Proper Noun Ontology

AKA: Named Entity Ontology.
Example(s):
Counter-Example(s):
- LinkedIn Database,
- WordNet database.
See: Ontology, Corpus, Knowledge Base, Natural Language Processing Task, Named Entity Disambiguation, Named Entity, Question Answering Task, Named Entity Recognition, Information Retrieval Task.

References

(Toral et al., 2008) ⇒ Antonio Toral, Rafael Muñoz, and Monica Monachini. (2008). “Named Entity WordNet.” In: Proceedings of the 6th Conference on Language Resources and Evaluation (LREC 2008).
- QUOTE: Regarding nouns, WordNet distinguishes between common nouns (classes) and proper nouns (instances) from version 2.1. (Miller and Hristea, 2006). On the one hand, WordNet’s coverage about open domain common nouns is quite high, but on the other it contains very few proper nouns^[1] . This is related with the following statement: “building a proper noun ontology is more difficult than building a common noun ontology as the set of proper nouns grows more rapidly” (Mann, 2002). The problem is then that a proper noun resource should be constantly updated(...)
  This paper presents Named Entity WordNet (NEWN), a new resource that extends WordNet with NEs automatically extracted from the English Wikipedia. Our hypothesis is that exploiting Wikipedia is a sensible choice to automatically populate LRs with proper nouns. The main reasons are that Wikipedia is a dynamic source, contains a huge amount of proper nouns and has some degree of structure that facilitates their extraction.

(Mann, 2002) ⇒ Gideon S. Mann. (2002). “Fine-Grained Proper Noun Ontologies for Question Answering.” In: Proceedings of the Worshop on Building and Using Semantic Networks (SemaNet'02) at (COLING 2002). doi:10.3115/1118735.1118746
- QUOTE: Unfortunately, building a proper noun ontology is more difficult than building a common noun ontology, since the set of proper nouns grows more rapidly. New people are born.