Named entity recognition

Named-entity recognition (NER) or proper name recognition is a task in information extraction and refers to the automatic identification and classification of proper names. A proper name is a sequence of words that describes a real entity, such as B. a company name.

For example, the MUC-7 data set is used for the evaluation . On this, 93.39% was achieved according to the measure, whereas people on this data set achieve between 96.95% and 97.60%. ${\ displaystyle F_ {1}}$

Individual evidence

^ Kai-Uwe Carstensen: Applications . In: Computational Linguistics and Language Technology . Spektrum Akademischer Verlag, 2010, ISBN 978-3-8274-2023-7 , pp. 596 , doi : 10.1007 / 978-3-8274-2224-8_5 ( springer.com [accessed October 22, 2017]).
↑ Jing Jiang: Information Extraction from Text . In: Mining Text Data . Springer, Boston, MA, 2012, ISBN 978-1-4614-3222-7 , pp. 15 , doi : 10.1007 / 978-1-4614-3223-4_2 ( springer.com [accessed October 22, 2017]).
↑ http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/marsh_slides.pdf

[1] Kai-Uwe Carstensen: Applications . In: Computational Linguistics and Language Technology . Spektrum Akademischer Verlag, 2010, ISBN 978-3-8274-2023-7 , pp. 596 , doi : 10.1007 / 978-3-8274-2224-8_5 ( springer.com [accessed October 22, 2017]).

[2] Jing Jiang: Information Extraction from Text . In: Mining Text Data . Springer, Boston, MA, 2012, ISBN 978-1-4614-3222-7 , pp. 15 , doi : 10.1007 / 978-1-4614-3223-4_2 ( springer.com [accessed October 22, 2017]).

[3] ttp://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/marsh_slides.pdf