Korpuslinguistik
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Linguistic corpora have been annotated by means of SGML-based markup languages for almost 20 years. We can, very roughly, differentiate between three distinct evolutionary stages of markup technologies. (1)Originally, single SGML tree-based document instances were deemed sufficient for the representation of linguistic structures. (2) Linguists began to realize that alternatives and extensions to the traditional model are needed. Formalisms such as, for example, NITE were proposed: the NITE Object Model (NOM) consists of multi-rooted trees. (3) We are now on the threshold of the third evolutionary stage: even NITE's very flexible approach is not suited for all linguistic purposes. As some structures, such as these, cannot be modeled by multi-rooted trees, an even more flexible approach is needed in order to provide a generic annotation format that is able to represent genuinely arbitrary linguistic data structures.
We start by trying to answer a question that has already been asked by de Schryver et al. (2006): Do dictionary users (frequently) look up words that are frequent in a corpus. Contrary to their results, our results that are based on the analysis of log files from two different online dictionaries indicate that users indeed look up frequent words frequently. When combining frequency information from the Mannheim German Reference Corpus and information about the number of visits in the Digital Dictionary of the German Language as well as the German language edition of Wiktionary, a clear connection between corpus and look-up frequencies can be observed. In a follow-up study, we show that another important factor for the look-up frequency of a word is its temporal social relevance. To make this effect visible, we propose a de-trending method where we control both frequency effects and overall look-up trends.
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).
Overlap in markup occurs where some markup structures do not nest, such as where the structural division of the text into lists, sections, etc., differs from the syntactic division of the text into sentences and phrases. The Multiple Annotation solution to this problem (redundant encoding in multiple forms) has many advantages: it is based on XML, the modeling of alternative annotations is possible, each level can be viewed separately, and new levels can be added at any time. But it has the significant disadvantage of independence of the separate files. These multiply annotated files can be regarded as an interrelated unit, with the text serving as the implicit link. Two representations of the information contained in the multiple files (one in Prolog and one in XML) can be programmatically derived and used together for editing, for inference, or for unification of the multiply annotated documents.
In this paper, we present a GOLD standard of part-of-speech tagged transcripts of spoken German. The GOLD standard data consists of four annotation layers – transcription (modified orthography), normalization (standard orthography), lemmatization and POS tags – all of which have undergone careful manual quality control. It comes with guidelines for the manual POS annotation of transcripts of German spoken data and an extended version of the STTS (Stuttgart Tübingen Tagset) which accounts for phenomena typically found in spontaneous spoken German. The GOLD standard was developed on the basis of the Research and Teaching Corpus of Spoken German, FOLK, and is, to our knowledge, the first such dataset based on a wide variety of spontaneous and authentic interaction types. It can be used as a basis for further development of language technology and corpus linguistic applications for German spoken language.
Part-of-speech tagging (POS-tagging) of spoken data requires different means of annotation than POS-tagging of written and edited texts. In order to capture the features of German spoken language, a distinct tagset is needed to respond to the kinds of elements which only occur in speech. In order to create such a coherent tagset the most prominent phenomena of spoken language need to be analyzed, especially with respect to how they differ from written language. First evaluations have shown that the most prominent cause (over 50%) of errors in the existing automatized POS-tagging of transcripts of spoken German with the Stuttgart Tübingen Tagset (STTS) and the treetagger was the inaccurate interpretation of speech particles. One reason for this is that this class of words is virtually absent from the current STTS. This paper proposes a recategorization of the STTS in the field of speech particles based on distributional factors rather than semantics. The ultimate aim is to create a comprehensive reference corpus of spoken German data for the global research community. It is imperative that all phenomena are reliably recorded in future part-of-speech tag labels.
Corpus researchers, along with many other disciplines in science are being put under continual pressure to show accountability and reproducibility in their work. This is unsurprisingly difficult when the researcher is faced with a wide array of methods and tools through which to do their work; simply tracking the operations done can be problematic, especially when toolchains are often configured by the developers, but left largely as a black box to the user. Here we present a scheme for encoding this ‘meta data’ inside the corpus files themselves in a structured data format, along with a proof-of-concept tool to record the operations performed on a file.
This article reports on the on-going CoRoLa project, aiming at creating a reference corpus of contemporary Romanian (from 1945 onwards), opened for online free exploitation by researchers in linguistics and language processing, teachers of Romanian, students. We invest serious efforts in persuading large publishing houses and other owners of IPR on relevant language data to join us and contribute the project with selections of their text and speech repositories. The CoRoLa project is coordinated by two Computer Science institutes of the Romanian Academy, but enjoys cooperation of and consulting from professional linguists from other institutes of the Romanian Academy. We foresee a written component of the corpus of more than 500 million word forms, and a speech component of about 300 hours of recordings. The entire collection of texts (covering all functional styles of the language) will be pre-processed and annotated at several levels, and also documented with standardized metadata. The pre-processing includes cleaning the data and harmonising the diacritics, sentence splitting and tokenization. Annotation will include morpho-lexical tagging and lemmatization in the first stage, followed by syntactic, semantic and discourse annotation in a later stage.