5 citations · 7 across the 3 of their papers we have counts for
4 papers · 1 filter
Does Recommend-Revise Produce Reliable Annotations? An Analysis on Missing Instances in DocRED
Quzhe Huang, Shibo Hao, Yuan Ye +3
DocRED is a widely used dataset for document-level relation extraction. In the large-scale annotation, a \textit{recommend-revise} scheme is adopted to reduce the workload. Within…
Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction
Quzhe Huang, Shengqi Zhu, Yansong Feng +3
Document-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a smal…
Integrating Relation Constraints with Neural Relation Extractors
Yuan Ye, Yansong Feng, Bingfeng Luo +2
Recent years have seen rapid progress in identifying predefined relationship between entity pairs using neural networks NNs. However, such models often make predictions for each en…
Analysis of Bag-of-n-grams Representation's Properties Based on Textual Reconstruction
Qi Huang, Zhanghao Chen, Zijie Lu +1
Despite its simplicity, bag-of-n-grams sen- tence representation has been found to excel in some NLP tasks. However, it has not re- ceived much attention in recent years and fur- t…