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The problem of quantitatively comparing tile performance of different broad-coverage grammars of En-glish 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 Abneying), Don tfindle (AT&T), Bob Ingria (BBN), and(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)
This paper reports on some recent developments in our natural language text retrieval system. The system uses advanced natural language processing techniques to enhance the effectiveness of term-based document retrieval. The backbone of our system is a traditional statistical engine which builds inverted index files from pre-processed documents, and then(More)
† HITIQA (High Quality Interactive Question Answering) is currently being developed to assist analysts in finding answers to complex intelligence problems, efficiently and thoroughly. The system uses event-based, data-driven semantic processing and natural language dialogue, coupled with an advanced information visualization interface, to deliver accurate(More)
1. Summary The GE/Rutgers/SICS/Helsinki team has performed runs in the main ad-hoc task. All submissions are NLP-assisted retrieval. We used two retrieval engines: SMART and InQuery built into the stream model architecture where each stream represents an alternative text indexing method. The processing of TREC data was performed at Helsinki using the(More)