Leveraging Question Answering for Domain-Agnostic Information Extraction

Author:

Ferreira Bruno Carlos LuísORCID,Oliveira Hugo GonçaloORCID,Silva CatarinaORCID

Publisher

Springer Nature Switzerland

Reference18 articles.

1. Adnan, K., Akbar, R.: Limitations of information extraction methods and techniques for heterogeneous unstructured big data. Int. J. Eng. Bus. Manag. 11, 1847979019890771 (2019)

2. Arici, T., Kumar, K., Çeker, H., Saladi, A.S., Tutar, I.: Solving price per unit problem around the world: formulating fact extraction as question answering. arXiv preprint arXiv:2204.05555 (2022)

3. Baradaran, R., Ghiasi, R., Amirkhani, H.: A survey on machine reading comprehension systems. Nat. Lang. Eng. 28(6), 683–732 (2022)

4. Bhutani, N., Suhara, Y., Tan, W., Halevy, A.Y., Jagadish, H.V.: Open information extraction from question-answer pairs. CoRR abs/1903.00172 (2019). http://arxiv.org/abs/1903.00172

5. Brown, T., et al.: Language models are few-shot learners. In: Advances in Neural Information Processing Systems, vol. 33, pp. 1877–1901. Curran Associates, Inc. (2020)

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