Supervised Named Entity Recognition (NER) Task

A Supervised Named Entity Recognition (NER) Task is a data-driven named entity recognition task that is a supervised text recognition task.

• Context:
  • input: an NER Training Corpus.
  • It can be solved by a Supervised Named Entity Recognition System (that implements a Supervised Named Entity Recognition Algorithm).
  • It can range from being a Fully-Supervised Named Entity Recognition Task to being a Semi-Supervised Named Entity Recognition Task.
  • It can support a Supervised Information Extraction Task.
  • …
• Example(s):
  • Supervised Person Name Recognition.
  • Supervised URL Recognition.
  • ...
• Counter-Example(s):
  • a Rule-based NER Task.
  • a Dictionary-based NER Task.
  • a Supervised Syntactic Phrase Chunking Task.
• See: Supervised Concept Mention Recognition Task.

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References

2013

• (Zhang, 2013) ⇒ Ziqi Zhang. (2013). “Named Entity Recognition: Challenges in Document Annotation, Gazetteer Construction and Disambiguation." PhD Thesis, University of Sheffield.

2007

• (Nadeau & Sekine, 2007) ⇒ David Nadeau, and Satoshi Sekine. (2007). “A Survey of Named Entity Recognition and Classification.” In: Lingvisticae Investigationes, 30(1).

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