no code implementations • 4 Jul 2022 • Tao He, Ming Liu, Yixin Cao, Tianwen Jiang, Zihao Zheng, Jingrun Zhang, Sendong Zhao, Bing Qin
In this paper, we solve the sparse KGC from these two motivations simultaneously and handle their respective drawbacks further, and propose a plug-and-play unified framework VEM$^2$L over sparse KGs.
no code implementations • EMNLP (Eval4NLP) 2021 • Qingkai Zeng, Mengxia Yu, Wenhao Yu, Tianwen Jiang, Meng Jiang
It can be used to validate the label consistency (or catches the inconsistency) in multiple sets of NER data annotation.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Qingkai Zeng, Wenhao Yu, Mengxia Yu, Tianwen Jiang, Tim Weninger, Meng Jiang
The training process of scientific NER models is commonly performed in two steps: i) Pre-training a language model by self-supervised tasks on huge data and ii) fine-tune training with small labelled data.
1 code implementation • 25 Jul 2020 • Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang
In this work, we present a novel framework called CoEvoGNN for modeling dynamic attributed graph sequence.
no code implementations • 17 Jun 2020 • Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang
Noun phrases and relational phrases in Open Knowledge Bases are often not canonical, leading to redundant and ambiguous facts.
no code implementations • IJCNLP 2019 • Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh Chawla, Meng Jiang
In this work, we propose a new sequence labeling framework (as well as a new tag schema) to jointly extract the fact and condition tuples from statement sentences.
no code implementations • 26 Jun 2019 • Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang
Conditions are essential in the statements of biological literature.
no code implementations • 8 Mar 2019 • Tianwen Jiang, Sendong Zhao, Jing Liu, Jin-Ge Yao, Ming Liu, Bing Qin, Ting Liu, Chin-Yew Lin
Time-DS is composed of a time series instance-popularity and two strategies.
no code implementations • 8 Mar 2019 • Tianwen Jiang, Ming Liu, Bing Qin, Ting Liu
This paper investigates an attention-based automatic paradigm called TransATT for attribute acquisition, by learning the representation of hierarchical classes and attributes in Chinese ontology.