1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CL2019★ 1 cited
ScienceExamCER: A High-Density Fine-Grained Science-Domain Corpus for Common Entity Recognition
Hannah Smith, Zeyu Zhang, John Culnan +1
Named entity recognition identifies common classes of entities in text, but these entity labels are generally sparse, limiting utility to downstream tasks. In this work we present…
cs.CL2019
QASC: A Dataset for Question Answering via Sentence Composition
Tushar Khot, Peter Clark, Michal Guerquin +2
Composing knowledge from multiple pieces of texts is a key challenge in multi-hop question answering. We present a multi-hop reasoning dataset, Question Answering via Sentence Comp…
cs.CL2019
Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
Dongfang Xu, Peter Jansen, Jaycie Martin +5
Prior work has demonstrated that question classification (QC), recognizing the problem domain of a question, can help answer it more accurately. However, developing strong QC algor…