{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:23:22Z","timestamp":1783095802257,"version":"3.54.6"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62422303"],"award-info":[{"award-number":["62422303"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373035"],"award-info":[{"award-number":["62373035"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.engappai.2026.115112","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T11:22:19Z","timestamp":1778757739000},"page":"115112","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["A self-feedback zero-shot information extraction framework via multi-round chain of thought"],"prefix":"10.1016","volume":"178","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3209-725X","authenticated-orcid":false,"given":"Yongming","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjie","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"Geng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.115112_bib1","doi-asserted-by":"crossref","first-page":"8371","DOI":"10.1007\/s00521-024-09532-1","article-title":"Application of BiLSTM-CRF model with different embeddings for product name extraction in unstructured Turkish text","volume":"36","author":"Arslan","year":"2024","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121264","article-title":"Dictionary-based multi-instance learning method with universum information","volume":"682","author":"Cao","year":"2024","journal-title":"Inf. Sci."},{"key":"10.1016\/j.engappai.2026.115112_bib3","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111365","article-title":"A multi-head attention-based bidirectional gated recurrent unit and multilayer perceptron for relation extraction model","volume":"158","author":"Chen","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.115112_bib4","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.126120","article-title":"Using GPT-4 to guide causal machine learning","volume":"268","author":"Constantinou","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib5","series-title":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","first-page":"1040","article-title":"A lexicon-based graph neural network for Chinese NER","author":"Gui","year":"2019"},{"key":"10.1016\/j.engappai.2026.115112_bib6","series-title":"Findings of the Association for Computational Linguistics: NAACL 2024","first-page":"3628","article-title":"FIRE: a dataset for financial relation extraction","author":"Hamad","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib7","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.neunet.2023.11.062","article-title":"Document-level relation extraction with relation correlations","volume":"171","author":"Han","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.engappai.2026.115112_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118927","article-title":"Virtual prompt pre-training for prototype-based few-shot relation extraction","volume":"213","author":"He","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125914","article-title":"RAG-based explainable prediction of road users behaviors for automated driving using knowledge graphs and LLMs","volume":"265","author":"Hussien","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib10","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/MCG.2025.3624666","article-title":"Visualizing the chain of thought in large language models","volume":"46","author":"Ilgen","year":"2026","journal-title":"IEEE Comput. Graph. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib11","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1109\/CITSC64390.2025.00152","article-title":"Joint entity and relation extraction form medical information based on potential relation and CasRel","author":"Li","year":"2025","journal-title":"2025 Asia-Europe Conf. Cybersecurity, Internet Things Soft Comput. (CITSC)"},{"key":"10.1016\/j.engappai.2026.115112_bib12","series-title":"Findings of the Association for Computational Linguistics: EMNLP 2024","first-page":"13147","article-title":"Unleashing the power of LLMs in zero-shot relation extraction via self-prompting","author":"Liu","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib13","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110992","article-title":"Harnessing high-quality pseudo-labels for robust few-shot nested named entity recognition","volume":"156","author":"Ming","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.115112_bib14","doi-asserted-by":"crossref","DOI":"10.2196\/60095","article-title":"Developing an ICD-10 coding assistant: pilot study using RoBERTa and GPT-4 for term extraction and description-based code selection","volume":"9","author":"Puts","year":"2025","journal-title":"JMIR Form Res."},{"key":"10.1016\/j.engappai.2026.115112_bib15","doi-asserted-by":"crossref","DOI":"10.1007\/s10791-025-09859-w","article-title":"Information retrieval framework using knowledge graph embeddings and uncertainty modelling using probabilistic soft logic","volume":"29","author":"Rawat","year":"2026","journal-title":"Discov. Comput."},{"key":"10.1016\/j.engappai.2026.115112_bib16","series-title":"Studies in Health Technology and Informatics","doi-asserted-by":"crossref","first-page":"3161861","DOI":"10.3233\/SHTI240794","article-title":"Leveraging rule-based NLP to translate textual reports as structured inputs automatically processed by a clinical decision support system","author":"Redjdal","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib17","series-title":"2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)","first-page":"1","article-title":"Enhancing named entity recognition through neural architectures","author":"Shakir","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib18","doi-asserted-by":"crossref","DOI":"10.51256\/ANJ062414","article-title":"FAQs: AI and prompt engineering: the future of nursing education and professional development","volume":"19","author":"Shepherd","year":"2024","journal-title":"Am. Nurse J."