Korpuslinguistik
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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.
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.
The present paper examines a variety of ways in which the Corpus of Contemporary Romanian Language (CoRoLa) can be used. A multitude of examples intends to highlight a wide range of interrogation possibilities that CoRoLa opens for different types of users. The querying of CoRoLa displayed here is supported by the KorAP frontend, through the querying language Poliqarp. Interrogations address annotation layers, such as the lexical, morphological and, in the near future, the syntactical layer, as well as the metadata. Other issues discussed are how to build a virtual corpus, how to deal with errors, how to find expressions and how to identify expressions.
This paper presents an algorithm and an implementation for efficient tokenization of texts of space-delimited languages based on a deterministic finite state automaton. Two representations of the underlying data structure are presented and a model implementation for German is compared with state-of-the-art approaches. The presented solution is faster than other tools while maintaining comparable quality.
The user interfaces for corpus analysis platforms must provide a high degree of accessibility for ordinary users and at the same time provide the possibility to answer complex research questions. In this paper, we present the design concepts behind the user interface of KorAP, a corpus analysis platform that has evolved into the main gateway to CoRoLa, the Reference Corpus of Contemporary Romanian Language. Based on established principles of user interface design, we show how KorAP addresses the challenge of providing a user-friendly interface for heterogeneous corpus data to a wide range of users with different research questions.
Die Korpusanalyseplattform KorAP ist von Grund auf sprachenunabhängig konzipiert. Dies gilt sowohl in Bezug auf die Lokalisierung der Benutzeroberfläche als auch hinsichtlich unterschiedlicher Anfragesprachen und der Unterstützung fremdsprachiger Korpora und ihren Annotationen. Diese Eigenschaften dienen im Rahmen der EuReCo Initiative aktuell besonders der Bereitstellung weiterer National- und Referenzkorpora neben DeReKo. EuReCo versucht, Kompetenzen beim Aufbau großer Korpora zu bündeln und durch die Verfügbarmachung vergleichbarer Korpora quantitative Sprachvergleichsforschung zu erleichtern. Hierzu bietet KorAP inzwischen, neben dem Zugang durch die Benutzeroberfläche, einen Web API Client an, der statistische Erhebungen, auch korpusübergreifend, vereinfacht.
Für die spezifischen Bedürfnisse der Schreibbeobachtung wurde das Orthografische Kernkorpus (OKK) als virtuelles Korpus in DeReKo entwickelt. Mit derzeit rund 14 Mrd. Token deckt es den Schriftsprachgebrauch in den deutschsprachigen Ländern im Zeitraum von 1995 bis in die Gegenwart ab. Der Zugriff über die Korpusanalyseplattform KorAP erlaubt nicht nur die Nutzung verschiedener Annotationen, sondern über die API-Schnittstellen auch die Einbindung in diverse Auswertungsumgebungen wie RStudio über den RKorAPClient und macht es so für zahlreiche Analyse- und Visualisierungsmöglichkeiten zugänglich.
KorAP is a corpus search and analysis platform, developed at the Institute for the German Language (IDS). It supports very large corpora with multiple annotation layers, multiple query languages, and complex licensing scenarios. KorAP’s design aims to be scalable, flexible, and sustainable to serve the German Reference Corpus DEREKO for at least the next decade. To meet these requirements, we have adopted a highly modular microservice-based architecture. This paper outlines our approach: An architecture consisting of small components that are easy to extend, replace, and maintain. The components include a search backend, a user and corpus license management system, and a web-based user frontend. We also describe a general corpus query protocol used by all microservices for internal communications. KorAP is open source, licensed under BSD-2, and available on GitHub.
When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state of the art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.
When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state-ofthe-art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.