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The project elexiko compiles an extensive, monolingual dictionary of Contemporary German. This contribution deals with the grammatical data in this dictionary; it is not only described how these are arranged content-wise depending on corpus data, but also how they were modelled.
Das Projekt elexiko erarbeitet ein umfangreiches, einsprachiges Wörterbuch des Gegenwartsdeutschen. In diesem Beitrag geht es um die grammatischen Angaben in diesem Wörterbuch; es wird nicht nur erläutert, wie diese inhaltlich in Abhängigkeit vom Prinzip der Korpusbasiertheit gestaltet sind, sondern auch, wie sie modelliert wurden.
Automatic summarization systems usually are trained and evaluated in a particular domain with fixed data sets. When such a system is to be applied to slightly different input, labor- and cost-intensive annotations have to be created to retrain the system. We deal with this problem by providing users with a GUI which allows them to correct automatically produced imperfect summaries. The corrected summary in turn is added to the pool of training data. The performance of the system is expected to improve as it adapts to the new domain.
In this contribution we present some work of the R&D European project “LIRICS” and of the ISO/TC 37/SC 4 committee related to the topic of interoperability and re-use of language resources. We introduce some basic mechanisms of the standardization work in ISO and describe in more details the general approach on how to cope with the annotation of language data within ISO.
This study investigates the question of whether the processing of complex anaphors require more cognitive effort than the processing of NP-anaphors. Complex anaphors refer to abstract objects which are not introduced as a noun phrase and bring about the creation of a new discourse referent. This creation is called “complexation process”. We describe ERP findings which provide converging support for the assumption that the cognitive cost of this complexation process is higher than the cognitive cost of processing NP-anaphors.
Lexical resources are often represented in table form, e. g., in relational databases, or represented in specially marked up texts, for example, in document based XML models. This paper describes how it is possible to model lexical structures as graphs and how this model can be used to exploit existing lexical resources and even how different types of lexical resources can be combined.