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This study examines what kind of cues and constraints for discourse interpretation can be derived from the logical and generic document structure of complex texts by the example of scientific journal articles. We performed statistical analysis on a corpus of scientific articles annotated on different annotations layers within the framework of XML-based multi-layer annotation. We introduce different discourse segment types that constrain the textual domains in which to identify rhetorical relation spans, and we show how a canonical sequence of text type structure categories is derived from the corpus annotations. Finally, we demonstrate how and which text type structure categories assigned to complex discourse segments of the type “block” statistically constrain the occurrence of rhetorical relation types.
Computerlinguistik (die Verarbeitung von Sprache mit dem Computer) und Texttechnologie (die automatisierte Handhabung elektronischer Texte) haben im letzten Jahrzehnt unterschiedliche Richtungen eingeschlagen. Beide Disziplinen speisen sich jedoch aus der gleichen Quelle: der formalen Grammatik. Deshalb ist eine gemeinsame Darstellung sinnvoll. Der Bezug auf die gemeinsamen Grundlagen und die kontrastierende Gegenüberstellung einzelner Teilbereiche fördern das Verständnis der jeweils anderen Disziplin und eröffnen interessante Querbezüge. Erstmals wird die Verknüpfung von Computerlinguistik und Texttechnologie mit dieser Einführung in knapper Form systematisch vollzogen, was sie insbesodere für Module im Bachelor-Studium geeignet macht.
Knowledge in textual form is always presented as visually and hierarchically structured units of text, which is particularly true in the case of academic texts. One research hypothesis of the ongoing project Knowledge ordering in texts - text structure and structure visualisations as sources of natural ontologies1 is that the textual structure of academic texts effectively mirrors essential parts of the knowledge structure that is built up in the text. The structuring of a modern dissertation thesis (e.g. in the form of an automatically generated table of contents - toes), for example, represents a compromise between requirements of the text type and the methodological and conceptual structure of its subject-matter. The aim of the project is to examine how visual-hierarchical structuring systems are constructed, how knowledge structures are encoded in them, and how they can be exploited to automatically derive ontological knowledge for navigation, archiving, or search tasks. The idea to extract domain concepts and semantic relations mainly from the structural and linguistic information gathered from tables of contents represents a novel approach to ontology learning.
Präsentationstechnologien bedingen Konvergenzprozesse verschiedener Kommunikationsmodi. In wissenschaftlichen Präsentationen werden unterschiedliche kommunikative Elemente (unter anderem Text, Bild und redebegleitende Gesten) miteinander verbunden, wodurch eine komplexe, mehrdimensionale Form der Multimodalität entsteht Die multimodale Struktur von Präsentationen kann durch eine neuartige Betrachtungsweise mit linguistischem Instrumentarium beschrieben und analysiert werden. Die Grundlage eines solchen linguistischen Ansatzes bildet die Annahme, dass Präsentationen als komplexe, multimodale Texte verstanden werden können. Der Beitrag zeigt, wie auf Basis dieser Annahme die Funktionsweise wissenschaftlicher Präsentationen theoretisch modelliert werden kann.
This chapter addresses the requirements and linguistic foundations of automatic relational discourse analysis of complex text types such as scientific journal articles. It is argued that besides lexical and grammatical discourse markers, which have traditionally been employed in discourse parsing, cues derived from the logical and generical document structure and the thematic structure of a text must be taken into account. An approach to modelling such types of linguistic information in terms of XML-based multi-layer annotations and to a text-technological representation of additional knowledge sources is presented. By means of quantitative and qualitative corpus analyses, cues and constraints for automatic discourse analysis can be derived. Furthermore, the proposed representations are used as the input sources for discourse parsing. A short overview of the projected parsing architecture is given.