Supervised Entity Mention Coreference Resolution Algorithm

An Supervised Entity Mention Coreference Resolution Algorithm is a Data-Driven Mention Coreference Resolution Algorithm that is also a Supervised Coreference Resolution Algorithm.

• Context:
  • It can be applied by a Supervised Entity Mention Resolution System (to solve a Supervised Entity Mention Resolution Task).
  • …
• Counter-Example(s):
  • an Unsupervised Entity Mention Coreference Resolution Algorithm.
  • a Supervised Relation Mention Coreference Resolution Algorithm.
  • an Supervised Record Coreference Resolution Algorithm (such as a supervised duplicate record detection algorithm).
  • a Supervised Word Sense Disambiguation Algorithm.
• See: Supervised Anaphora Resolution Algorithm.

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References

2008

• (Clark and González-Brenes, 2008) ⇒ Jonathan H. Clark, and José P. González-Brenes. (2008). “Coreference: Current Trends and Future Directions." CMU course on Language and Statistics II Literature Review, Fall 2008.
  • “Until recently, statistical approaches treated coreference resolution as a binary classification problem, in which the probability of two mentions from the text [math]\displaystyle{ i }[/math] and [math]\displaystyle{ j }[/math] having a coreferential outcome can be calculated from data by estimating the probability of Denis and Baldridge (2007). “Pc(COREF|<i,j>) (1)

2001

• (Soon et al., 2001) ⇒ Wee Meng Soon, Hwee Tou Ng, and Daniel Chung Yong Lim. (2001). “A Machine Learning Approach to Coreference Resolution of Noun Phrases.” In: Computational Linguistics, Vol. 27, No. 4.

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