},{"key":"10.1016\/j.engappai.2026.115112_bib19","series-title":"2024 IEEE 7th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","first-page":"301","article-title":"Research on entity relation extraction of Chinese medical texts based on pre-training model","author":"Shuang","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib20","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2026.114596","article-title":"Multi-stage reasoning framework for biomedical document-level relation extraction with dynamic memory mechanism","volume":"174","author":"Sun","year":"2026","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.115112_bib21","first-page":"121","article-title":"The joint entity\u2013relation extraction model based on hierarchical architecture for Chinese programming knowledge with complex semantics","volume":"22","author":"Tian","year":"2026","journal-title":"Int. J. Web Inf. Syst."},{"key":"10.1016\/j.engappai.2026.115112_bib22","doi-asserted-by":"crossref","DOI":"10.1088\/1742-6596\/2560\/1\/012044","article-title":"Named entity recognition of electronic medical records based on BERT-BiLSTM-Biaffine model","volume":"2560","author":"Wang","year":"2023","journal-title":"J. Phys. Conf."},{"key":"10.1016\/j.engappai.2026.115112_bib23","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.121000","article-title":"Selective privacy-preserving framework for LLMs fine-tuning","volume":"678","author":"Wang","year":"2024","journal-title":"Inf. Sci."},{"key":"10.1016\/j.engappai.2026.115112_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2025.136377","article-title":"Production prediction and energy saving of complex industrial processes using multiscale variable dynamic interaction information extraction network integrating regressor","volume":"326","author":"Wang","year":"2025","journal-title":"Energy"},{"key":"10.1016\/j.engappai.2026.115112_bib25","series-title":"ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT","author":"Wei","year":"2024"},{"key":"10.1016\/j.engappai.2026.115112_bib26","series-title":"Proceedings of the Fourth Workshop on Simple and Efficient Natural Language Processing (Sustainlp), Toronto, Canada (Hybrid)","first-page":"190","article-title":"How to unleash the power of LLMs for few-shot relation extraction?","author":"Xu","year":"2023"},{"key":"10.1016\/j.engappai.2026.115112_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126951","article-title":"Diff-ZsVQA: zero-shot visual question answering with frozen LLMs using diffusion model","volume":"275","author":"Xu","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2026.115112_bib28","first-page":"17675","article-title":"A benchmark for multi-context visual grounding in the era of MLLMs","author":"Xu","year":"2025","journal-title":"Proceed. IEEE\/CVF Int. Conf. Comput. Vision (ICCV)"},{"key":"10.1016\/j.engappai.2026.115112_bib29","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.107117","article-title":"A discrete convolutional network for entity relation extraction","volume":"184","author":"Yang","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.engappai.2026.115112_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129741","article-title":"Rehearsal-free continual few-shot relation extraction via contrastive weighted prompts","volume":"633","author":"Yang","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2026.115112_bib31","doi-asserted-by":"crossref","first-page":"7943","DOI":"10.1109\/TIP.2025.3635048","article-title":"Text-guided semantic alignment network with spatial-frequency interaction for infrared-visible image fusion under extreme illumination","volume":"34","author":"Yue","year":"2025","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"10.1016\/j.engappai.2026.115112_bib32","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1109\/TAI.2025.3596925","article-title":"Prompt-aware adapter: learning adaptive visual tokens for multimodal large language models","volume":"7","author":"Zhang","year":"2026","journal-title":"IEEE Trans. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.115112_bib33","first-page":"14","article-title":"Named entity recognition for Chinese texts on marine coral reef ecosystems based on the BERT-BiGRU-Att-CRF model","author":"Zhao","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.115112_bib34","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2025.122570","article-title":"DecKG: decentralized collaborative learning with knowledge graph enhancement for POI recommendation","volume":"721","author":"Zheng","year":"2025","journal-title":"Inf. Sci."},{"key":"10.1016\/j.engappai.2026.115112_bib35","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1093\/jamia\/ocae147","article-title":"LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction","volume":"31","author":"Zhou","year":"2024","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.engappai.2026.115112_bib36","first-page":"15169","article-title":"Dropping experts, recombining neurons: retraining-free pruning for sparse mixture-of-experts LLMs","author":"Zhou","year":"2025","journal-title":"Find. Assoc. Comput. Linguist.: EMNLP"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626013953?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626013953?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T15:53:52Z","timestamp":1783094032000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626013953"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":36,"alternative-id":["S0952197626013953"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115112","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A self-feedback zero-shot information extraction framework via multi-round chain of thought","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.115112","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115112"}}