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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’
This contribution explores the relationship between the English CEFR (Common European Framework of Reference for Languages) vocabulary levels and user interest in English Wiktionary entries. User interest was operationalized through the number of views of these entries in Wikimedia server logs covering a period of four years (2019–2022). Our findings reveal a significant relationship between CEFR levels and user interest: entries classified at lower CEFR levels tend to attract more views, which suggests a greater user interest in more basic vocabulary. A multiple regression model controlling for other known or potential factors affecting interest: corpus frequency, polysemy, word prevalence, and age of acquisition confirmed that lower CEFR levels attract significantly more views even after taking into account the other predictors. These findings highlight the importance of CEFR levels in predicting which words users are likely to look up, with implications for lexicography and the development of language learning materials.
In a previous study, Aceves and Evans present a large-scale quantitative information-theoretic analysis of parallel corpus data in ~1,000 languages to show that there are apparently strong associations between the way languages encode information into words and patterns of communication, e.g. the configuration of semantic information. During the peer review process, one reviewer raised the question of the extent to which the presented results depend on different corpus sizes (see the Peer Review File). This is a very important question given that most, if not all, of the quantities associated with word frequency distributions vary systematically with corpus size. While Aceves and Evans claim that corpus size does not affect the results presented, I challenge this view by presenting reanalyses of the data that clearly suggest that it does.
Less than one percent of words would be affected by gender-inclusive language in German press texts
(2024)
Research on gender and language is tightly knitted to social debates on gender equality and non-discriminatory language use. Psycholinguistic scholars have made significant contributions in this field. However, corpus-based studies that investigate these matters within the context of language use are still rare. In our study, we address the question of how much textual material would actually have to be changed if non-gender-inclusive texts were rewritten to be gender-inclusive. This quantitative measure is an important empirical insight, as a recurring argument against the use of gender-inclusive German is that it supposedly makes written texts too long and complicated. It is also argued that gender-inclusive language has negative effects on language learners. However, such effects are only likely if gender-inclusive texts are very different from those that are not gender-inclusive. In our corpus-linguistic study, we manually annotated German press texts to identify the parts that would have to be changed. Our results show that, on average, less than 1% of all tokens would be affected by gender-inclusive language. This small proportion calls into question whether gender-inclusive German presents a substantial barrier to understanding and learning the language, particularly when we take into account the potential complexities of interpreting masculine generics.
In this article, we provide an insight into the development and application of a corpus-lexicographic tool for finding neologisms that are not yet listed in German dictionaries. As a starting point, we used the words listed in a glossary of German neologisms surrounding the COVID-19 pandemic. These words are lemma candidates for a new dictionary on COVID-19 discourse in German. They also provided the database used to develop and test the NeoRate tool. We report on the lexicographic work in our dictionary project, the design and functionalities of NeoRate, and describe the first test results with the tool, in particular with regard to previously unregistered words. Finally, we discuss further development of the tool and its possible applications.
It is well known that the distribution of lexical and grammatical patterns is size- and register-sensitive (Biber 1986, and later publications). This fact alone presents a challenge to many corpus-oriented linguistic studies focusing on a single language. When it comes to cross-linguistic studies using corpora, the challenge becomes even greater due to the lack of high-quality multilingual corpora (Kupietz et al. 2020; Kupietz/Trawiński 2022), which are comparable with respect to the size and the register. That was the motivation for the creation of the European Reference Corpus EuReCo, an initiative started in 2013 at the Leibniz Institute for the German Language (IDS) together with several European partners (Kupietz et al. 2020). EuReCo is an emerging federated corpus, with large virtual comparable corpora across various languages and with an infrastructure supporting contrastive research. The core of the infrastructure is KorAP (Diewald et al. 2016), a scalable open-source platform supporting the analysis and visualisation of properties of texts annotated by multiple and potentially conflicting information layers, and supporting several corpus query languages. Until recently, EuReCo consisted of three monolingual subparts: the German Reference Corpus DeReKo (Kupietz et al. 2018), the Reference Corpus of Contemporary Romanian Language (Barbu Mititelu/Tufiş/Irimia 2018), and the Hungarian National Corpus (Váradi 2002). The goal of the present submission is twofold. On the one hand, it reports about the new component of EuReCo: a sample of the National Corpus of Polish (Przepiórkowski et al. 2010). On the other hand, it presents the results of a new pilot study using the newly extended EuReCo. This pilot study investigates selected Polish collocations involving light verbs and their prepositional / nominal complements (Fig. 1) and extends the collocation analyses of German, Romanian and Hungarian (Fig. 2) discussed in Kupietz/Trawiński (2022).