Colin Batchelor

Also published as: Colin R. Batchelor


2020

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A Corpus of Very Short Scientific Summaries
Yifan Chen | Tamara Polajnar | Colin Batchelor | Simone Teufel
Proceedings of the 24th Conference on Computational Natural Language Learning

We present a new summarisation task, taking scientific articles and producing journal table-of-contents entries in the chemistry domain. These are one- or two-sentence author-written summaries that present the key findings of a paper. This is a first look at this summarisation task with an open access publication corpus consisting of titles and abstracts, as input texts, and short author-written advertising blurbs, as the ground truth. We introduce the dataset and evaluate it with state-of-the-art summarisation methods.

2019

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Proceedings of the Celtic Language Technology Workshop
Teresa Lynn | Delyth Prys | Colin Batchelor | Francis Tyers
Proceedings of the Celtic Language Technology Workshop

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Universal dependencies for Scottish Gaelic: syntax
Colin Batchelor
Proceedings of the Celtic Language Technology Workshop

2014

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gdbank: The beginnings of a corpus of dependency structures and type-logical grammar in Scottish Gaelic
Colin Batchelor
Proceedings of the First Celtic Language Technology Workshop

2013

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A Discourse-Driven Content Model for Summarising Scientific Articles Evaluated in a Complex Question Answering Task
Maria Liakata | Simon Dobnik | Shyamasree Saha | Colin Batchelor | Dietrich Rebholz-Schuhmann
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

2010

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Corpora for the Conceptualisation and Zoning of Scientific Papers
Maria Liakata | Simone Teufel | Advaith Siddharthan | Colin Batchelor
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present two complementary annotation schemes for sentence based annotation of full scientific papers, CoreSC and AZ-II, applied to primary research articles in chemistry. AZ-II is the extension of AZ for chemistry papers. AZ has been shown to have been reliably annotated by independent human coders and useful for various information access tasks. Like AZ, AZ-II follows the rhetorical structure of a scientific paper and the knowledge claims made by the authors. The CoreSC scheme takes a different view of scientific papers, treating them as the humanly readable representations of scientific investigations. It seeks to retrieve the structure of the investigation from the paper as generic high-level Core Scientific Concepts (CoreSC). CoreSCs have been annotated by 16 chemistry experts over a total of 265 full papers in physical chemistry and biochemistry. We describe the differences and similarities between the two schemes in detail and present the two corpora produced using each scheme. There are 36 shared papers in the corpora, which allows us to quantitatively compare aspects of the annotation schemes. We show the correlation between the two schemes, their strengths and weeknesses and discuss the benefits of combining a rhetorical based analysis of the papers with a content-based one.

2009

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Towards Domain-Independent Argumentative Zoning: Evidence from Chemistry and Computational Linguistics
Simone Teufel | Advaith Siddharthan | Colin Batchelor
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

2007

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Semantic enrichment of journal articles using chemical named entity recognition
Colin R. Batchelor | Peter T. Corbett
Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions

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Annotation of Chemical Named Entities
Peter Corbett | Colin Batchelor | Simone Teufel
Biological, translational, and clinical language processing