LM-KBC 2022
Knowledge Base Construction from Pre-trained Language Models 2022

Table of Contents

Challenge overview

• LM-KBC: Knowledge Base Construction from Pre-trained Language Models 1-10
  Sneha Singhania , Tuan-Phong Nguyen , Simon Razniewski
  
  Summary: There were a total of 8 submissions to the two tracks of the challenge. Out of these, 6 teams submitted a paper for peer review (including one dataset paper). We accepted all 6 papers for this volume.

System papers

• Prompting as Probing: Using Language Models for Knowledge Base Construction 11-34
  Dimitrios Alivanistos , Selene Baez Santamaria , Michael Cochez , Jan-Christoph Kalo , Emile van Krieken , Thiviyan Thanapalasingam
• Task-specific Pre-training and Prompt Decomposition for Knowledge Graph Population with Language Models 35-45
  Tianyi Li , Wenyu Huang , Nikos Papasarantopoulos , Pavlos Vougiouklis , Jeff Z. Pan
• Knowledge Base Construction from Pre-trained Language Models by Prompt learning 46-54
  Xiao Ning , Remzi Celebi
• Prompt Design and Answer Processing for Knowledge Base Construction from Pre-trained Language Models 55-66
  Xiao Fang , Alex Kalinowski , Haoran Zhao , Ziao You , Yuhao Zhang , Yuan An
• Manual Prompt Generation For Language Model Probing 67-76
  Sumit Dalal , Abhisek Sharma , Sarika Jain , Mayank Dave