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<p><b>Abstract</b>—This paper presents a possible solution for the text inference problem—extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the basis for the development of a large linguistic knowledge base. The inference algorithm consists of a set of highly parallel search methods that, when applied to the knowledge base, find contexts in which sentences are interpreted. These contexts reveal information relevant to the text. Implementation, results, and parallelism analysis are discussed.</p>
Parallel search algorithms, parallel knowledge processing, marker propagations, natural language understanding, parallel inference, metrics for parallelism analysis, speed-up.

D. I. Moldovan and S. M. Harabagiu, "A Parallel System for Text Inference Using Marker Propagations," in IEEE Transactions on Parallel & Distributed Systems, vol. 9, no. , pp. 729-747, 1998.
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