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20202023
most citedComprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision

38 citations · 56 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CL2023

ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision

Ming Zhong, Siru Ouyang, Minhao Jiang +4

Structured chemical reaction information plays a vital role for chemists engaged in laboratory work and advanced endeavors such as computer-aided drug design. Despite the importanc…

cs.CL2023

Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models

Pengcheng Jiang, Shivam Agarwal, Bowen Jin +3

The mission of open knowledge graph (KG) completion is to draw new findings from known facts. Existing works that augment KG completion require either (1) factual triples to enlarg…

cs.CL2023

OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing

Tanay Komarlu, Minhao Jiang, Xuan Wang +1

Fine-grained entity typing (FET), which assigns entities in text with context-sensitive, fine-grained semantic types, is a basic but important task for knowledge extraction from un…

cs.CL20211 cited

Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

Yu Meng, Yunyi Zhang, Jiaxin Huang +4

We study the problem of training named entity recognition (NER) models using only distantly-labeled data, which can be automatically obtained by matching entity mentions in the raw…

cs.CL202038 cited

Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision

Xuan Wang, Xiangchen Song, Bangzheng Li +2

We created this CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020-03-13). This CORD-NER data…