Arabic Named Entity Extractor

Synopsis

Named Entity Recognition "NER" is the process of selecting the most likely sequence of informative lexical items in a sentence. The process determines syntactic and semantic characteristics of the words from unstructured text, such as person, place, organization, date etc. and also classifies them to subcategories according to the taxonomy implemented.


MAPSSemanDatabasesSoftware
Arabic Part of Speech Tagger Arabic Corpus Arabic Root Extractor
Arabic Text Parser Arabic Roots Arabic Text Diacritizer
Arabic Ontology Processor Arabic Stems Arabic Verb Conjugator
Arabic Named Entity Extractor Loan Words Arabic Noun Inflector
Loan Terms Personal Names Retrieval
Colloquial Arabic Toponym Romanizer
English/Arabic Entity Names

Kalmasoft NERSys is an Arabic Named Entity Recognition/Extraction tool aimed at preparing Arabic annotated corpora; a context-sensitive rule-based solution utilizing hand-crafted set of comprehensive semantic and syntactic rules to deal with unstructured Arabic texts, the output is an annotated structured XML or JSON formatted corpus but SQL database and TXT are among the other output alternatives. For the purposes of quick review HTML, XLSX, and PDF are also available.

NERSys is designed to prepare Arabic structured datasets since documents of unstructured text are difficult to make use of in their raw nature in NLP applications like MT, IR, Entity linking, Semantic search, and search engines because there is more information there than in the raw text alone.

NERSys also implements advanced classification algorithm to categorize text to more than 20 predefined subject domains.


Arabic Named Entity Recognition
A screenshot of NERSys interface, you can view the technical specifications. You may also DOWNLOAD Evaluation copy.

Arabic Named Entity Recognition
Arabic Named Entity Recognition.

Home » MAPS » MAPS Semantics » Arabic Named Entity Extractor

Category Software | Reference MNERSYS | Family MAPSEMANL | Last updated 25/10/2021