{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T19:43:37Z","timestamp":1782416617705,"version":"3.54.5"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031342400","type":"print"},{"value":"9783031342417","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-34241-7_1","type":"book-chapter","created":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T17:02:50Z","timestamp":1685466170000},"page":"3-11","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Just Tell Me: Prompt Engineering in\u00a0Business Process Management"],"prefix":"10.1007","author":[{"given":"Kiran","family":"Busch","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Rochlitzer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diana","family":"Sola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henrik","family":"Leopold","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,5,31]]},"reference":[{"key":"1_CR1","unstructured":"van der Aa, H., Carmona, J., Leopold, H., Mendling, J., Padr\u00f3, L.: Challenges and opportunities of applying natural language processing in business process management. In: COLING, pp. 2791\u20132801 (2018)"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Bellan, P., Dragoni, M., Ghidini, C.: Extracting business process entities and relations from text using pre-trained language models and in-context learning. In: Enterprise Design, Operations, and Computing, pp. 182\u2013199 (2022)","DOI":"10.1007\/978-3-031-17604-3_11"},{"key":"1_CR3","unstructured":"Brown, T., et al.: Language models are few-shot learners. NeurIPS 33, 1877\u20131901 (2020)"},{"key":"1_CR4","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: NAACL-HLT, pp. 4171\u20134186 (2019)"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Galanti, R., Coma-Puig, B., de Leoni, M., Carmona, J., Navarin, N.: Explainable predictive process monitoring. In: ICPM, pp. 1\u20138 (2020)","DOI":"10.1109\/ICPM49681.2020.00012"},{"key":"1_CR6","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1007\/978-3-030-85347-1_13","volume-title":"Quality of Information and Communications Technology","author":"M K\u00e4ppel","year":"2021","unstructured":"K\u00e4ppel, M., Jablonski, S., Sch\u00f6nig, S.: Evaluating predictive business process monitoring approaches on small event logs. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., P\u00e9rez-Castillo, R. (eds.) QUATIC 2021. CCIS, vol. 1439, pp. 167\u2013182. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-85347-1_13"},{"key":"1_CR7","unstructured":"Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., Iwasawa, Y.: Large language models are zero-shot reasoners. In: ICML Workshop KRLM (2022)"},{"issue":"9","key":"1_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3560815","volume":"55","author":"P Liu","year":"2023","unstructured":"Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., Neubig, G.: Pre-train, prompt, and predict: a systematic survey of prompting methods in natural language processing. ACM Comput. Surv. 55(9), 1\u201335 (2023)","journal-title":"ACM Comput. Surv."},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Liu, V., Chilton, L.B.: Design guidelines for prompt engineering text-to-image generative models. In: CHI, pp. 1\u201323 (2022)","DOI":"10.1145\/3491102.3501825"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Liu, Y., Lapata, M.: Text summarization with pretrained encoders. In: EMNLP-IJCNLP, pp. 3730\u20133740. Association for Computational Linguistics (2019)","DOI":"10.18653\/v1\/D19-1387"},{"issue":"1","key":"1_CR11","first-page":"78","volume":"1","author":"J Mendling","year":"2015","unstructured":"Mendling, J., Leopold, H., Pittke, F.: 25 challenges of semantic process modeling. IJISEBC 1(1), 78\u201394 (2015)","journal-title":"IJISEBC"},{"key":"1_CR12","first-page":"11054","volume":"34","author":"E Perez","year":"2021","unstructured":"Perez, E., Kiela, D., Cho, K.: True few-shot learning with language models. NeurIPS 34, 11054\u201311070 (2021)","journal-title":"NeurIPS"},{"issue":"1","key":"1_CR13","first-page":"5485","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21(1), 5485\u20135551 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Schick, T., Sch\u00fctze, H.: Exploiting cloze-questions for few-shot text classification and natural language inference. In: EACL, pp. 255\u2013269 (2021)","DOI":"10.18653\/v1\/2021.eacl-main.20"},{"key":"1_CR15","doi-asserted-by":"crossref","unstructured":"Schick, T., Sch\u00fctze, H.: It\u2019s not just size that matters: small language models are also few-shot learners. In: NAACL-HLT, pp. 2339\u20132352 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.185"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Shin, T., Razeghi, Y., Logan IV, R.L., Wallace, E., Singh, S.: Autoprompt: eliciting knowledge from language models with automatically generated prompts. In: EMNLP, pp. 4222\u20134235 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.346"},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Sola, D., van der Aa, H., Meilicke, C., Stuckenschmidt, H.: Activity recommendation for business process modeling with pre-trained language models. In: ESWC. Springer, Cham (2023)","DOI":"10.1007\/978-3-031-33455-9_19"},{"key":"1_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1007\/978-3-030-79382-1_20","volume-title":"Advanced Information Systems Engineering","author":"D Sola","year":"2021","unstructured":"Sola, D., Meilicke, C., van der Aa, H., Stuckenschmidt, H.: A rule-based recommendation approach for business process modeling. In: La Rosa, M., Sadiq, S., Teniente, E. (eds.) CAiSE 2021. LNCS, vol. 12751, pp. 328\u2013343. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-79382-1_20"},{"key":"1_CR19","unstructured":"Vaswani, A., et al.: Attention is all you need. NeurIPS 30 (2017)"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Wang, Q., et al.: Learning deep transformer models for machine translation. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1810\u20131822 (2019)","DOI":"10.18653\/v1\/P19-1176"},{"key":"1_CR21","unstructured":"Wei, J., et al.: Chain of thought prompting elicits reasoning in large language models. arXiv preprint arXiv:2201.11903 (2022)"},{"key":"1_CR22","unstructured":"Zhao, Z., Wallace, E., Feng, S., Klein, D., Singh, S.: Calibrate before use: improving few-shot performance of language models. In: ICML, pp. 12697\u201312706 (2021)"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Zhou, X., Zhang, Y., Cui, L., Huang, D.: Evaluating commonsense in pre-trained language models. In: AAAI, vol. 34, pp. 9733\u20139740 (2020)","DOI":"10.1609\/aaai.v34i05.6523"}],"container-title":["Lecture Notes in Business Information Processing","Enterprise, Business-Process and Information Systems Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-34241-7_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,5]],"date-time":"2023-06-05T23:04:40Z","timestamp":1686006280000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-34241-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031342400","9783031342417"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-34241-7_1","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BPMDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Business Process Modeling, Development and Support","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zaragoza","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bpmds2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.bpmds.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"9","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}