Korpuslinguistik
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We describe a general two-stage procedure for re-using a custom corpus for spoken language system development involving a transformation from character-based markup to XML, and DSSSL stylesheet-driven XML markup enhancement with multiple lexical tag trees. The procedure was used to generate a fully tagged corpus; alternatively with greater economy of computing resources, it can be employed as a parametrised ‘tagging on demand’ filter. The implementation will shortly be released as a public resource together with the corpus (German spoken dialogue, about 500k word form tokens) and lexicon (about 75k word form types).
Co-reference annotation and resources: a multilingual corpus of typologically diverse languages
(2002)
This article introduces a dialogue corpus containing data from two typologically different languages, Japanese and Kilivila. The corpus is annotated in accordance with language specific annotation schemes for co-referential and similar relations. The article describes the corpus data, the properties of language specific co-reference in the two languages and a methodology for its annotation. Examples from the corpus show how this methodology is used in the workflow of the annotation process.
This paper proposes a methodology for querying linguistic data represented in different corpus formats. Examples of the need for queries over such heterogeneous resources are the corpus-based analysis of multimodal phenomena like the interaction of gestures and prosodic features, or syntax-related phenomena like information structure which exceed the expressive power of a tree-centered corpus format. Query languages (QLs) currently under development are strongly connected to corpus formats, like the NITE Object Model (NOM, Carletta et al., 2003) or the Meta-Annotation Infrastructure for ATLAS (MAIA, Laprun and Fiscus, 2002). The parallel development of linguistic query languages and corpus formats is due to the fact that general purpose query languages like XQuery (Boag et al., 2003) do not fulfill the changing needs of linguistically motivated queries, e.g. to give access to (non-)hierarchically organized, theory and language dependent annotations of multi modal signals and/or text. This leads to the problem that existing corpus formats and query languages are hard to reuse. They have to be re developed and re-implemented time-consumingly and expensively for unforeseen tasks. This paper describes an approach for overcoming these problems and a sample application.
This paper describes a corpus of Japanese task-oriented dialogues, i.e. its data, annotations, analysis methodology and preliminary results for the modeling of co-referential phenomena. Current corpus based approaches to co-reference concentrate on textual data from English or other European languages. Hence, the emerging language-general models of co-reference miss input from dialogue data of non-European languages. We aim to fill this gap and contribute to a model of co-reference on various language-specific and language-general levels.
The aim of the paper is twofold. Firstly, an approach is presented how to select the correct antecedent for an anaphoric element according to the kind of text segments in which both of them occur. Basically, information on logical text structure (e.g. chapters, sections, paragraphs) is used in order to select the antecedent life span of a linguistic expression, i.e. some linguistic expressions are more likely to be chosen as an antecedent throughout the whole text than others. In addition, an appropriate search scope for an anaphora expressed by an expression can be defined according to the document structuring elements that include the linguistic expression. Corpus investigations give rise to the supposition that logical text structure influences the search scope of candidates for antecedents. Second, a solution is presented how to integrate the resources used for anaphora resolution. In this approach, multi-layered XML annotation is used in order to make a set of resources accessible for the anaphora resolution system.
The metadata management system for speech corpora “memasysco” has been developed at the Institut für Deutsche Sprache (IDS) and is applied for the first time to document the speech corpus “German Today”. memasysco is based on a data model for the documentation of speech corpora and contains two generic XML schemas that drive data capture, XML native database storage, dynamic publishing, and information retrieval. The development of memasysco’s information architecture was mainly based on the ISLE MetaData Initiative (IMDI) guidelines for publishing metadata of linguistic resources. However, since we also have to support the corpus management process in research projects at the IDS, we need a finer atomic granularity for some documentation components as well as more restrictive categories to ensure data integrity. The XML metadata of different speech corpus projects are centrally validated and natively stored in an Oracle XML database. The extension of the system to the management of annotations of audio and video signals (e.g. orthographic and phonetic transcriptions) is planned for the near future.
This paper describes the efforts in the field of sustainability of the Institut für Deutsche Sprache (IDS) in Mannheim with respect to DEREKO (Deutsches Referenzkorpus) the Archive of General Reference Corpora of Contemporary Written German. With focus on re-usability and sustainability, we discuss its history and our future plans. We describe legal challenges related to the creation of a large and sustainable resource; sketch out the pipeline used to convert raw texts to the final corpus format and outline migration plans to TEI P5. Due to the fact, that the current version of the corpus management and query system is pushed towards its limits, we discuss the requirements for a new version which will be able to handle current and future DEREKO releases. Furthermore, we outline the institute’s plans in the field of digital preservation.
We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus of contemporary German (Kupietz et al., 2010). DeReKo 's strong dispersion wrt. genre, register and time forces us to base our decision for a specific NERC system on an evaluation performed on a representative sample of DeReKo instead of performance figures that have been reported for the individual NERC systems when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally applicable method for sampling evaluation data from an unbalanced target corpus for any sort of natural language processing.
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.