Unsupervised Relation Mention Extraction Task

An Unsupervised Relation Mention Extraction Task is a data-driven relation mention extraction task that is an unsupervised text-based extraction task.

• Context:
  • It can be solved by an Unsupervised Relation Mention Extraction System (that applies an Unsupervised Relation Mention Extraction algorithm).
• Example(s):
  • for the scientific domain (Gábor et al., 2016b).
  • …
• Counter-Example(s):
  • Supervised Relation Mention Extraction Task.
• See: Unsupervised Relation Extraction System.

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References

2016

• (Gábor et al., 2016b) ⇒ Kata Gábor, Haïfa Zargayouna, Isabelle Tellier, Davide Buscaldi, and Thierry Charnois. (2016). “Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining.” In: Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings. ISBN:978-3-319-46349-0
  • QUOTE: Unsupervised extraction is often applied to specialized domains, since the manual construction of knowledge bases or training examples for such domains is costly in terms of effort and expertise. The research we present is concerned with unsupervised relation extraction in the scientific domain.

2005

• (Jinxiu et al., 2005) ⇒ Chen Jinxiu, Ji Donghong, Tan Chew Lim, Niu Zhengyu. (2005). “Automatic Relation Extraction with Model Order Selection and Discriminative Label Identification.” In: Proceedings of 2nd International Joint Conference on Natural Language Processing (JICNLP-2005).

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