Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering
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Abstract (arXiv)
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 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 and an introductory video are both available online.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 31 references that are in the map. First posted on arXiv 28 May 2021.
Builds on
15 of 31 references.
References · 15
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1.
3 papers.