Abstract
The START system responds to natural language queries with answers in text, pictures, and other media. START's sentence-level natural language parsing relies on a number of mechanisms to help it process the huge, diverse resources available on the World Wide Web. Blitz, a hybrid heuristic- and corpus-based natural language preprocessor enables START to integrate a large and ever-changing lexicon of proper names, by using heuristic rules and precompiled tables of symbols to preprocess various highly regular and fixed expressions into lexical tokens. LaMeTH, a content-based system for extracting information from HTML documents, assists START by providing a uniform method of accessing information on the Web in real time. These mechanisms have considerably improved STARTS ability to analyze real-world sentences and answer queries through expansion of its lexicon and integration of Web resources.
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