An annotation scheme for discourse-level argumentation in research articles

Proceedings of EACL '99 An annotation scheme for discourse-level argumentation in research articles Simone Teufel t and Jean Carletta f and Marc Moens ~ tHCRC Language Technology Group and tHuman 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 ab- stracting systems, there is a need for bet- ter training resources than are currently available. In this paper, we introduce an annotation scheme for scientific ar- ticles 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 intu- itive to use. 1 Introduction Current approaches to automatic summariza- tion cannot create coherent, flexible automatic summaries. Sentence selection techniques (e.g. Brandow et al., 1995; Kupiec et al. 1995) pro- duce extracts which can be incoherent and which, because of the generality of the methodology, can give under-informative results; fact extrac- tion 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 un- restricted text. Sp~irck 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 Struc- ture Theory (RST, (Mann and Thompson, 1987)). In contrast to this approach, we stress the impor- tance of rhetorical moves which are global to the argumentation of the paper, as opposed to local RST-type moves. For example, sentences which describe weaknesses of previous approaches can provide a good characterization of the scientific articles in which they occur, since they are likely to also be a description of the problem that pa- per is intending to solve. Take a sentence like "Un]ortunately, this work does not solve problem X": if X is a shortcoming in someone else's work, this usually means that the current paper will try to solve X. Sentence extraction methods can lo- cate sentences like these, e.g. using a cue phrase method (Paice, 1990). But a very similar-looking sentence can play a completely different argumentative role in a sci- entific text: when it occurs in the section "Future Work", it might refer to a minor weakness in the work presented in the source paper (i.e. of the au- thor's own solution). In that case, the sentence is not a good characterization of the paper. Our approach to automatic …

Content truncated to 500 words