Disambiguation to Wikipedia (D2W) Task

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A Disambiguation to Wikipedia (D2W) Task is a Text Wikification Task whose input is a Wikipedia snapshot.



References

2019

  • (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Entity_linking Retrieved:2019-6-15.
    • In natural language processing, entity linking, named entity linking (NEL), named entity disambiguation (NED), named entity recognition and disambiguation (NERD) or named entity normalization (NEN)[1] is the task of determining the identity of entities mentioned in text. For example, given the sentence "Paris is the capital of France", the idea is to determine that "Paris" refers to the city of Paris and not to Paris Hilton or any other entity that could be referred as "Paris". NED is different from named entity recognition (NER) in that NER identifies the occurrence or mention of a named entity in text but it does not identify which specific entity it is.

      Entity linking requires a knowledge base containing the entities to which entity mentions can be linked. A popular choice for entity linking on open domain text are knowledge-bases based on Wikipedia,[1] [2] in which each page is regarded as a named entity. NED using Wikipedia entities has been also called wikification (see Wikify! an early entity linking system[3] ). A knowledge base may also be induced automatically from training text [4] or manually built.[5] (...)

  1. 1.0 1.1 M. A. Khalid, V. Jijkoun and M. de Rijke (2008). The impact of named entity normalization on information retrieval for question answering. Proc. ECIR.
  2. Xianpei Han, Le Sun and Jun Zhao (2011). Collective entity linking in web text: a graph-based method. Proc. SIGIR.
  3. Rada Mihalcea and Andras Csomai (2007)Wikify! Linking Documents to Encyclopedic Knowledge. Proc. CIKM.
  4. Aaron M. Cohen (2005). Unsupervised gene/protein named entity normalization using automatically extracted dictionaries. Proc. ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics, pp. 17–24.
  5. Wikidata

2016

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2008

2007