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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.
This paper describes the application of probabilistic part of speech taggers to the Dzongkha language. A tag set containing 66 tags is designed, which is based on the Penn Treebank. A training corpus of 40,247 tokens is utilized to train the model. Using the lexicon extracted from the training corpus and lexicon from the available word list, we used two statistical taggers for comparison reasons. The best result achieved was 93.1% accuracy in a 10-fold cross validation on the training set. The winning tagger was thereafter applied to annotate a 570,247 token corpus.
Knowledge in textual form is always presented as visually and hierarchically structured units of text, which is particularly true in the case of academic texts. One research hypothesis of the ongoing project Knowledge ordering in texts - text structure and structure visualisations as sources of natural ontologies1 is that the textual structure of academic texts effectively mirrors essential parts of the knowledge structure that is built up in the text. The structuring of a modern dissertation thesis (e.g. in the form of an automatically generated table of contents - toes), for example, represents a compromise between requirements of the text type and the methodological and conceptual structure of its subject-matter. The aim of the project is to examine how visual-hierarchical structuring systems are constructed, how knowledge structures are encoded in them, and how they can be exploited to automatically derive ontological knowledge for navigation, archiving, or search tasks. The idea to extract domain concepts and semantic relations mainly from the structural and linguistic information gathered from tables of contents represents a novel approach to ontology learning.
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.
How (and when) do speakers generalise from memorised exemplars of a construction to a productive schema? The present paper presents a novel take on this issue by offering a corpus-based approach to semantic extension processes. Focusing on clusters of German ADJ N expressions involving the heavily polysemous adjective tief ‚deep’, it is shown that type frequency (a commonly used measure of productivity) needs to be relativised to distinct semantic classes within the overall usage spectrum of a given construction in order to predict the occurrence of novel types within a particular region of this spectrum. Some methodological and theoretical implications for usage-based linguistic model building are considered.
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.
Some grammatical phenomena that only seldom appear in the corpora of written language often coincide with Speakers' uncertainty about a given form's grammatical Status. Such display of uncertainty is often subject to prescriptive criticism, which pays little attention to actual usage. However, thorough and discriminating corpus analyses can help in a proper description of various low-frequency phenomena and in situating them more adequately in the grammatical System, against the background of different contexts, communicative situations, and language varieties. To exemplify this potential, this study examines three linguistic phenomena in German, using a corpus-based approach: the dative singular ending -e, the construction aus aller Herren Länder, which lacks the dative plural ending -t and the non-standard preterite form frug. The results can be seen as a contribution to a more precise grammatical description on the one hand and, on the other, as a basis for an improved, more usage-oriented approach in providing practical advice to language users.
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.
This paper describes the efforts in the field of sustainability of the Institut für Deutsche Sprache (IDS) in Mannheim with respect to DEREKO (Deutsches Referenzkorpus) the Archive of General Reference Corpora of Contemporary Written German. With focus on re-usability and sustainability, we discuss its history and our future plans. We describe legal challenges related to the creation of a large and sustainable resource; sketch out the pipeline used to convert raw texts to the final corpus format and outline migration plans to TEI P5. Due to the fact, that the current version of the corpus management and query system is pushed towards its limits, we discuss the requirements for a new version which will be able to handle current and future DEREKO releases. Furthermore, we outline the institute’s plans in the field of digital preservation.