TY - GEN
T1 - BlabKG
AU - De Moraes Ligabue, Pedro
AU - Franco Brandao, Anarosa Alves
AU - Peres, Sarajane Marques
AU - Cozman, Fabio Gagliardi
AU - Pirozelli, Paulo
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The Blue Amazon represents a large area off the coast of Brazil. The region is important for economic reasons, as it holds the majority of Brazil's oil and gas resources, as well as for its biological, geological and environmental features. Not much information about this region, however, is organized in systematic and computer-readable ways. In this context, we built a knowledge graph for the Blue Amazon based on a set of 496 scientific paper abstracts on the subject. The corpus includes a large number of topics, such as biodiversity, natural resources and climate change. Entities and relationships were automatically extracted from text through the use of OpenIE (a relationship triple extraction method) and were combined using word embeddings. The generated knowledge graph was then evaluated by comparing it to the source documents. Results show that key knowledge was correctly extracted, but also that there is still room for improvement, specially when it comes to weeding out undesirable or context-dependent data.
AB - The Blue Amazon represents a large area off the coast of Brazil. The region is important for economic reasons, as it holds the majority of Brazil's oil and gas resources, as well as for its biological, geological and environmental features. Not much information about this region, however, is organized in systematic and computer-readable ways. In this context, we built a knowledge graph for the Blue Amazon based on a set of 496 scientific paper abstracts on the subject. The corpus includes a large number of topics, such as biodiversity, natural resources and climate change. Entities and relationships were automatically extracted from text through the use of OpenIE (a relationship triple extraction method) and were combined using word embeddings. The generated knowledge graph was then evaluated by comparing it to the source documents. Results show that key knowledge was correctly extracted, but also that there is still room for improvement, specially when it comes to weeding out undesirable or context-dependent data.
KW - Atlantic Ocean
KW - Blue Amazon
KW - Brazil
KW - knowledge graph
KW - relationship triple extraction
KW - word embeddings
UR - http://www.scopus.com/inward/record.url?scp=85148538081&partnerID=8YFLogxK
U2 - 10.1109/ICKG55886.2022.00028
DO - 10.1109/ICKG55886.2022.00028
M3 - Contribución a la conferencia
AN - SCOPUS:85148538081
T3 - Proceedings - 13th IEEE International Conference on Knowledge Graph, ICKG 2022
SP - 164
EP - 171
BT - Proceedings - 13th IEEE International Conference on Knowledge Graph, ICKG 2022
A2 - Li, Peipei
A2 - Yu, Kui
A2 - Chawla, Nitesh
A2 - Feldman, Ronen
A2 - Li, Qing
A2 - Wu, Xindong
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 30 November 2022 through 1 December 2022
ER -