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	title        = {Vocation Identification in Swedish Fiction. },
	abstract     = {This paper presents a system for automatic annotation of vocational signals in 19th century Swedish prose fiction. Besides vocation identification, the system assigns gender (male, female, unknown) to the vocation words. Since gender is a prominent attribute of first names, we apply a named-entity recognizer (NER) that uses first name gazetteers where each name has been pre-assigned gender, which aids gender assignment to vocations with unknown gender if appropriate context is available. We also use a statistical modelling method, conditional random fields (CRF), for learning gender-assigned vocations in combination with the results of the NER and other pattern matching techniques. The purpose of this work is to develop and apply tools to literature as means to expand our understanding of history in the area of literature-based gender studies, e.g. investigate how women enter literature, which functions do they assume and their working patterns. Vocation identification can be used as one such indicator for achieving some these goals.},
	booktitle    = {Proceedings of the Fifth Swedish Language Technology Conference (SLTC)},
	author       = {Kokkinakis, Dimitrios and Ighe, Ann and Malm, Mats},
	year         = {2014},
	pages        = {3},