Difference between revisions of "Benajiba and Rosso, LREC 2008"
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== Summary == | == Summary == | ||
| − | This [[Category::paper]] describes | + | This [[Category::paper]] describes a [[UsesMethod::Conditional Random Field]] approach to the Arabic [[AddressesProblem::Named Entity Recognition]] problem. |
[[UsesDataset::ANERcorp]] | [[UsesDataset::ANERcorp]] | ||
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| + | In this paper the authors used Conditional Random Fields | ||
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| + | Previous to this paper, the authors were using Maximum Entropy model [[RelatedPaper::]] with binary features which uses the word itself, the preceding word, the bigrams around the word and external resources. Furthermore in order to ease the difficulty of detecting the named entities, they used a 2-step approach where the first steps focused on detecting the entities and the second step classifies them. | ||
| + | person, location, organization and miscellaneous. | ||
Revision as of 06:07, 28 November 2010
Citation
Yassine Benajiba and Paolo Rosso. 2008. Arabic Named Entity Recognition using Conditional Random Fields. In Proc. of Workshop on HLT&NLP within the Arabic World, LREC'08.
Online version
Summary
This paper describes a Conditional Random Field approach to the Arabic Named Entity Recognition problem. ANERcorp
In this paper the authors used Conditional Random Fields
Previous to this paper, the authors were using Maximum Entropy model with binary features which uses the word itself, the preceding word, the bigrams around the word and external resources. Furthermore in order to ease the difficulty of detecting the named entities, they used a 2-step approach where the first steps focused on detecting the entities and the second step classifies them. person, location, organization and miscellaneous.
