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Found 6 papers, 4 papers with code
Why Attention? Analyzing and Remedying BiLSTM Deficiency in Modeling Cross-Context for NER
State-of-the-art approaches of NER have used sequence-labeling BiLSTM as a core module.
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER
We test the practical impacts of the deficiency on real-world NER datasets, OntoNotes 5. 0 and WNUT 2017, with clear and consistent improvements over the baseline, up to 8. 7% on some of the multi-token entity mentions.
Ranked #19 on
Named Entity Recognition (NER)
on WNUT 2017
CA-EHN: Commonsense Analogy from E-HowNet
We present CA-EHN, the first commonsense word analogy dataset containing 90, 505 analogies covering 5, 656 words and 763 relations.
GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction
In contrast to previous baselines, we consider the interaction between named entities and relations via a 2nd-phase relation-weighted GCN to better extract relations.
CKIP at IJCNLP-2017 Task 2: Neural Valence-Arousal Prediction for Phrases
In addition, the CKIP phrase Valence-Arousal (VA) predictor depends on knowledge of modifier words and head words.
Leveraging Linguistic Structures for Named Entity Recognition with Bidirectional Recursive Neural Networks
Motivated by the observation that named entities are highly related to linguistic constituents, we propose a constituent-based BRNN-CNN for named entity recognition.
