ACL2021
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering
Tuan-Phong Nguyen, Simon Razniewski, Gerhard Weikum
Abstract
ASCENT is a fully automated methodology for extracting and consolidating commonsense assertions from web contents (Nguyen et al., 2021) . It advances traditional triple-based commonsense knowledge representation by capturing semantic facets like locations and purposes, and composite concepts, i.e., subgroups and related aspects of subjects. In this demo, we present a web portal that allows users to understand its construction process, explore its content, and observe its impact in the use case of question answering. The demo website 1 and an introductory video 2 are both available online.