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Báo cáo khoa học: "An annotation scheme for discourse-level argumentation in research articles"

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. | Proceedings of EACL 99 An annotation scheme for discourse-level argumentation in research articles Simone Teufel and Jean Carletta and Marc Moens HCRC Language Technology Group and Human Communication Research Centre Division of Informatics University of Edinburgh S.Teufel@ed.ac.uk J.Carletta@ed.ac.uk M.Moens@ed.ac.uk Abstract 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. 1 Introduction Current approaches to automatic summarization cannot create coherent flexible automatic summaries. Sentence selection techniques e.g. Brandow et al. 1995 Kupiec et al. 1995 produce extracts which can be incoherent and which because of the generality of the methodology can give under-informative results fact extraction techniques e.g. Rau et al. 1989 Young and Hayes 1985 are tailored to particular domains but have not really scaled up from restricted texts and restricted domains to larger domains and unrestricted text. Spărck Jones 1998 argues that taking into account the structure of a text will help when summarizing the text. The problem with sentence selection is that it relies on extracting sentences out of context but the meaning of extracted material tends to depend on where in the text the extracted sentence was found. However sentence selection still has the distinct advantage of robustness. We think sentence selection could be improved substantially if the global rhetorical context of the extracted material was taken into account more. Marcu 1997 makes a similar point based on rhetorical relations as defined by Rhetorical Structure Theory RST Mann and Thompson 1987 . In contrast to this