Named Entity Mention Detection Task
- AKA: Named Entity Detection Task, Named Entity Mention Segmentation Task, Named Entity Mention Segmentation.
- input: Text Item
- output: a Named Entity Mention Annotated Text Item.
- It can be a part of the Named Entity Recognition Task.
- It can be solved by a Named Entity Mention Detection System (that implements a Named Entity Mention Detection Algorithm).
- It can be a Supervised NER Detection Task, if a NER Training Set is provided.
- It can be a Dictionary-based NER Detection Task, if an Entity Database is provided.
- [math]f[/math]("Jane Zhou went to São Paolo") ⇒ "[Jane Zhou] went to [São Paolo]".
- See: Entity Record Detection Task.
- (Sutton & McCallum, 2007) ⇒ Charles Sutton, and Andrew McCallum. (2007). “An Introduction to Conditional Random Fields for Relational Learning.” In: (Getoor & Taskar, 2007).
- The named-entity recognition task is, given a sentence, first to segment which words are part of entities, and then to classify each entity by type (person, organization, location, and so on). The challenge of this problem is that many named entities are too rare to appear even in a large training set, and therefore the system must identify them based only on context.