What’s Yours and What’s Mine: Determining Intellectual Attribution in Scientific Text

What's yours and what's mine: Determining Intellectual Attribution in Scientific Text Simone Teufel t Computer Science Department Columbia University t eufel©cs, columbia, edu Marc Moens HCRC Language Technology Group University of Edinburgh Marc. Moens©ed. ac. uk Abstract We believe that identifying the structure of scien- tific argumentation in articles can help in tasks such as automatic summarization or the auto- mated construction of citation indexes. One par- ticularly important aspect of this structure is the question of who a given scientific statement is at- tributed to: other researchers, the field in general, or the authors themselves. We present the algorithm and a systematic eval- uation of a system which can recognize the most salient textual properties that contribute to the global argumentative structure of a text. In this paper we concentrate on two particular features, namely the occurrences of prototypical agents and their actions in scientific text. 1 Introduction When writing an article, one does not normally go straight to presenting the innovative scien- tific claim. Insteacl, one establishes other, well- known scientific facts first, which are contributed by other researchers. Attribution of ownership of- ten happens explicitly, by phrases such as "Chom- sky (1965) claims that". The question of intel- lectual attribution is important for researchers: not understanding the argumentative status of part of the text is a common problem for non- experts reading highly specific texts aimed at ex- perts (Rowley, 1982). In particular, after reading an article, researchers need to know who holds the "knowledge claim" for a certain fact that interests them. We propose that segmentation according to in- tellectual ownership can be done automatically, and that such a segmentation has advantages for various shallow text understanding tasks. At the heart of our classification scheme is the following trisection: * BACKGROUND (generally known work) * OWN, new work and . specific OTHER work. The advantages of a segmentation at a rhetori- cal level is that rhetorics is conveniently constant tThis work was done while the first author was at the HCRC Language Technology Group, Edinburgh. BACKGROUND: Researchers in knowledge representa- tion agree that one of the hard problems of understanding narrative is the representation of temporal information. Certain facts of nat- ural language make it hard to capture tempo- ral information [...] OTHER WORK: Recently, Researcher-4 has suggested the following solution to this problem [...]. WEAKNESS/CONTRAST: But this solution cannot be used to inter- pret the following Japanese examples: [...] OWN CONTRIBUTION: We propose a solution which circumvents this prow while retaining the explanatory power of Researcher-4's approach. Figure h Fictional introduction section across different articles. Subject matter, on the contrary, is not constant, nor are writing style and other factors. We work with a corpus of scientific pa- pers (80 computational linguistics conference ar- ticles (ACL, EACL, COLING or ANLP), de- posited on the CMP_LG archive between 1994 and 1996). This is a difficult test bed due to the large variation with respect to different fac- tors: subdomain (theoretical linguistics, statisti- cal NLP, logic programming, …

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