Named entity extraction (NEE) and disambiguation (NED) are two areas of research that are well covered in literature. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web. Although these topics are highly dependent, almost no existing works examine this dependency. It is the aim of this position paper to explore that dependency and show how one affects the other, and vice versa. We show the benefit of using this reinforcement effect on two domains: NEE and NED for toponyms in formal text; and for arbitrary entity types in informal short text in tweets. Finally we give an insight about the potential of this approach for future research.
|Title of host publication||Proceedings of the Sixth International Workshop on Exploiting Semantic Annotations in Information Retrieval, ESAIR 2013|
|Place of Publication||New York|
|Publisher||Association for Computing Machinery (ACM)|
|Number of pages||3|
|Publication status||Published - Oct 2013|
- Named Entity RecognitionNamed Entity LinkingNamed Entity ExtractionNamed Entity DisambiguationSocial MediaTwitterTweetsMicroblogs
Habib, M. B., & van Keulen, M. (2013). Named entity extraction and disambiguation: the missing link. In Proceedings of the Sixth International Workshop on Exploiting Semantic Annotations in Information Retrieval, ESAIR 2013 (pp. 37-40). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/2513204.2513217