Download Text Understanding in LILOG: Integrating Computational by Otthein Herzog, Claus-Rainer Rollinger PDF

By Otthein Herzog, Claus-Rainer Rollinger

The IBM venture LILOG awarded during this quantity represents a primary stepbeyond laptop technological know-how as hitherto understood. It used to be a winning venture in each appreciate and has make clear conjectured simple interrelations among wisdom processing and language definition. wisdom processing is strongly coupled to the ordinary language used, and for utilized wisdom processing a knowledge base is neededwhich defines the semantic contents and interrelations of the language. The LILOG venture was once an implementation of a knowledge basein the German language. a collection of instruments used to be additionally built to paintings with the process, together with established man-machine interfaces utilizing usual language, inference algorithms, and a whole subsystem to obtain and shop the mandatory wisdom. The LILOG venture began in 1985 and a practical method was once established in 1991. The undertaking concerned nearly two hundred of the scientists operating in Germany within the fields of computational linguistics, common language realizing platforms, and synthetic intelligence. The undertaking proves cooperative undertaking among universities and can produce precious effects either in natural learn and in carried out equipment and tools.

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Extra resources for Text Understanding in LILOG: Integrating Computational Linguistics and Artificial Intelligence Final Report on the IBM Germany LILOG-Project

Sample text

It is understood as (syntax : (direction : (left))), where any term in parentheses is a well-formed feature term. Note also that we can embed arbitrary feature terms with feature (or path) selection. , that this substructure is "shared" between these two paths. We do this by using an equation as in: [ syntax: [ value: syntax: s direction : left argument : np ] < s y n t a x v a l u e s e m a n t i c _ f o r m > = ] Logical Variables Variables in feature terms stand for specific nodes in the described feature graph.

In Proceedings of the l~4th Annual Meeting of the AC15, Columbia University, pp. 257-265, New York, NY, 1986 [PS87] Carl Pollard, Ivan A. Sag: Inlormation-Based Syntaz and Semantics. CSLI Lecture Notes 13. N. D. Warren: Definite dattse grammars for language analysis--a survey of the formalism and a comparison with augmented transition networks. Artificial Intelligence, 13:231-278, 1980 [Shi891 Stuart M. Shieber: Parsing and type inference for natural and computer languages. Technical Note 460, SRI International, Artificial Intelligence Center, Menlo Park, CA, March 1989 [SmoSSl Gert Smolksz A feature logic with subsorts.

5. " One is tempted to reverse his words when judging how far we have closed in toward our scenarios: despite its achievements, LILOG is but a stepping stone towards our loftier goals. In other words, LILOG is not the last piece in a linguistic puzzle, but rather the end of a climb to an intermediate vantage point which opens broad new vistas to future goals. Many of these goals have to do with the issues of Sect. 3 for which LILOG provides a much better understanding but which it by no means resolves.

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