no code implementations • EMNLP 2021 • Minh Van Nguyen, Tuan Ngo Nguyen, Bonan Min, Thien Huu Nguyen
To address this issue, we propose a novel crosslingual alignment method that leverages class information of REE tasks for representation learning.
no code implementations • EMNLP 2020 • Viet Dac Lai, Tuan Ngo Nguyen, Thien Huu Nguyen
Recent studies on event detection (ED) have shown that the syntactic dependency graph can be employed in graph convolution neural networks (GCN) to achieve state-of-the-art performance.
no code implementations • NAACL (TextGraphs) 2021 • Duy Phung, Tuan Ngo Nguyen, Thien Huu Nguyen
Prior work has demonstrated the benefits of the predicate-argument information and document context for resolving the coreference of event mentions.
no code implementations • 27 Oct 2020 • Viet Dac Lai, Tuan Ngo Nguyen, Thien Huu Nguyen
Recent studies on event detection (ED) haveshown that the syntactic dependency graph canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per-formance.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Amir Pouran Ben Veyseh, Tuan Ngo Nguyen, Thien Huu Nguyen
The goal of Event Argument Extraction (EAE) is to find the role of each entity mention for a given event trigger word.
no code implementations • WS 2019 • Tuan Ngo Nguyen, Franck Dernoncourt, Thien Huu Nguyen
Deep learning models have achieved state-of-the-art performances on many relation extraction datasets.