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2023 | OriginalPaper | Buchkapitel

PromptIE - Information Extraction with Prompt-Engineering and Large Language Models

verfasst von : Sigurd Schacht, Sudarshan Kamath Barkur, Carsten Lanquillon

Erschienen in: HCI International 2023 Posters

Verlag: Springer Nature Switzerland

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Abstract

Extracting triples of subjects, objects, and predicates from text to populate knowledge bases traditionally involves several intermediate steps such as co-reference resolution, named entity recognition, and relationship extraction. Treating triple extraction as translation task from source sentences to sets of triples, we present an end-to-end solution for information extraction that uses task prefixes to prompts a fine-tuned large language model to extract triples from text. Thus, the need for data labeling and training multiple models is reduced.

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Literatur
1.
Zurück zum Zitat Adnan, K., Akbar, R.: Limitations of information extraction methods and techniques for heterogeneous unstructured big data. Int. J. Eng. Bus. Manag. 11, 1847979019890771 (2019)CrossRef Adnan, K., Akbar, R.: Limitations of information extraction methods and techniques for heterogeneous unstructured big data. Int. J. Eng. Bus. Manag. 11, 1847979019890771 (2019)CrossRef
2.
4.
Zurück zum Zitat Del Corro, L., Gemulla, R.: ClausIE: clause-based open information extraction. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 355–366 (2013) Del Corro, L., Gemulla, R.: ClausIE: clause-based open information extraction. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 355–366 (2013)
6.
Zurück zum Zitat Etzioni, O., Banko, M., Soderland, S., Weld, D.S.: Open information extraction from the web. Commun. ACM 51(12), 68–74 (2008)CrossRef Etzioni, O., Banko, M., Soderland, S., Weld, D.S.: Open information extraction from the web. Commun. ACM 51(12), 68–74 (2008)CrossRef
7.
Zurück zum Zitat Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp. 1535–1545. Association for Computational Linguistics (2011). https://aclanthology.org/D11-1142 Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp. 1535–1545. Association for Computational Linguistics (2011). https://​aclanthology.​org/​D11-1142
10.
Zurück zum Zitat Mausam, M.: Open information extraction systems and downstream applications. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp. 4074–4077 (2016) Mausam, M.: Open information extraction systems and downstream applications. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp. 4074–4077 (2016)
11.
Zurück zum Zitat Niklaus, C., Cetto, M., Freitas, A., Handschuh, S.: A survey on open information extraction. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 3866–3878. Association for Computational Linguistics (2018). https://aclanthology.org/C18-1326 Niklaus, C., Cetto, M., Freitas, A., Handschuh, S.: A survey on open information extraction. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 3866–3878. Association for Computational Linguistics (2018). https://​aclanthology.​org/​C18-1326
14.
15.
Zurück zum Zitat Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311–318 (2002) Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311–318 (2002)
16.
Zurück zum Zitat Ro, Y., Lee, Y., Kang, P.: Multi\(^{2}\)OIE: multilingual open information extraction based on multi-head attention with BERT. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 1107–1117 (2020). http://arxiv.org/abs/2009.08128 Ro, Y., Lee, Y., Kang, P.: Multi\(^{2}\)OIE: multilingual open information extraction based on multi-head attention with BERT. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 1107–1117 (2020). http://​arxiv.​org/​abs/​2009.​08128
17.
Zurück zum Zitat Stanovsky, G., Michael, J., Zettlemoyer, L., Dagan, I.: Supervised open information extraction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 885–895. Association for Computational Linguistics (2018). http://aclweb.org/anthology/N18-1081 Stanovsky, G., Michael, J., Zettlemoyer, L., Dagan, I.: Supervised open information extraction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 885–895. Association for Computational Linguistics (2018). http://​aclweb.​org/​anthology/​N18-1081
19.
Zurück zum Zitat Wang, C., Liu, X., Chen, Z., Hong, H., Tang, J., Song, D.: Zero-shot information extraction as a unified text-to-triple translation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 1225–1238. Association for Computational Linguistics (2021). https://aclanthology.org/2021.emnlp-main.94 Wang, C., Liu, X., Chen, Z., Hong, H., Tang, J., Song, D.: Zero-shot information extraction as a unified text-to-triple translation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 1225–1238. Association for Computational Linguistics (2021). https://​aclanthology.​org/​2021.​emnlp-main.​94
20.
22.
Zurück zum Zitat Zhang, Y., Zhong, V., Chen, D., Angeli, G., Manning, C.D.: Position-aware attention and supervised data improve slot filling. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 35–45. Association for Computational Linguistics (2017). http://aclweb.org/anthology/D17-1004 Zhang, Y., Zhong, V., Chen, D., Angeli, G., Manning, C.D.: Position-aware attention and supervised data improve slot filling. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 35–45. Association for Computational Linguistics (2017). http://​aclweb.​org/​anthology/​D17-1004
Metadaten
Titel
PromptIE - Information Extraction with Prompt-Engineering and Large Language Models
verfasst von
Sigurd Schacht
Sudarshan Kamath Barkur
Carsten Lanquillon
Copyright-Jahr
2023
DOI
https://doi.org/10.1007/978-3-031-36004-6_69

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