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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 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 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)
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)
Automatic intelligent web exploration will benefit from shallow information extraction techniques if the latter can be brought to work within many different domains. The major bottleneck for this, however, lies in the so far difficult and expensive modeling of lexical knowledge, extraction rules, and an ontology that together define the information(More)
We present an intelligent information agent that uses semantic methods and natural language processing capabilites in order to gather tourist information from the WWW and present it to the human user in an intuitive, user-friendly way. Thereby, the information agent is designed such that as background knowledge and linguistic coverage increase, its benefits(More)
This report describes the work done by the QA group of the Language Technology Lab at DFKI, for the 2004 edition of the Cross-Language Evaluation Forum (CLEF). Based on the experience we obtained through our participation at QA@Clef-2003 with our initial cross-lingual QA prototype system BiQue (cf. [NS03]), the focus of the system extension for this year's(More)