Refine
Year of publication
Document Type
- Part of a Book (53) (remove)
Keywords
- Korpus <Linguistik> (18)
- Computerlinguistik (15)
- Annotation (12)
- Digital Humanities (8)
- Forschungsdaten (8)
- Sprachdaten (7)
- XML (6)
- Automatische Sprachanalyse (5)
- Infrastruktur (4)
- CLARIN (3)
Publicationstate
- Veröffentlichungsversion (32)
- Zweitveröffentlichung (11)
- Postprint (5)
Reviewstate
- (Verlags)-Lektorat (33)
- Peer-Review (11)
Publisher
- de Gruyter (8)
- European language resources association (ELRA) (4)
- Springer (4)
- Narr (3)
- Institut für Deutsche Sprache (2)
- Lang (2)
- Libri Books on Demand (2)
- Schöningh (2)
- TEIA Lehrbuch Verlag (2)
- Aisthesis Verlag (1)
Integrated Linguistic Annotation Models and Their Application in the Domain of Antecedent Detection
(2011)
Seamless integration of various, often heterogeneous linguistic resources in terms of their output formats and a combined analysis of the respective annotation layers are crucial tasks for linguistic research. After a decade of concentration on the development of formats to structure single annotations for specific linguistic issues, in the last years a variety of specifications to store multiple annotations over the same primary data has been developed. The paper focuses on the integration of the knowledge resource logical document structure information into a text document to enhance the task of automatic anaphora resolution both for the task of candidate detection and antecedent selection. The paper investigates data structures necessary for knowledge integration and retrieval.
This paper describes the effort of the Institut für Deutsche Sprache (IDS), the central research institution for the German language, connected with Information and Communications Technology (ICT). Use of ICT in a language research institute is twofold. On the one hand, ICT provides basic services for researches to accomplish their daily work. On the other hand, several national and international institutions have a strong interest in ICT. Therefore, ICT can also be seen as an amplifier for language research. The first part of this paper reports on the activates of the IDS in internal and external ICT-related projects and initiatives. The second part describes a general strategy towards an ICT strategy that could be useful both for the IDS and other national language institutes. We think such a general strategy is necessary to create a strong foundation not only for the ICT-related projects, but as a basis for a modem research institute.
In the mid-1990s, the Faculty of Linguistics and Literary-Studies at Bielefeld University began to establish the field Text technology, both in research and education. Text technology is a new field of research on the border of Computational Linguistics and Computational Philology.
This paper focuses on Text technology in academic education. In 2002, Text Technology was introduced as a minor subject for B.A. Programs. It is organized in modules: Module 1 introduces the characteristics of electronic texts and documents, typography, typesetting systems and hypertext. Module 2 introduces one or two programming languages relevant to the field of humanities computing. Markup languages and the principles of information structuring are the main topics of Module 3. The formal fundamentals of computer-based text processing, as formal languages and their grammars, Logics et cetera are subjects of another module. The paper ends with a short description of other Bachelor- and Master-Programs at Bielefeld University which contain text technological themes.
The actual or anticipated impact of research projects can be documented in scientific publications and project reports. While project reports are available at varying level of accessibility, they might be rarely used or shared outside of academia. Moreover, a connection between outcomes of actual research project and potential secondary use might not be explicated in a project report. This paper outlines two methods for classifying and extracting the impact of publicly funded research projects. The first method is concerned with identifying impact categories and assigning these categories to research projects and their reports by extension by using subject matter experts; not considering the content of research reports. This process resulted in a classification schema that we describe in this paper. With the second method which is still work in progress, impact categories are extracted from the actual text data.
SGML und Linguistik
(1999)