Refine
Document Type
- Conference Proceeding (3)
- Article (2)
- Part of a Book (1)
- Working Paper (1)
Keywords
- Korpus <Linguistik> (3)
- Gesprochene Sprache (2)
- Ontologie <Wissensverarbeitung> (2)
- Parser (2)
- Strukturbaum (2)
- Annotation (1)
- Antwortrelationen (1)
- Antwortstrukturen (1)
- Computerunterstützte Kommunikation (1)
- Deutsch (1)
Publicationstate
- Zweitveröffentlichung (7) (remove)
Reviewstate
- (Verlags)-Lektorat (5)
- Peer-Review (1)
- Verlagslektorat (1)
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.
In the project SemDok (Generic document structures in linearly organised texts) funded by the German Research Foundation DFG, a discourse parser for a complex type (scientific articles by example), is being developed. Discourse parsing (henceforth DP) according to the Rhetorical Structure Theory (RST) (Mann and Taboada, 2005; Marcu, 2000) deals with automatically assigning a text a tree structure in which discourse segments and rhetorical relations between them are marked, such as Concession. For identifying the combinable segments, declarative rules are employed, which describe linguistic and structural cues and constraints about possible combinations by referring to different XML annotation layers of the input text, and external knowledge bases such as a discourse marker lexicon, a lexico-semantic ontology (later to be combined with a domain ontology), and an ontology of rhetorical relations. In our text-technological environment, the obvious choice of formalism to represent such ontologies is OWL (Smith et al., 2004). In this paper, we describe two OWL ontologies and how they are consulted from the discourse parser to solve certain tasks within DP. The first ontology is a taxononomy of rhetorical relations which was developed in the project. The second one is an OWL version of GermaNet, the model of which we designed together with our project partners.
This paper presents types and annotation layers of reply relations in computer- mediated communication (CMC). Reply relations hold between post units in CMC interactions and describe references from one given post to a previous post. We classify three types of reply relations in CMC interactions: first, technical replies, i. e. the possibility to reply directly to a previous post by clicking a ‘reply’ button; second, indentations, e. g. in wiki talk pages in which users insert their contributions in the existing talk page by indenting them and third, interpretative reply relations, i. e. the reply action is not realised formally but signalled by other structural or linguistics means such as address markers ‘@’, greetings, citations and/or Q-A structures. We take a look at existing practices in the description and representation of such relations in corpora and examples of chat, Wikipedia talk pages, Twitter and blogs. We then provide an annotation proposal that combines the different levels of description and representation of reply relations and which adheres to the schemas and practices for encoding CMC corpus documents within the TEI framework as defined by the TEI CMC SIG. It constitutes a prerequisite for correctly identifying higher levels of interactional relations such as dialogue acts or discussion trees.
Der Beitrag untersucht vorhandene Lösungen und neue Möglichkeiten des Korpusausbaus aus Social Media- und internetbasierter Kommunikation (IBK) für das Deutsche Referenzkorpus (DEREKO). DEREKO ist eine Sammlung gegenwartssprachlicher Schriftkorpora am IDS, die der sprachwissenschaftlichen Öffentlichkeit über die Korpusschnittstellen COSMAS II und KorAP angeboten wird. Anhand von Definitionen und Beispielen gehen wir zunächst auf die Extensionen und Überlappungen der Konzepte Social Media, Internetbasierte Kommunikation und Computer-mediated Communication ein. Wir betrachten die rechtlichen Voraussetzungen für einen Korpusausbau aus Sozialen Medien, die sich aus dem kürzlich in relevanten Punkten reformierten deutschen Urheberrecht, aus Persönlichkeitsrechten wie der europäischen Datenschutz-Grundverordnung ergeben und stellen Konsequenzen sowie mögliche und tatsächliche Umsetzungen dar. Der Aufbau von Social Media-Korpora in großen Textmengen unterliegt außerdem korpustechnologischen Herausforderungen, die für traditionelle Schriftkorpora als gelöst galten oder gar nicht erst bestanden. Wir berichten, wie Fragen der Datenaufbereitung, des Korpus-Encoding, der Anonymisierung oder der linguistischen Annotation von Social Media Korpora für DEREKO angegangen wurden und welche Herausforderungen noch bestehen. Wir betrachten die Korpuslandschaft verfügbarer deutschsprachiger IBK- und Social Media-Korpora und geben einen Überblick über den Bestand an IBK- und Social Media-Korpora und ihre Charakteristika (Chat-, Wiki Talk- und Forenkorpora) in DEREKO sowie von laufenden Projekten in diesem Bereich. Anhand korpuslinguistischer Mikro- und Makro-Analysen von Wikipedia-Diskussionen im Vergleich mit dem Gesamtbestand von DEREKO zeigen wir charakterisierende sprachliche Eigenschaften von Wikipedia-Diskussionen auf und bewerten ihren Status als Repräsentant von IBK-Korpora.