9 citations · 33 across the 10 of their papers we have counts for
10 papers · 1 filter
Universal Information Extraction as Unified Semantic Matching
Jie Lou, Yaojie Lu, Dai Dai +5
The challenge of information extraction (IE) lies in the diversity of label schemas and the heterogeneity of structures. Traditional methods require task-specific model design and…
Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model
Wenkai Zhang, Hongyu Lin, Xianpei Han +4
Denoising is the essential step for distant supervision based named entity recognition. Previous denoising methods are mostly based on instance-level confidence statistics, which i…
Syntactic and Semantic-driven Learning for Open Information Extraction
Jialong Tang, Yaojie Lu, Hongyu Lin +4
One of the biggest bottlenecks in building accurate, high coverage neural open IE systems is the need for large labelled corpora. The diversity of open domain corpora and the varie…
ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling
Yaojie Lu, Annan Li, Hongyu Lin +2
ISCAS participated in two subtasks of SemEval 2020 Task 5: detecting counterfactual statements and detecting antecedent and consequence. This paper describes our system which is ba…
End-to-End Neural Event Coreference Resolution
Yaojie Lu, Hongyu Lin, Jialong Tang +2
Traditional event coreference systems usually rely on pipeline framework and hand-crafted features, which often face error propagation problem and have poor generalization ability.…
A Rigorous Study on Named Entity Recognition: Can Fine-tuning Pretrained Model Lead to the Promised Land?
Hongyu Lin, Yaojie Lu, Jialong Tang +4
Fine-tuning pretrained model has achieved promising performance on standard NER benchmarks. Generally, these benchmarks are blessed with strong name regularity, high mention covera…
Cost-sensitive Regularization for Label Confusion-aware Event Detection
Hongyu Lin, Yaojie Lu, Xianpei Han +1
In supervised event detection, most of the mislabeling occurs between a small number of confusing type pairs, including trigger-NIL pairs and sibling sub-types of the same coarse t…
Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networks
Hongyu Lin, Yaojie Lu, Xianpei Han +1
Sequential labeling-based NER approaches restrict each word belonging to at most one entity mention, which will face a serious problem when recognizing nested entity mentions. In t…
Adaptive Scaling for Sparse Detection in Information Extraction
Hongyu Lin, Yaojie Lu, Xianpei Han +1
This paper focuses on detection tasks in information extraction, where positive instances are sparsely distributed and models are usually evaluated using F-measure on positive clas…
Nugget Proposal Networks for Chinese Event Detection
Hongyu Lin, Yaojie Lu, Xianpei Han +1
Neural network based models commonly regard event detection as a word-wise classification task, which suffer from the mismatch problem between words and event triggers, especially…