Merging and validating heterogenous, multi-layered corpora with discoursegraphs

Abstract

We present discoursegraphs, a library and command-line application for the conversion and merging of linguistic annotations written in Python. The software reads and writes numerous formats for syntactic and discourse-related annotations, but also supports generic interchange formats. discoursegraphs models primary data and its annotations as a graph and is therefore able to merge multiple independent, possibly conflicting annotation layers into a unified representation. We show how this approach is beneficial for the revision and validation of a corpus with multiple conflicting, independently annotated layers.