CaEXR: A Joint Extraction Framework for Causal Relationships Based on Word-Pair Network
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5672-8_38
Reference19 articles.
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3. Hashimoto, C., et al.: Toward future scenario generation: extracting event causality exploiting semantic relation, context, and association features. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 987–997 (2014)
4. Zhou, B., et al.: An end-to-end tabular information-oriented causality event evolutionary knowledge graph for manufacturing documents. Adv. Eng. Inform. 50, 101441 (2021)
5. Lecture Notes in Computer Science;A Ittoo,2011
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