CRF-based Sequence Tagging Function

A CRF-based Sequence Tagging Function is a Conditional Random Field that is a Sequence Tagging Function.

• AKA: CRF-based Sequence Tagger.
• Context:
  • It can be a CRF-based Sequence Segmentation Function (e.g. if it uses an IBO Tag Set).
• Example(s):
  • a CRF-based NER Tagger,
  • a CRF-based POS Tagger,
  • a CRF-based Text Chunker.
  • a CRF-based Concept Mention Tagger.
  • …
• Counter-Example(s):
  • a CRF-based Tree Tagging Function.
  • a CRF-based Lattice Tagging Function.
  • an SVM-based Sequence Tagging Function.
• See: CRF System.

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References

2005

• (Wallach, 2005) ⇒ Hanna M. Wallach. (2005). “Conditional Random Fields." Literature Survey Webpage.
  • Conditional random fields (CRFs) are a probabilistic framework for labeling and segmenting structured data, such as sequences, trees and lattices.

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