Search Results for author: Longhua Qian

Found 6 papers, 1 papers with code

Multi-layer Sequence Labeling-based Joint Biomedical Event Extraction

no code implementations10 Aug 2024 Gongchi Chen, Pengchao Wu, Jinghang Gu, Longhua Qian, Guodong Zhou

Hence, we propose MLSL, a method based on multi-layer sequence labeling for joint biomedical event extraction.

Event Extraction

Pipelined Biomedical Event Extraction Rivaling Joint Learning

no code implementations19 Mar 2024 Pengchao Wu, Xuefeng Li, Jinghang Gu, Longhua Qian, Guodong Zhou

Biomedical event extraction is an information extraction task to obtain events from biomedical text, whose targets include the type, the trigger, and the respective arguments involved in an event.

Event Extraction Relation Extraction

Joint Learning-based Causal Relation Extraction from Biomedical Literature

no code implementations2 Aug 2022 Dongling Li, Pengchao Wu, Yuehu Dong, Jinghang Gu, Longhua Qian, Guodong Zhou

Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions.

Relation Relation Extraction

Modeling Graph Structure in Transformer for Better AMR-to-Text Generation

1 code implementation IJCNLP 2019 Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, Guodong Zhou

Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence.

Abstract Meaning Representation AMR-to-Text Generation +1

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