Phuong Nguyen


Complex Word Identification in Vietnamese: Towards Vietnamese Text Simplification
Phuong Nguyen | David Kauchak
Proceedings of the Workshop on Multilingual Information Access (MIA)

Text Simplification has been an extensively researched problem in English, but has not been investigated in Vietnamese. We focus on the Vietnamese-specific Complex Word Identification task, often the first step in Lexical Simplification (Shardlow, 2013). We examine three different Vietnamese datasets constructed for other Natural Language Processing tasks and show that, like in other languages, frequency is a strong signal in determining whether a word is complex, with a mean accuracy of 86.87%. Across the datasets, we find that the 10% most frequent words in many corpus can be labelled as simple, and the rest as complex, though this is more variable for smaller corpora. We also examine how human annotators perform at this task. Given the subjective nature, there is a fair amount of variability in which words are seen as difficult, though majority results are more consistent.


CovRelex: A COVID-19 Retrieval System with Relation Extraction
Vu Tran | Van-Hien Tran | Phuong Nguyen | Chau Nguyen | Ken Satoh | Yuji Matsumoto | Minh Nguyen
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations

This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers. This work aims at building a system supporting users efficiently in acquiring knowledge across a huge number of COVID-19 scientific papers published rapidly. Our system can be accessed via