Korpuslinguistik
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Discourse segmentation is the division of a text into minimal discourse segments, which form the leaves in the trees that are used to represent discourse structures. A definition of elementary discourse segments in German is provided by adapting widely used segmentation principles for English minimal units, while considering punctuation, morphology, sytax, and aspects of the logical document structure of a complex text type, namely scientific articles. The algorithm and implementation of a discourse segmenter based on these principles is presented, as well an evaluation of test runs.
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.
Within cognitive linguistics, there is an increasing awareness that the study of linguistic phenomena needs to be grounded in usage. Ideally, research in cognitive linguistics should be based on authentic language use, its results should be replicable, and its claims falsifiable. Consequently, more and more studies now turn to corpora as a source of data. While corpus-based methodologies have increased in sophistication, the use of corpus data is also associated with a number of unresolved problems. The study of cognition through off-line linguistic data is, arguably, indirect, even if such data fulfils desirable qualities such as being natural, representative and plentiful. Several topics in this context stand out as particularly pressing issues. This discussion note addresses (1) converging evidence from corpora and experimentation, (2) whether corpora mirror psychological reality, (3) the theoretical value of corpus linguistic studies of ‘alternations’, (4) the relation of corpus linguistics and grammaticality judgments, and, lastly, (5) the nature of explanations in cognitive corpus linguistics. We do not claim to resolve these issues nor to cover all possible angles; instead, we strongly encourage reactions and further discussion.
Contemporary studies on the characteristics of natural language benefit enormously from the increasing amount of linguistic corpora. Aside from text and speech corpora, corpora of computer-mediated communication (CMC) Position themselves between orality and literacy, and beyond that provide in- sight into the impact of "new", mainly intemet-based media on language beha- viour. In this paper, we present an empirical attempt to work with annotated CMC corpora for the explanation of linguistic phenomena. In concrete terms, we implement machine leaming algorithms to produce decision trees that reveal rules and tendencies about the use of genitive markers in German.
Using the Google Ngram Corpora for six different languages (including two varieties of English), a large-scale time series analysis is conducted. It is demonstrated that diachronic changes of the parameters of the Zipf–Mandelbrot law (and the parameter of the Zipf law, all estimated by maximum likelihood) can be used to quantify and visualize important aspects of linguistic change (as represented in the Google Ngram Corpora). The analysis also reveals that there are important cross-linguistic differences. It is argued that the Zipf–Mandelbrot parameters can be used as a first indicator of diachronic linguistic change, but more thorough analyses should make use of the full spectrum of different lexical, syntactical and stylometric measures to fully understand the factors that actually drive those changes.
Distributional models of word use constitute an indispensable tool in corpus based lexicological research for discovering paradigmatic relations and syntagmatic patterns (Belica et al. 2010). Recently, word embeddings (Mikolov et al. 2013) have revived the field by allowing to construct and analyze distributional models on very large corpora. This is accomplished by reducing the very high dimensionality of word cooccurrence contexts, the size of the vocabulary, to few dimensions, such as 100-200. However, word use and meaning can vary widely along dimensions such as domain, register, and time, and word embeddings tend to represent only the most prevalent meaning. In this paper we thus construct domain specific word embeddings to allow for systematically analyzing variations in word use. Moreover, we also demonstrate how to reconstruct domain specific co-occurrence contexts from the dense word embeddings.
This paper discusses a theoretical and empirical approach to language fixedness that we have developed at the Institut für Deutsche Sprache (IDS) (‘Institute for German Language’) in Mannheim in the project Usuelle Worterbindungen(UWV) over the last decade. The analysis described is based on the Deutsches Referenzkorpus (‘German Reference Corpus’; DeReKo) which is located at the IDS. The corpus analysis tool used for accessing the corpus data is COSMAS II (CII) and – for statistical analysis – the IDS collocation analysis tool (Belica, 1995; CA). For detecting lexical patterns and describing their semantic and pragmatic nature we use the tool lexpan (or ‘Lexical Pattern Analyzer’) that was developed in our project. We discuss a new corpus-driven pattern dictionary that is relevant not only to the field of phraseology, but also to usage-based linguistics and lexicography as a whole.
In this paper, we present an overview of freely available web applications providing online access to spoken language corpora. We explore and discuss various solutions with which the corpus providers and corpus platform developers address the needs of researchers who are working with spoken language. The paper aims to contribute to the long-overdue exchange and discussion of methods and best practices in the design of online access to spoken language corpora.