sis 23(1):

Research Article

A Hybrid Named Entity Recognition System for Aviation Text

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  • @ARTICLE{10.4108/eetsis.4185,
        author={Bharathi A and Robin Ramdin and Preeja Babu and Vijay Krishna Menon and Chandrasekhar Jayaramakrishnan and Sudarasan Lakshmikumar},
        title={A Hybrid Named Entity Recognition System for Aviation Text},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={10},
        keywords={Named Entity Recognition, Machine Learning, Aviation Herald, Spacy NER, GPE, Rule Augmentation},
        doi={10.4108/eetsis.4185}
    }
    
  • Bharathi A
    Robin Ramdin
    Preeja Babu
    Vijay Krishna Menon
    Chandrasekhar Jayaramakrishnan
    Sudarasan Lakshmikumar
    Year: 2023
    A Hybrid Named Entity Recognition System for Aviation Text
    SIS
    EAI
    DOI: 10.4108/eetsis.4185
Bharathi A1, Robin Ramdin1,*, Preeja Babu1, Vijay Krishna Menon1, Chandrasekhar Jayaramakrishnan1, Sudarasan Lakshmikumar1
  • 1: KeepFlying
*Contact email: robin@keepflying.aero

Abstract

Named Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP) that aims to identify and categorize named entities in text. While NER has been well-studied in various domains, it remains a challenging task in new domains where annotated data is limited. In this paper, we propose an NER system for the aviation domain that addresses this challenge. Our system combines rule-based and supervised methods to develop a model with little to no manual annotation work.We evaluate our system on a benchmark dataset and it outperforms baseline scores and achieves competitive results. To the best of our knowledge, this is the first study to develop an NER system that specifically targets aviation entities. Our findings highlight the potential of our proposed system for NER in aviation and pave the way for future research in this area.