The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A shortest path dependency kernel for relation extraction
Open accessAbstract
We present a novel approach to relation extraction, based on the observation that the information required to assert a relationship between two named entities in the same sentence is typically captured by the shortest path between the two entities in the dependency graph. Experiments on extracting top-level relations from the ACE (Automated Content Extraction) newspaper corpus show that the new shortest path dependency kernel outperforms a recent approach based on dependency tree kernels.
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Dependency tree kernels for relation extraction
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Kernel methods for relation extraction
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Cited by
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.-J., Shamma, D. A., et al. (2017) · International Journal of Computer Vision · doi:10.1007/s11263-016-0981-7 · Cited by 5,107
Open information extraction from the web
Etzioni, O., Banko, M., Soderland, S., & Weld, D. S. (2008) · Communications of the ACM · doi:10.1145/1409360.1409378 · Cited by 1,012
Graph Convolution over Pruned Dependency Trees Improves Relation Extraction
Zhang, Y., Qi, P., & Manning, C. D. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1244 · Cited by 847
Sarawagi, S. (2008) · Foundations and Trends in Databases · doi:10.1561/1900000003 · Cited by 707
A Frustratingly Easy Approach for Entity and Relation Extraction
Zhong, Z., & Chen, D. (2020) · arXiv · doi:10.48550/arxiv.2010.12812 · Cited by 531
Metadata
- Authors
- Bunescu, R. C., & Mooney, R. J.
- Venue
- Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05
- Published
- 2005
- Pages
- 724-731
- OpenAlex
- W2138627627
- Cited by
- 955
- References
- 11
- FWCI
- 17.17
- Type
- conference paper
- Language
- en
- Open access
- gold
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