Korpuslinguistik
Refine
Year of publication
Document Type
- Conference Proceeding (81)
- Part of a Book (77)
- Article (34)
- Book (9)
- Other (4)
- Working Paper (4)
- Doctoral Thesis (2)
- Part of Periodical (2)
- Bachelor Thesis (1)
- Review (1)
Language
- German (111)
- English (103)
- Multiple languages (1)
Is part of the Bibliography
- no (215) (remove)
Keywords
- Korpus <Linguistik> (215) (remove)
Publicationstate
- Veröffentlichungsversion (142)
- Zweitveröffentlichung (44)
- Postprint (2)
Reviewstate
Publisher
- de Gruyter (33)
- Institut für Deutsche Sprache (26)
- Narr (20)
- European Language Resources Association (ELRA) (7)
- Leibniz-Institut für Deutsche Sprache (7)
- Leibniz-Institut für Deutsche Sprache (IDS) (7)
- European Language Resources Association (5)
- Niemeyer (4)
- Nisaba (4)
- Gesellschaft für Sprachtechnologie und Computerlinguistik (3)
The project Referenzkorpus Altdeutsch (‘Old German Reference Corpus’) aims to es- tablish a deeply-annotated text corpus of all extant Old German texts. As the automated part-of-speech and morphological pre-annotation is amended by hand, a quality control system for the results seems a desirable objective. To this end, standardized inflectional forms, generated using the morphological information, are compared with the attested word forms. Their creation is described by way of example for the Old High German part of the corpus. As is shown, in a few cases, some features of the attested word forms are also required in order to determine as exactly as possible the shape of the inflected lemma form to be created.
The availability of electronic corpora of historical stages of languages has been wel- comed as possibly attenuating the inherent problem of diachronic linguistics, i.e. that we only have access to what has chanced to come down to us - the problem which was memorably named by Labov (1992) as one of “Bad Data”. However, such corpora can only give us access to an increased amount ot historical material and this can essentially still only be a partial and possibly distorted picture of the actual language at a particular period of history. Corpora can be improved by taking a more representative sample of extant texts if these are available (as they are in significant number for periods after the invention of printing). But, as examples from the recently compiled GerManC corpus of seventeenth and eighteenth century German show, the evidence from such corpora can still fail to yield definitive answers to our questions about earlier stages of a language. The data still require expert interpretation, and it is important to be realistic about what can legitimately be expected from an electronic historical corpus.
Multi-faceted alignment. Toward automatic detection of textual similarity in Gospel-derived texts
(2015)
Ancient Germanic Bible-derived texts stand in as test material for producing computational means for automatically determining where textual contamination and linguistic interference have influenced the translation process. This paper reports on the results of research efforts that produced a text corpus; a method for decomposing the texts involved into smaller, more directly comparable thematically-related chunks; a database of relationships between these chunks; and a user-interface allowing for searches based on various referential criteria. Finally, the state of the product at the end of the project is discussed, namely as it was handed over to another researcher who has extended it to automatically find semantic and syntactic similarities within comparable chunks.
In this paper we present some preliminary considerations concerning the possibility of automatic parsing an annotated corpus for N-N compounds. This should in prin- ciple be possible at least for relational and stereotype compounds, if the lemmatization of the corpus connects the lemmata with lexical entries as described in Höhle (1982). These lexical entries then supply the necessary information about the argument structure of a relational noun or about the stereotypical purpose associated with the noun’s referent which can be used to establish a relation between the first and the head constituent of the compound.
The relative order of dative and accusative objects in older German is less free than it is today. The reason for this could be that speakers of the direct predecessor of Old High German organized the referents according to the Thematic Hierarchy. If one applies a Case Hierarchy Nom>Acc>Dat to this, the order Nom - Dat - Acc falls out. It becomes apparent that the status of the Thematic Hierarchy is not a factor governing underlying word order, but a factor inducing scrambling. Arguments from binding theory, whose validity is discussed, indicate that the underlying order is ‘accusative before dative’
GraphVar ist ein Korpus aus über 1.600 Abiturarbeiten, die zwischen 1917 und 2018 an einem niedersächsischen Gymnasium geschrieben wurden. Das Hauptinteresse beim Aufbau bestand in der Beschreibung graphematischer Variation und ihrer Entwicklung über die Zeit. Leitend war die Frage, was Schreiberinnen und Schreiber eigentlich tatsächlich machen bzw. gemacht haben – und zwar unbeeinflusst von technischen Hilfsmitteln oder Schluss- und Endredaktion, aber unter vergleichbaren Bedingungen. Das Korpus bietet somit ein Fenster auf den unverfälschten Schreibgebrauch von Abiturientinnen und Abiturienten im Laufe der Zeit. Zum jetzigen Zeitpunkt sind 1.618 Arbeiten transkribiert, linguistisch annotiert und über eine ANNIS-Instanz erreichbar (graphvar.unibonn.de, Stand: 8.8.2023). Im Sommer 2022 konnten weitere 1.600 Arbeiten zwischen 1900 und 2021 an einem Gymnasium in Nordrhein-Westfalen digitalisiert werden. Neben schriftlinguistischen Fragestellungen ist das Korpus prinzipiell auch für syntaktische, morphologische und lexikalische Fragestellungen geeignet; auch didaktische Untersuchungen sind möglich, genau wie kulturwissenschaftliche.
Dieser Beitrag beschreibt die Prozesse der Datenerhebung, -aufbereitung und geplanten Veröffentlichung eines Teilkorpus des vom österreichischen Wissenschaftsfonds (FWF) finanzierten Spezialforschungsbereichs (SFB) „Deutsch in Österreich. Variation – Kontakt – Perzeption“ (FWF F060). Die Daten werden v. a. aus variationslinguistischer, kontaktlinguistischer wie auch perzeptionslinguistischer Perspektive analysiert, wofür eigene Tools entwickelt wurden, die – ebenso wie das Korpus selbst – mittelfristig der interessierten Öffentlichkeit zur Verfügung gestellt werden.
Das Werk versteht sich als eine Darstellung der wichtigsten syntaktischen, prosodischen, semantischen und pragmatischen Eigenschaften kausaler und konditionaler Konnektoren des gesprochenen Deutsch.
Die Untersuchung formuliert notwendige theoretische Grundlagen und zeigt die komplexe Interaktion mehrerer Faktoren, die sich auf die Interpretation einer Äußerung auswirken. Empirische Daten belegen, dass die kontextuelle und pragmatische Interpretation der untersuchten Relationen stark mit ihren syntaktischen und prosodischen Mustern korreliert. Jedoch handelt es sich nicht um eine Eins-zu-eins-Beziehung, denn gleiche Lesarten können von kausalen und konditionalen Relationen unterschiedlich markiert sein. Anhand der Ergebnisse wird das Verhältnis zwischen Konditionalität und Kausalität diskutiert.
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.