Diachronic Evaluation of NER Systems on Old Newspapers

In recent years, many cultural institutions have engaged in large-scale newspaper digitization projects and large amounts of historical texts are being acquired (via transcription or OCRization). Beyond document preservation, the next step consists in providing an enhanced access to the content of these digital resources. In this regard, the processing of units which act as referential anchors, namely named entities (NE), is of particular importance. Yet, the application of standard NE tools to historical texts faces several challenges and performances are often not as good as on contemporary documents. This paper investigates the performances of different NE recognition tools applied on old newspapers by conducting a diachronic evaluation over 7 time-series taken from the archives of Swiss newspaper Le Temps.

Dipper, Stephanie
Neubarth, Friedrich
Zinsmeister, Heike
Published in:
Proceedings of the 13th Conference on Natural Language Processing (KONVENS 2016), 97-107
Presented at:
13th Conference on Natural Language Processing (KONVENS 2016), Bochum, Germany, September 19-21, 2016
Conference on Natural Language Processing, Bochum, Germany, September 19–21, 2016
Bochum, Germany, Bochumer Linguistische Arbeitsberichte

 Record created 2016-09-18, last modified 2018-02-06

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