Papers by Huey Fang Ong

2 papers
Malaysian English News Decoded: A Linguistic Resource for Named Entity and Relation Extraction (2024.lrec-main)

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Challenge: Standard English and Malaysian English exhibit significant differences in morphosyntactic variations . existing datasets are not sufficient to enhance NLP tasks in Malaysian english .
Approach: They propose to use a Malaysian English news article dataset to refine NER models for Malaysian english.
Outcome: The proposed dataset can improve the performance of NER on Malaysian English.
Document-Level Zero-Shot Relation Extraction with Entity Side Information (2026.eacl-long)

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Challenge: Existing approaches rely on Large Language Models (LLMs) to generate synthetic data for unseen labels.
Approach: They propose a document-level zero-shot relation extraction framework with Entity Side Information to solve existing problems.
Outcome: The proposed approach achieves an average improvement of 11.6% in the macro F1-Score compared to baseline models and existing benchmarks.

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