activity
20212023
most citedA Sequence-to-Set Network for Nested Named Entity Recognition

5 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2023

GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks

Xuming Hu, Aiwei Liu, Zeqi Tan +4

Relation extraction (RE) tasks show promising performance in extracting relations from two entities mentioned in sentences, given sufficient annotations available during training.…

cs.CL2022

Query-based Instance Discrimination Network for Relational Triple Extraction

Zeqi Tan, Yongliang Shen, Xuming Hu +4

Joint entity and relation extraction has been a core task in the field of information extraction. Recent approaches usually consider the extraction of relational triples from a ste…

cs.CL2022

Parallel Instance Query Network for Named Entity Recognition

Yongliang Shen, Xiaobin Wang, Zeqi Tan +5

Named entity recognition (NER) is a fundamental task in natural language processing. Recent works treat named entity recognition as a reading comprehension task, constructing type-…

cs.CL20215 cited

A Sequence-to-Set Network for Nested Named Entity Recognition

Zeqi Tan, Yongliang Shen, Shuai Zhang +2

Named entity recognition (NER) is a widely studied task in natural language processing. Recently, a growing number of studies have focused on the nested NER. The span-based methods…

cs.CL2021

Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition

Yongliang Shen, Xinyin Ma, Zeqi Tan +3

Named entity recognition (NER) is a well-studied task in natural language processing. Traditional NER research only deals with flat entities and ignores nested entities. The span-b…