A formal framework for linguistic annotation
Speech Communication - Special issue on speech annotation and corpus tools
Natural Language Engineering
MedPost: a part-of-speech tagger for bioMedical text
Bioinformatics
Introduction to the CoNLL-2002 shared task: language-independent named entity recognition
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Language independent NER using a maximum entropy tagger
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Introduction to the bio-entity recognition task at JNLPBA
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Investigating the effects of selective sampling on the annotation task
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Recognising nested named entities in biomedical text
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Porting a lexicalized-grammar parser to the biomedical domain
Journal of Biomedical Informatics
Reducing semantic drift with bagging and distributional similarity
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Unsupervised discovery of negative categories in lexicon bootstrapping
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Relation guided bootstrapping of semantic lexicons
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Datasets for generic relation extraction*
Natural Language Engineering
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In this paper we discuss technical issues arising from the interdependence between tokenisation and XML-based annotation tools, in particular those which use standoff annotation in the form of pointers to word tokens. It is common practice for an XML-based annotation tool to use word tokens as the target units for annotating such things as named entities because it provides appropriate units for stand-off annotation. Furthermore, these units can be easily selected, swept out or snapped to by the annotators and certain classes of annotation mistakes can be prevented by building a tool that does not permit selection of a substring which does not entirely span one or more XML elements. There is a downside to this method of annotation, however, in that it assumes that for any given data set, in whatever domain, the optimal tokenisation is known before any annotation is performed. If mistakes are made in the initial tokenisation and the word boundaries conflict with the annotators' desired actions, then either the annotation is inaccurate or expensive retokenisation and reannotation will be required. Here we describe the methods we have developed to address this problem. We also describe experiments which explore the effects of different granularities of tokenisation on NER tagger performance.