Open Access

Discourse parsing of complex text types such as scientific research articles requires the analysis of an input document on linguistic and structural levels that go beyond traditionally employed lexical discourse markers. This chapter describes a text-technological approach to discourse parsing. Discourse parsing with the aim of providing a discourse structure is seen as the addition of a new annotation layer for input documents marked up on several linguistic annotation levels. The discourse parser generates discourse structures according to the Rhetorical Structure Theory. An overview of the knowledge sources and components for parsing scientific joumal articles is given. The parser’s core consists of cascaded applications of the GAP, a Generic Annotation Parser. Details of the chart parsing algorithm are provided, as well as a short evaluation in terms of comparisons with reference annotations from our corpus and with recently developed Systems with a similar task.

We present an approach on how to investigate what kind of semantic information is regularly associated with the structural markup of scientific articles. This approach addresses the need for an explicit formal description of the semantics of text-oriented XML-documents. The domain of our investigation is a corpus of scientific articles from psychology and linguistics from both English and German online available journals. For our analyses, we provide XML-markup representing two kinds of semantic levels: the thematic level (i.e. topics in the text world that the article is about) and the functional or rhetorical level. Our hypothesis is that these semantic levels correlate with the articles’ document structure also represented in XML. Articles have been annotated with the appropriate information. Each of the three informational levels is modelled in a separate XML document, since in our domain, the different description levels might conflict so that it is impossible to model them within a single XML document. For comparing and mining the resulting multi-layered XML annotations of one article, a Prolog-based approach is used. It focusses on the comparison of XML markup that is distributed among different documents. Prolog predicates have been defined for inferring relations between levels of information that are modelled in separate XML documents. We demonstrate how the Prolog tool is applied in our corpus analyses.

Igel is a small XQuery-based web application for examining a collection of document grammars; in particular, for comparing related document grammars to get a better overview of their differences and similarities. In its initial form, Igel reads only DTDs and provides only simple lists of constructs in them (elements, attributes, notations, parameter entities). Our continuing work is aimed at making Igel provide more sophisticated and useful information about document grammars and building the application into a useful tool for the analysis (and the maintenance!) of families of related document grammars

An approach to the unification of XML (Extensible Markup Language) documents with identical textual content and concurrent markup in the framework of XML-based multi-layer annotation is introduced. A Prolog program allows the possible relationships between element instances on two annotation layers that share PCDATA to be explored and also the computing of a target node hierarchy for a well-formed, merged XML document. Special attention is paid to identity conflicts between element instances, for which a default solution that takes into account metarelations that hold between element types on the different annotation layers is provided. In addition, rules can be specified by a user to prescribe how identity conflicts should be solved for certain element types.