In order to build robust automatic abstracting systems, there is a need for better training resources than are currently available. In this paper, we introduce an annotation scheme for scientific articles which can be used to build such a resource in a consistent way. The seven categories of the scheme are based on rhetorical moves of argumentation. Our experimental results show that the scheme is stable, reproducible and intuitive to use.
|Publisher||Association for Computational Linguistics|
|Conference||Ninth Conference on European Chapter of the Association for Computational Linguistics|
|Period||8/06/99 → 12/06/99|