Tomek Strzalkowski

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The problem of quantitatively comparing tile performance of different broad-coverage grammars of English has to date resisted solution. Prima facie, known English grammars appear to disagree strongly with each other as to the elements of even tile simplest sentences. For instance, the grammars of Steve Abney (Bellcore), Ezra Black (IBM), Dan Flickinger(More)
In this paper we report on the joint GE/Lockheed Martin/Rutgers/NYU natural language information retrieval project as related to the 5th Text Retrieval Conference (TREC-5). The main thrust of this project is to use natural language processing techniques to enhance the effectiveness of full-text document retrieval. Since our first TREC entry in 1992 (as NYU(More)
This article describes our novel approach to the automated detection and analysis of metaphors in text. We employ robust, quantitative language processing to implement a system prototype combined with sound social science methods for validation. We show results in 4 different languages and discuss how our methods are a significant step forward from(More)
HITIQA is an interactive question answering technology designed to allow intelligence analysts and other users of information systems to pose questions in natural language and obtain relevant answers, or the assistance they require in order to perform their tasks. Our objective in HITIQA is to allow the user to submit exploratory, analytical, non-factual(More)
One central goal of the AMITIÉS multilingual humancomputer dialogue project is to create a dialogue management system capable of engaging the user in human-like conversation in a specific domain. To that end, we have developed new methods for the manual annotation of spoken dialogue transcriptions from European financial call centers. We have modified the(More)
Natural language processing techniques may hold a tremendous potential for overcoming the inadequacies of purely quantitative methods of text information retrieval, but the empirical evidence to support such predictions has thus far been inadequate, and appropriate scale evaluations have been slow to emerge. In this chapter, we report on the progress of the(More)
Natural language processing techniques may hold a tremendous potential for overcoming the inadequacies of purely quantitative methods of text information retrieval, but the empirical evidence to support such predictions has thus far been inadequate, and appropriate scale evaluations have been slow to emerge. In this chapter, we report on the progress of the(More)