118 citations · 322 across the 24 of their papers we have counts for
4 papers · 1 filter
Materialized Knowledge Bases from Commonsense Transformers
Tuan-Phong Nguyen, Simon Razniewski
Starting from the COMET methodology by Bosselut et al. (2019), generating commonsense knowledge directly from pre-trained language models has recently received significant attentio…
Language Models As or For Knowledge Bases
Simon Razniewski, Andrew Yates, Nora Kassner +1
Pre-trained language models (LMs) have recently gained attention for their potential as an alternative to (or proxy for) explicit knowledge bases (KBs). In this position paper, we…
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering
Tuan-Phong Nguyen, Simon Razniewski, Gerhard Weikum
ASCENT is a fully automated methodology for extracting and consolidating commonsense assertions from web contents (Nguyen et al., WWW 2021). It advances traditional triple-based co…
Commonsense Knowledge Base Construction in the Age of Big Data
Simon Razniewski
Compiling commonsense knowledge is traditionally an AI topic approached by manual labor. Recent advances in web data processing have enabled automated approaches. In this demonstra…