Supervised Named Entity Recognition (NER) System

A Supervised Named Entity Recognition (NER) System is a data-driven NER system that is a supervised sequence recognition system which implements a supervised NER algorithm to solve a supervised NER task.

• Context:
  • It can make use of the BCEUO Tag Set.
• Example(s):
  • https://github.com/glample/tagger
  • a LingPipe NER System.
  • a MALLET NER System.
  • a Stanford NER System.
  • an Apache OpenNLP NER System.
  • …
• Counter-Example(s):
  • a Dictionary-based NER System.
  • a Rule-based NER System.
  • a Supervised NER Canonicalization System.
  • a Supervised Gene Finding System.
• See: Sequence Tagging Task.

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References

2016

• (Github, 2016) ⇒ https://github.com/glample/tagger
  • QUOTE: ... NER Tagger is an implementation of a Named Entity Recognizer that obtains state-of-the-art performance in NER on the 4 CoNLL datasets (English, Spanish, German and Dutch) without resorting to any language-specific knowledge or resources such as gazetteers. Details about the model can be found at: http://arxiv.org/abs/1603.01360 ...

2009

• (Stanford University NLP, 2009) ⇒ Stanford Named Entity Recognizer System: http://nlp.stanford.edu/software/CRF-NER.shtml
  • QUOTE: CRFClassifier is a Java implementation of a Named Entity Recognizer.

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