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T1  - Projecting named entity recognizers without annotated or parallel corpora 
SN  -  /  
UR  - http://hdl.handle.net/10138/306000 
T3  - Linköping Electronic Conference Proceedings 
A1  - Hou, Jue; Koppatz, Maximilian; Hoya Quecedo, Jose María; Yangarber, Roman 
A2  - Hartmann, Mareike; Plank, Barbara 
PB  - Linköping University Electronic Press 
Y1  - 2019 
LA  - eng 
AB  - Named entity recognition (NER) is a well-researched task in the field of NLP, which typically requires large annotated corpora for training usable models. This is a problem for languages which lack large annotated corpora, such as Finnish. We propose an approach to create a named entity recognizer with no annotated or parallel documents, by leveraging strong NER models that exist for English. We automatically gather a large amount of chronologically matched data in two languages, then project na... 
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KW  - 113 Computer and information sciences; 6121 Languages 
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