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DarNERcorp: a Named Entity Recognition Corpus in the Moroccan Dialect

Domain:

natural language processing

Record type:

dataset
Creator:
Han
Editor:
HanAsm
Publisher:
Men
Host:avatar
DarNERcorp is a manually annotated corpus for Named Entity Recognition (NER) in the Moroccan Dialect or Darija. The corpus contains more than 65K tokens, 13.8% of which are named entities. Named entities in the dataset are annotated with one of the following tags, using the BIO tagging scheme: person (PER), location (LOC), organization (ORG), miscellaneous (MISC). The distribution of named entities in the dataset is as follows: PER (15.3%), LOC (38.1%), ORG (15.5%), MISC (31.1%). The corpus is presented in the Data folder and it is split into two sets: DarNERcorp_train and DarNERcorp_test. The first set represents 80% of the data and the second represents 20%. In addition to the data, the Python scripts used in the collection and data formatting are provided in the Code folder.

Visit

doi.orgdata.mendeley.com

Tasks

information extractionnamed entity recognition

Languages

Arabic, Algerian Spoken

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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