Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Towards Multi-paper Summarization Using Reference Information
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
An annotation scheme for discourse-level argumentation in research articles
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Inter-coder agreement for computational linguistics
Computational Linguistics
Automatic classification of citation function
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Zones of conceptualisation in scientific papers: a window to negative and speculative statements
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
Evaluating a meta-knowledge annotation scheme for bio-events
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Section classification in clinical notes using supervised hidden markov model
Proceedings of the 1st ACM International Health Informatics Symposium
Towards automated related work summarization
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
A weakly-supervised approach to argumentative zoning of scientific documents
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improving MeSH classification of biomedical articles using citation contexts
Journal of Biomedical Informatics
Discourse structure and computation: past, present and future
ACL '12 Proceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries
A three-way perspective on scientific discourse annotation for knowledge extraction
ACL '12 Proceedings of the Workshop on Detecting Structure in Scholarly Discourse
Discourse structure and language technology
Natural Language Engineering
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Argumentative Zoning (AZ) is an analysis of the argumentative and rhetorical structure of a scientific paper. It has been shown to be reliably used by independent human coders, and has proven useful for various information access tasks. Annotation experiments have however so far been restricted to one discipline, computational linguistics (CL). Here, we present a more informative AZ scheme with 15 categories in place of the original 7, and show that it can be applied to the life sciences as well as to CL. We use a domain expert to encode basic knowledge about the subject (such as terminology and domain specific rules for individual categories) as part of the annotation guidelines. Our results show that non-expert human coders can then use these guidelines to reliably annotate this scheme in two domains, chemistry and computational linguistics.