A Framework for Named Entity Recognition for Malayalam—A Comparison of Different Deep Learning Architectures

Authors

R. Rajimol¹, V. S. Anoop^{2, *,}

¹Indian Institute of Information Technology and Management—Kerala (IIITM-K), Thiruvananthapuram, 695581, Kerala, India

²Rajagiri College of Social Sciences, Kochi, 683104, Kerala, India

^*Corresponding author. Email: anoop@rajagiri.edu

DOI

10.2991/nlpr.d.201005.001How to use a DOI?

Keywords

Named entity recognition; Malayalam language; Deep learning; Information extraction; Low resource language computing; Indic language processing

Abstract

Information extraction (IE) is the process of extracting relevant and useful patterns or information from unstructured data. Named entity recognition (NER) is a subtask of IE that identifies entities from unstructured text documents and organize them into different predefined categories such as person, location, organization, number, date, etc. NER is considered to be one of the important steps in natural language processing which may find direct applications in areas such as question answering (QA), entity linking, and co-reference resolution, to name a few. NER systems perform comparatively well in high-resource languages such as English but there is a lack of well-developed NER systems for low-resource languages such as Malayalam, which is an Indic language spoken in the state of Kerala, India. This work is an approach in this direction which makes use of deep learning (DL) techniques for developing a NER system for Malayalam. We have compared different DL approaches such as recurrent neural networks, gated recurrent unit, long short-term memory, and bi-directional long short-term memory and found that DL based approaches significantly outperform traditional shallow-learning based -approaches for NER. When compared with some state-of-the-art approaches our proposed framework is found to be outperforming in terms of precision, recall, and F-measure and could achieve an improved precision of 7.89% and 8.92% of F-measure.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

TY  - JOUR
AU  - R. Rajimol
AU  - V. S. Anoop
PY  - 2020
DA  - 2020/10/16
TI  - A Framework for Named Entity Recognition for Malayalam—A Comparison of Different Deep Learning Architectures
JO  - Natural Language Processing Research
SP  - 14
EP  - 22
VL  - 1
IS  - 1-2
SN  - 2666-0512
UR  - https://doi.org/10.2991/nlpr.d.201005.001
DO  - 10.2991/nlpr.d.201005.001
ID  - Rajimol2020
ER  -