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Complex common names such as Indian elephant or green tea denote a certain type of entity, viz. kinds. Moreover, those kinds are always subkinds of the kind denoted by their head noun. Establishing such subkinds is essentially the task of classifying modifiers that are a defining trait of endocentrically structured complex common names. Examining complex common names of different lexico-syntactic types(NN compounds, N+N syntagmas, NP/PP syntagmas, A+N syntagmas) and from different languages (particularly English, German and French) it can be shown that complex common names are subject to language- independent formal and semantic constraints. In particular, complex common names qualify as name-like expressions in that they tend to be deficient in terms of formal complexity and semantic compositionality.
This article introduces the topic of ‘‘Multilingual language resources and interoperability’’. We start with a taxonomy and parameters for classifying language resources. Later we provide examples and issues of interoperatability, and resource architectures to solve such issues. Finally we discuss aspects of linguistic formalisms and interoperability.
We report on finished work in a project that is concerned with providing methods, tools, best practice guidelines, and solutions for sustainable linguistic resources. The article discusses several general aspects of sustainability and introduces an approach to normalizing corpus data and metadata records. Moreover, the architecture of the sustainability platform implemented by the authors is described.
This article shows that the TEI tag set for feature structures can be adopted to represent a heterogeneous set of linguistic corpora. The majority of corpora is annotated using markup languages that are based on the Annotation Graph framework, the upcoming Linguistic Annotation Format ISO standard, or according to tag sets defined by or based upon the TEI guidelines. A unified representation comprises the separation of conceptually different annotation layers contained in the original corpus data (e.g. syntax, phonology, and semantics) into multiple XML files. These annotation layers are linked to each other implicitly by the identical textual content of all files. A suitable data structure for the representation of these annotations is a multi-rooted tree that again can be represented by the TEI and ISO tag set for feature structures. The mapping process and representational issues are discussed as well as the advantages and drawbacks associated with the use of the TEI tag set for feature structures as a storage and exchange format for linguistically annotated data.