|Title||Modern Tools for Old Content - in Search of Named Entities in a Finnish OCRed Historical Newspaper Collection 1771-1910|
|Publication Type||Conference Paper|
|Year of Publication||2016|
|Authors||Kettunen, K, Mäkelä, E, Ruokolainen, T, Niemi, J|
|Conference Name||LWDA 2016|
Named Entity Recognition (NER), search, classification and tagging of names and name like frequent informational elements in texts, has become a standard information extraction procedure for textual data. NER has been applied to many types of texts and different types of entities: newspapers, fiction, historical records, persons, locations, chemical compounds, protein families, animals etc. In general a NER system's performance is genre and domain dependent and also used entity categories vary (Nadeau and Sekine, 2007). The most general set of named entities is usually some version of three partite categorization of locations, persons and organizations. In this paper we report first large scale trials and evaluation of NER with data out of a digitized Finnish historical newspaper collection Digi. Experiments, results and discussion of this research serve development of the Web collection of historical Finnish newspapers.