Using a unified taxonomy to annotate discourse markers in speech and writing
Year: 2015
Type: book-chapter
Abstract: We report an annotation experiment aiming at assessing the use of a single functional taxonomy of sense relations for discourse markers in spoken and written data. We start by presenting an operational definition of the category of DMs and its application to identify tokens of DMs in corpora. We then present an original annotation experiment making use of a unified taxonomy to annotate written and spoken data in English and French. In this experiment, we test the reliability of the annotations made separately by two annotators and the applicability of the tag set across two languages in the spoken and written modes. Our experiment leads us to conclude that: i) spoken data is not more difficult to annotate than written data in terms of inter-annotator agreement, ii) recurrent problems are found across the two languages and modes, iii) the reliability of the annotation scheme is improved by the use of more explicit instructions and training.
Source: Digital Access to Libraries
Authors: Ludivine Crible, Sandrine Zufferey
Institutions: UCLouvain, KU Leuven, University of Fribourg
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1733983371