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Register a new userA Survey of Named Entity Recognition in Assamese and other Indian Languages
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Pranjal Protim Borah
Publication date
2014
fields
Informatics Engineering
and research's language is
English
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Named Entity Recognition is always important when dealing with major Natural Language Processing tasks such as information extraction, question-answering, machine translation, document summarization etc so in this paper we put forward a survey of Named Entities in Indian Languages with particular reference to Assamese. There are various rule-based and machine learning approaches available for Named Entity Recognition. At the very first of the paper we give an idea of the available approaches for Named Entity Recognition and then we discuss about the related research in this field. Assamese like other Indian languages is agglutinative and suffers from lack of appropriate resources as Named Entity Recognition requires large data sets, gazetteer list, dictionary etc and some useful feature like capitalization as found in English cannot be found in Assamese. Apart from this we also describe some of the issues faced in Assamese while doing Named Entity Recognition.
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We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders. We detail characteristics of the languages to help researchers understand the challenges that these languages pose for NER. We analyze our datasets and conduct an extensive empirical evaluation of state-of-the-art methods across both supervised and transfer learning settings. We release the data, code, and models in order to inspire future research on African NLP.
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