TY - GEN
T1 - CSKG
T2 - 18th European Semantic Web Conference, ESWC 2021
AU - Ilievski, Filip
AU - Szekely, Pedro
AU - Zhang, Bin
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Sources of commonsense knowledge support applications in natural language understanding, computer vision, and knowledge graphs. Given their complementarity, their integration is desired. Yet, their different foci, modeling approaches, and sparse overlap make integration difficult. In this paper, we consolidate commonsense knowledge by following five principles, which we apply to combine seven key sources into a first integrated CommonSense Knowledge Graph (CSKG). We analyze CSKG and its various text and graph embeddings, showing that CSKG is well-connected and that its embeddings provide a useful entry point to the graph. We demonstrate how CSKG can provide evidence for generalizable downstream reasoning and for pre-training of language models. CSKG and all its embeddings are made publicly available to support further research on commonsense knowledge integration and reasoning.
AB - Sources of commonsense knowledge support applications in natural language understanding, computer vision, and knowledge graphs. Given their complementarity, their integration is desired. Yet, their different foci, modeling approaches, and sparse overlap make integration difficult. In this paper, we consolidate commonsense knowledge by following five principles, which we apply to combine seven key sources into a first integrated CommonSense Knowledge Graph (CSKG). We analyze CSKG and its various text and graph embeddings, showing that CSKG is well-connected and that its embeddings provide a useful entry point to the graph. We demonstrate how CSKG can provide evidence for generalizable downstream reasoning and for pre-training of language models. CSKG and all its embeddings are made publicly available to support further research on commonsense knowledge integration and reasoning.
KW - Commonsense knowledge
KW - Embeddings
KW - Knowledge graph
UR - https://www.scopus.com/pages/publications/85111128411
UR - https://www.scopus.com/pages/publications/85111128411#tab=citedBy
U2 - 10.1007/978-3-030-77385-4_41
DO - 10.1007/978-3-030-77385-4_41
M3 - Conference contribution
AN - SCOPUS:85111128411
SN - 9783030773847
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 680
EP - 696
BT - The Semantic Web
A2 - Verborgh, Ruben
A2 - Hose, Katja
A2 - Paulheim, Heiko
A2 - Champin, Pierre-Antoine
A2 - Maleshkova, Maria
A2 - Corcho, Oscar
A2 - Ristoski, Petar
A2 - Alam, Mehwish
PB - Springer Nature
Y2 - 6 June 2021 through 10 June 2021
ER -