Refine
Year of publication
Document Type
- Part of a Book (108)
- Article (23)
- Conference Proceeding (19)
- Book (18)
- Other (8)
- Doctoral Thesis (1)
- Master's Thesis (1)
Language
- German (148)
- English (23)
- Multiple languages (6)
- Chinese (1)
Keywords
- Deutsch (29)
- Computerlinguistik (24)
- Korpus <Linguistik> (21)
- Dependenzgrammatik (20)
- Syntax (16)
- Social Media (13)
- Digitalisierung (12)
- Texttechnologie (12)
- Annotation (11)
- Multimodalität (10)
Publicationstate
- Zweitveröffentlichung (87)
- Veröffentlichungsversion (44)
- Postprint (11)
- (Verlags)-Lektorat (1)
- Preprint (1)
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.
Researchers in many disciplines, sometimes working in close cooperation, have been concerned with modeling textual data in order to account for texts as the prime information unit of written communication. The list of disciplines includes computer science and linguistics as well as more specialized disciplines like computational linguistics and text technology. What many of these efforts have in common is the aim to model textual data by means of abstract data types or data structures that support at least the semi-automatic processing of texts in any area of written communication.
XML-Dokumentgrammatiken, die als DTDs oder neuerdings als XML-Schemata spezifiziert werden, spezifizieren zwar die syntaktischen Eigenschaften einer Klasse von Dokumenten, für sie existiert aber normalerweise kein formales semantisches Modell des Gegenstandsbereichs, auf das Dokumentstrukturen abgebildet werden können. Der Beitrag zeigt am Beispiel der Tabelle, wie semantische Netze für diese Aufgabe herangezogen werden können. Die konkrete Umsetzung geschieht dabei auf der Grundlage des Topic-Map-Standards in Verbindung mit XPath-Ausdrücken, die aus dem semantischen Netz in die Dokumentinstanz bzw. in ein XML-Schema verweisen.