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The KorAP project (“Korpusanalyseplattform der nächste Generation”, “Corpus-analysis platform of the next generation”), carried out at the Institut fUr Deutsche Sprache (IDS) in Mannheim, Germany, has as its goal the development of a modem, state-of-the-art corpus-analysis platform, capable of handling very large corpora and opening the perspectives for innovative linguistic research. The platform will facilitate new linguistic findings by making it possible to manage and analyse extremely large amounts of primary data and annotations, while at the same time allowing an undistorted view of the primary un-annotated text, and thus fully satisfying expectations associated with a scientific tool. The project started in July 2011 and is funded till June 2014. The demo presentation in December will be the first version following a preliminary feature freeze, and will open the alpha testing phase of the project.
CMC Corpora in DeReKo
(2017)
We introduce three types of corpora of computer-mediated communication that have recently been compiled at the Institute for the German Language or curated from an external project and included in DeReKo, the German Reference Corpus, namely Wikipedia (discussion) corpora, the Usenet news corpus, and the Dortmund Chat Corpus. The data and corpora have been converted to I5, the TEI customization to represent texts in DeReKo, and are researchable via the web-based IDS corpus research interfaces and in the case of Wikipedia and chat also downloadable from the IDS repository and download server, respectively.
We evaluate a graph-based dependency parser on DeReKo, a large corpus of contemporary German. The dependency parser is trained on the German dataset from the SPMRL 2014 Shared Task which contains text from the news domain, whereas DeReKo also covers other domains including fiction, science, and technology. To avoid the need for costly manual annotation of the corpus, we use the parser’s probability estimates for unlabeled and labeled attachment as main evaluation criterion. We show that these probability estimates are highly correlated with the actual attachment scores on a manually annotated test set. On this basis, we compare estimated parsing scores for the individual domains in DeReKo, and show that the scores decrease with increasing distance of a domain to the training corpus.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).
This paper reports on the latest developments of the European Reference Corpus EuReCo and the German Reference Corpus in relation to three of the most important CMLC topics: interoperability, collaboration on corpus infrastructure building, and legal issues. Concerning interoperability, we present new ways to access DeReKo via KorAP on the API and on the plugin level. In addition we report about advancements in the EuReCo- and ICC-initiatives with the provision of comparable corpora, and about recent problems with license acquisitions and our solution approaches using an indemnification clause and model licenses that include scientific exploitation.
We present an approach to an aspect of managing complex access scenarios to large and heterogeneous corpora that involves handling user queries that, intentionally or due to the complexity of the queried resource, target texts or annotations outside of the given user’s permissions. We first outline the overall architecture of the corpus analysis platform KorAP, devoting some attention to the way in which it handles multiple query languages, by implementing ISO CQLF (Corpus Query Lingua Franca), which in turn constitutes a component crucial for the functionality discussed here. Next, we look at query rewriting as it is used by KorAP and zoom in on one kind of this procedure, namely the rewriting of queries that is forced by data access restrictions.
Maximizing the potential of very large corpora: 50 years of big language data at IDS Mannheim
(2014)
Very large corpora have been built and used at the IDS since its foundation in 1964. They have been made available on the Internet since the beginning of the 90’s to currently over 30,000 researchers worldwide. The Institute provides the largest archive of written German (Deutsches Referenzkorpus, DeReKe) which has recently been extended to 24 billion words. DeReKe has been managed and analysed by engines known as COSMAS and afterwards COSMAS II, which is currently being replaced by a new, scalable analysis platform called KorAP. KorAP makes it possible to manage and analyse texts that are accompanied by multiple, potentially conflicting, grammatical and structural annotation layers, and is able to handle resources that are distributed across different, and possibly geographically distant, storage systems. The majority of texts in DeReKe are not licensed for free redistribution, hence, the COSMAS and KorAP systems offer technical solutions to facilitate research on very large corpora that are not available (and not suitable) for download. For the new KorAP system, it is also planned to provide sandboxed environments to support non-remote-API access “near the data” through which users can run their own analysis programs.