Papers › A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala

A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala

3 Dec 2024arXiv:2412.02056archive 2025-07-28

Surangika Ranathunga, Asanka Ranasinghea, Janaka Shamala, Ayodya Dandeniyaa, Rashmi Galappaththia, Malithi Samaraweeraa

This paper presents a multi-way parallel English-Tamil-Sinhala corpus annotated with Named Entities (NEs), where Sinhala and Tamil are low-resource languages. Using pre-trained multilingual Language Models (mLMs), we establish new benchmark Named Entity Recognition (NER) results on this dataset for Sinhala and Tamil. We also carry out a detailed investigation on the NER capabilities of different types of mLMs. Finally, we demonstrate the utility of our NER system on a low-resource Neural Machine Translation (NMT) task. Our dataset is publicly released: https://github.com/suralk/multiNER.

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Low Resource Neural Machine TranslationLow-Resource Neural Machine TranslationMachine TranslationNERNMTNamed Entity RecognitionNamed Entity Recognition (NER)Translationnamed-entity-recognition

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