Whose idea was this? Deciding attribution in scientific literature

Advaith Siddharthan, Simone Teufel

Research output: Contribution to conferenceUnpublished paperpeer-review


For a variety of discourse level analyses and tasks performed on scientific literature, it is necessary to identify which (if any) cited paper the discourse entities in focus are attributable to. In this paper we introduce a scientific attribution task that aims to associate a range of linguistic expressions such as definite descriptions, pronouns and “work ” nouns with specific cited papers. We report human agreement of Krippendorff’s Alpha greater than 0.8 on our scientific attribution task, based on written guidelines with ten rules for common systematic problem cases. The high alpha suggests that our task is well defined and fairly intuitive to annotators. Our machine learning approach achieves Krippendorff’s Alpha of 0.67 and percentage agreement of 85 % with a manually constructed gold standard, suggesting that the task is simpler than traditional anaphora resolution tasks.
Original languageEnglish
Number of pages6
Publication statusPublished - 2007
Event6th Discourse Anaphora and Anaphor Resolution Colloquium (DAARC'07) - Logos, Portugal
Duration: 29 Mar 200730 Mar 2007


Conference6th Discourse Anaphora and Anaphor Resolution Colloquium (DAARC'07)

Bibliographical note

This work was funded by the EPSRC project SciBorg (EP/C010035/1, Extracting the Science from Scientific Publications).


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