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Learning Sequence Encoders for Temporal Knowledge Graph Completion
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[García-Durán et al., 2018] represents the concatenation of relation and timestamp as a sequence of tokens, and the representation of the synthetic relation is the final hidden state of an LSTM.
“[García-Durán et al., 2018] represents the concatenation of relation and timestamp as a sequence of tokens, e.g., {championOf, 2y, 0y, 1y, 0y} (y means year) for championOf :2010.The representation of synthetic relation is obtained as the final hidden state of an LSTM [Hochreiter and Schmidhuber, 1997], with the tokens as the input.”
From Temporal Knowledge Graph Completion: A Survey (2023) · cites this paper as García-Durán et al., 2018
YAGO15K augments events of FB15K with time intervals similar to WIKIDATA.
“YAGO15K [García-Durán et al., 2018] augmentes events of FB15K [Bordes et al., 2013] with time intervals similar to WIKI-DATA”
From Temporal Knowledge Graph Completion: A Survey (2023) · cites this paper as García-Durán et al., 2018
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Adam: A Method for Stochastic Optimization
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A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
Ji, S., Pan, S., Cambria, E., Marttinen, P., & Yu, P. S. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3070843 · Cited by 2,947
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
Wu, J., Cao, M., Cheung, J. C. K., & Hamilton, W. L. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.462 · Cited by 167
Temporal Knowledge Graph Completion: A Survey
Cai, B., Xiang, Y., Gao, L., Zhang, H., Li, Y., & Li, J. (2023) · Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/734 · Cited by 133
Large Language Models Can Learn Temporal Reasoning
Xiong, S., Payani, A., Kompella, R., & Fekri, F. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2024.acl-long.563 · Cited by 47
Qian, X., Zhang, Y., Zhao, Y., Zhou, B., Sui, X., Zhang, L., & Song, K. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2024.emnlp-main.394 · Cited by 35
Metadata
- Authors
- García-Durán, A., Dumančić, S., & Niepert, M.
- Venue
- Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
- Published
- 2018
- Pages
- 4816-4821
- Cited by
- 449
- References
- 1
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