016-12-01" @default.
• W2578080060 modified "2023-09-24" @default.
• W2578080060 title "Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts." @default.
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