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In this paper, the authors use the 2012 log files of two German online dictionaries (Digital Dictionary of the German Language and the German Version of Wiktionary) and the 100,000 most frequent words in the Mannheim German Reference Corpus from 2009 to answer the question of whether dictionary users really do look up frequent words, first asked by de Schryver et al. (2006). By using an approach to the comparison of log files and corpus data which is completely different from that of the aforementioned authors, we provide empirical evidence that indicates - contrary to the results of de Schryver et al. and Verlinde/Binon (2010) - that the corpus frequency of a word can indeed be an important factor in determining what online dictionary users look up. Finally, we incorporate word class Information readily available in Wiktionary into our analysis to improve our results considerably.
This paper presents a dictionary writing system developed at the Institute for the German Language in Mannheim (IDS) for an ongoing international lexicographical project that traces the way of German loanwords in the East Slavic languages Russian, Belarusian and Ukrainian that were possibly borrowed via Polish. The results will be published in the Lehnwortportal Deutsch (LWP, lwp.ids-mannheim.de), a web portal for loanword dictionaries with German as the common donor language. The system described here is currently in use for excerpting data from a large range of historical and contemporary East Slavic monolingual dictionaries. The paper focuses on the tools that help in merging excerpts that are etymologically related to one and the same Polish etymon. The merging process involves eliminating redundancies and inconsistencies and, above all, mapping word senses of excerpted entries onto a common cross-language set of ‘metasenses’. This mapping may involve literally hundreds of excerpted East Slavic word senses, including quotations, for one ‘underlying’ Polish etymon.
The wdlpOst dictionary writing system to be presented in this paper has been developed for the specific purposes of a lexicographical project on German loanwords in the East Slavic languages Russian, Belarusian, and Ukrainian. The project’s main objectives are (i) to document those loanwords for which a cognate lexical borrowing from German is known in Polish and (ii) to establish possible borrowing pathways for these lexical items. In the first phase of the project, the collaborative client/server architecture of the wdlpOst system has been used for excerpting detailed lexicographical information from a large range of historical and contemporary East Slavic dictionaries, taking the entries in a large dictionary of German loanwords in Polish as a common frame of reference. For the project’s second phase, the wdlpOst system provides innovative tooling for compiling entries of the East Slavic loanwords. Most importantly, the numerous word sense definitions for a set of cognate loanwords, as excerpted from different lexicographical sources, are mapped onto a system of newly defined cross-language word senses; in a similar vein, the phonemic and graphemic variation in the loanwords and their derivatives is captured through a tool that abstracts from dictionary-specific idiosyncrasies.
We present the conceptual foundations and basic features of fLexiCoGraph, a generic software package for creating and presenting curated human-oriented lexicographical resources that are roughly modeled according to Měchura’s (2016) idea of graph-augmented trees. The system is currently under development and will be made accessible as open source software. As a sample use case we discuss an existing online database of loanwords borrowed from German into other languages which is based on a growing number of language-specific loanword dictionaries (Lehnwortportal Deutsch). The paper outlines the conceptual foundations of fLexiCoGraph’s hybrid graph/XML data model. To establish a database, XML-based resources may be imported or even input manually. An additional graph database layer is then constructed from these XML source documents in a freely configurable, but automated way; subsequently, the resulting graph can be manipulated and enlarged through a visual user interface in such a way that keeps the relationship to the source document information explicit at all times. We sketch the tooling support for different kinds of graph-level editing processes, including mechanisms for dealing with updated XML source documents and coping with duplicate or inconsistent information, and briefly discuss the browser interface for end users.