Creating an annotated corpus for extracting canonical citations from classics-related texts by using active annotation

Authors:
Matteo Romanello
Affiliations:
Department of Digital Humanities, King's College London, London, UK
Venue:
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Year:
2013

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Abstract

This paper describes the creation of an annotated corpus supporting the task of extracting information---particularly canonical citations, that are references to the ancient sources---from Classics-related texts. The corpus is multilingual and contains approximately 30,000 tokens of POS-tagged, cleanly transcribed text drawn from the L'Année Philologique. In the corpus the named entities that are needed to capture such citations were annotated by using an annotation scheme devised specifically for this task. The contribution of the paper is two-fold: firstly, it describes how the corpus was created using Active Annotation, an approach which combines automatic and manual annotation to optimize the human resources required to create any corpus. Secondly, the performances of an NER classifier, based on Conditional Random Fields, are evaluated using the created corpus as training and test set: the results obtained by using three different feature sets are compared and discussed.