Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Artificial Intelligence
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MTTG '11 Proceedings of the Workshop on Monolingual Text-To-Text Generation
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MTTG '11 Proceedings of the Workshop on Monolingual Text-To-Text Generation
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Sentence fusion enables summarization and question-answering systems to produce output by combining fully formed phrases from different sentences. Yet there is little data that can be used to develop and evaluate fusion techniques. In this paper, we present a methodology for collecting fusions of similar sentence pairs using Amazon's Mechanical Turk, selecting the input pairs in a semi-automated fashion. We evaluate the results using a novel technique for automatically selecting a representative sentence from multiple responses. Our approach allows for rapid construction of a high accuracy fusion corpus.