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NER-FL: A Novel Named Entity Recognizer of Farsi Language using the Web-Based Natural Language Processors and Semantic Annotations

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 98 - Number 1
Year of Publication: 2014
Authors:
Babak Farhadi
10.5120/17150-7193

Babak Farhadi. Article: NER-FL: A Novel Named Entity Recognizer of Farsi Language using the Web-Based Natural Language Processors and Semantic Annotations. International Journal of Computer Applications 98(1):34-37, July 2014. Full text available. BibTeX

@article{key:article,
	author = {Babak Farhadi},
	title = {Article: NER-FL: A Novel Named Entity Recognizer of Farsi Language using the Web-Based Natural Language Processors and Semantic Annotations},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {98},
	number = {1},
	pages = {34-37},
	month = {July},
	note = {Full text available}
}

Abstract

Named Entity Recognition is a main task in the NLP area that has yielded multiple web-based natural language processors gaining popularity in the Semantic Web community for extracting knowledge from web data. These processors are generally located as pipelines, using dedicated APIs and various taxonomy for extracting, classifying and disambiguating named entities. In this paper, we address the problem of NER on Farsi language by proposing NER-FL, a novel semantic framework which unifies three popular named entity extractors available on the web, and the NER-FL ontology which provides a rich set of axioms aligning the taxonomies of these web natural language processors automatically on the LOD-cloud.

References

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