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This paper describes SMES, an information extraction core system for real world German text processing. The basic design criterion of the system is of providing a set of basic powerful, robust, and eecient natural language components and generic linguistic knowledge sources which can easily be customized for processing diierent tasks in a exible manner.
We present a new model of natural language processing in which natural language parsing and generation are strongly interleaved tasks. Interleaving of parsing and generation is important if we assume that natural language understanding and production are not only performed in isolation but also can work together to obtain subsentential interactions in text(More)
We present a divide-and-conquer strategy based on finite state technology for shallow parsing of real-world German texts. In a first phase only the topo-logical structure of a sentence (i.e., verb groups, subclauses) are determined. In a second phase the phrasal grammars are applied to the contents of the different fields of the main and sub-clauses.(More)
This paper 1 presents a new model for the production of natural language. The novel idea is to combine incremental and bidirectional generation with parallelism. The operational basis of our model is a distributed parallel system at every level of representation. Starting point of the production are segments of the conceptual level. These segments are(More)
This paper ~ describes the construction of syntactic structures within an incremental multi-level and parallel generation system. Incremental and parallel generation imposes special requirements upon syntactic description and processing. A head-driven grammar represented in a unification-based formalism is introduced which satisfies these demands.(More)
This paper presents the Excitement Open Platform (EOP), a generic architecture and a comprehensive implementation for tex-tual inference in multiple languages. The platform includes state-of-art algorithms, a large number of knowledge resources, and facilities for experimenting and testing innovative approaches. The EOP is distributed as an open source(More)
This paper presents a method for the automatic extraction of subgrammars to control and speeding-up natural language generation NLG. The method is based on explanation-based learning EBL. The main advantage for the proposed new method for NLG is that the complexity of the grammatical decision making process during NLG can be vastly reduced, because the EBL(More)