A Discourse Information Radio News Database for Linguistic Analysis

Abstract

In this paper we present DIRNDL, an annotated corpus resource comprising syntactic annotations as well as information status labels and prosodic information. We introduce each annotation layer and then focus on the linking of the data in a standoff approach. The corpus is based on data from radio news broadcasts, i.e. two sets of primary data: spoken radio news files and a written text version which sometimes deviates from the actual spoken data. We utilize a generic relational database management system to bridge the gap between the deviating primary data as well as between the different properties of the annotation levels. We show how the resource can support data extraction concerning the interface between information status, syntax and prosody.