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Preemptive information extraction using unrestricted relation discovery
Open accessAbstract
We are trying to extend the boundary of Information Extraction (IE) systems. Existing IE systems require a lot of time and human effort to tune for a new scenario. Preemptive Information Extraction is an attempt to automatically create all feasible IE systems in advance without human intervention. We propose a technique called Unrestricted Relation Discovery that discovers all possible relations from texts and presents them as tables. We present a preliminary system that obtains reasonably good results.
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Cited by
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Mintz, M., Bills, S., Snow, R., & Jurafsky, D. (2009) · Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - ACL-IJCNLP '09 · doi:10.3115/1690219.1690287 · Cited by 2,752
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
Sarawagi, S. (2008) · Foundations and Trends in Databases · doi:10.1561/1900000003 · Cited by 707
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Gruber, T. (2008) · Journal of Web Semantics · doi:10.1016/j.websem.2007.11.011 · Cited by 606
Continual Relation Learning via Episodic Memory Activation and Reconsolidation
Han, X., Dai, Y., Gao, T., Lin, Y., Liu, Z., Li, P., Sun, M., & Zhou, J. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2020.acl-main.573 · Cited by 104
Metadata
- Authors
- Shinyama, Y., & Sekine, S.
- Venue
- Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics -
- Published
- 2006
- Pages
- 304-311
- OpenAlex
- W2012179495
- Cited by
- 236
- References
- 0
- FWCI
- 9.84
- Type
- conference paper
- Language
- en
- Open access
- gold
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- Shinyama, Y., & Sekine, S. (2006). Preemptive information extraction using unrestricted relation discovery. Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics -. https://doi.org/10.3115/1220835.1220874
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