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This paper shows how corpora and related tools can be used to analyse and present significant colligational patterns lexicographically. In German, patterns such as das nötige Wissen vermitteln and sein Wissen unter Beweis stellen play a vital role when learning the language, as they exhibit relevant idiomatic usage and lexical and syntactic rules of combination. Each item has specific semantic and grammatical functions and particular preferences with respect to position and distribution. An analysis of adjectives, for example, identifies preferences in adverbial, attributive, or predicative functions.
Traditionally, corpus analyses of syntagmatic constructions have not been conducted for lexicographic purposes. This paper shows how to utilise corpora to extract and examine typical syntagms and how the results of such an analysis are documented systematically in ELEXIKO, a large-scale corpus-based Internet reference work of German. It also demonstrates how this dictionary accounts for the lexical and grammatical interplay between units in a syntagm and how authentic corpus material and complementary prose-style usage notes are a useful guide to text production or reception.
Corpus-based identification and disambiguation of reading indicators for German nominalizations
(2010)
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must be made aware of ambiguities. Therefore, given an extraction task, all relevant ambiguities must be identified. To resolve these ambiguities, contextual data responsible for one or another reading is to be considered. In the context of our present work, German -ung-nominalizations and their sortal readings are under examination. A number of these nominalizations may be read as an event or a result, depending on the semantic group they belong to. Here, we concentrate on nominalizations of verbs of saying (henceforth: "verba dicendi"), identify their context partners and their influence on the sortal reading of the nominalizations in question. We present a tool which calculates the sortal reading of such nominalizations and thus may improve not only corpus extraction, but also e.g. machine translation. Lastly, we describe successful attempts to identify the correct sortal reading, conclusions and future work.
Empirical synchronic language studies generally seek to investigate language phenomena for one point in time, even though this point in time is often not stated explicitly. Until today, surprisingly little research has addressed the implications of this time-dependency of synchronic research on the composition and analysis of data that are suitable for conducting such studies. Existing solutions and practices tend to be too general to meet the needs of all kinds of research questions. In this theoretical paper that is targeted at both corpus creators and corpus users, we propose to take a decidedly synchronic perspective on the relevant language data. Such a perspective may be realised either in terms of sampling criteria or in terms of analytical methods applied to the data. As a general approach for both realisations, we introduce and explore the FReD strategy (Frequency Relevance Decay) which models the relevance of language events from a synchronic perspective. This general strategy represents a whole family of synchronic perspectives that may be customised to meet the requirements imposed by the specific research questions and language domain under investigation.