Difference between revisions of "Finkel and Manning, EMNLP 2009. Nested Named Entity Recognition"
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== Brief description of the method == | == Brief description of the method == | ||
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| + | The authors model each sentence as a constituent tree. Each named entity would correspond to a phrase in the tree (i.e a subtree). A root node would connect the entire sentence. In addition, the POS tags of non-entities are also modeled. The diagram above is one such example of a "named entity tree". | ||
== Experimental Result == | == Experimental Result == | ||
Revision as of 19:57, 24 September 2011
Nested Named Entity Recognition, by J. R Finkel, C. D Manning. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009.
This Paper is available online [1].
Contents
Under construction 09/24
Summary
This paper focuses on a variant of the Named Entity Recognition problem. They present a method for identifying nested named entities using a discriminative constituency parser.
An example of a nested named entity in the first 3 tokens of the example sentence, which standard "flat" NER systems are unable to distinguish.
Brief description of the method
The authors model each sentence as a constituent tree. Each named entity would correspond to a phrase in the tree (i.e a subtree). A root node would connect the entire sentence. In addition, the POS tags of non-entities are also modeled. The diagram above is one such example of a "named entity tree".
Experimental Result
Dataset
The authors have released TwitterNER dataset and source code for the paper. The demo and data are available online at [2].
