{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T14:43:09Z","timestamp":1743086589688,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031702419"},{"type":"electronic","value":"9783031702426"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-70242-6_16","type":"book-chapter","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T10:03:06Z","timestamp":1726740186000},"page":"161-171","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatic Question Answering for\u00a0the\u00a0Linguistic Domain \u2013 An Evaluation of\u00a0LLM Knowledge Base Extension with\u00a0RAG"],"prefix":"10.1007","author":[{"given":"Christian","family":"Lang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6375-530X","authenticated-orcid":false,"given":"Roman","family":"Schneider","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7586-0617","authenticated-orcid":false,"given":"Ngoc Duyen Tanja","family":"Tu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"issue":"4","key":"16_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-022-01783-5","volume":"65","author":"H Abdel-Nabi","year":"2023","unstructured":"Abdel-Nabi, H., Awajan, A., Ali, M.: Deep learning-based question answering: a survey. Knowl. Inf. Syst. 65(4), 1\u201387 (2023)","journal-title":"Knowl. Inf. Syst."},{"key":"16_CR2","doi-asserted-by":"publisher","unstructured":"Artstein, R.: Inter-annotator agreement. In: Pustejovsky, J., Ide, N. (eds.) Handbook of Linguistic Annotation, vol. 1, pp. 297\u2013313. Springer, Dordrecht (2017). https:\/\/doi.org\/10.1007\/978-94-024-0881-2_11","DOI":"10.1007\/978-94-024-0881-2_11"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Dai, D., Sun, Y., Dong, L., Hao, Y., Sui, Z., Wei, F.: Why can GPT learn in-context? Language models secretly perform gradient descent as meta optimizers. In: Rogers, A., Boyd-Graber, J., Okazaki, N. (eds.) Findings of the Association for Computational Linguistics: ACL 2023, pp. 4005\u20134019 (2023)","DOI":"10.18653\/v1\/2023.findings-acl.247"},{"key":"16_CR4","unstructured":"Denny, P., Sarsa, S., Hellas, A., Leinonen, J.: Robosourcing Educational Resources \u2013 Leveraging Large Language Models for Learnersourcing (2022)"},{"key":"16_CR5","unstructured":"Dettmers, T., Pagnoni, A., Holtzman, A., Zettlemoyer, L.: QLoRA: efficient finetuning of quantized LLMs (2023)"},{"issue":"4","key":"16_CR6","doi-asserted-by":"publisher","first-page":"4124","DOI":"10.1007\/s10489-022-03732-9","volume":"53","author":"R Etezadi","year":"2022","unstructured":"Etezadi, R., Shamsfard, M.: The state of the art in open domain complex question answering: a survey. Appl. Intell. 53(4), 4124\u20134144 (2022)","journal-title":"Appl. Intell."},{"issue":"5","key":"16_CR7","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1037\/h0031619","volume":"76","author":"JL Fleiss","year":"1971","unstructured":"Fleiss, J.L.: Measuring nominal scale agreement among many raters. Psychol. Bull. 76(5), 378\u2013382 (1971)","journal-title":"Psychol. Bull."},{"key":"16_CR8","unstructured":"Houlsby, N., et al.: Parameter-efficient transfer learning for NLP (2019). arXiv Version Number: 2"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Kamalloo, E., Dziri, N., Clarke, C., Rafiei, D.: Evaluating open-domain question answering in the era of large language models. In: Rogers, A., Boyd-Graber, J., Okazaki, N. (eds.) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, vol. 1: Long Papers, pp. 5591\u20135606. Association for Computational Linguistics, Toronto (2023)","DOI":"10.18653\/v1\/2023.acl-long.307"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Kwiatkowski, T., et al.: Natural questions: a benchmark for question answering research. Trans. Assoc. Comput. Linguist. 7, 453\u2013466 (2019)","DOI":"10.1162\/tacl_a_00276"},{"key":"16_CR11","unstructured":"Lang, C., Tu, N.D.T., Zeidler, L.: Making non-normalized content retrievable \u2013 a tagging pipeline for a corpus of expert\u2013Layperson texts. In: Proceedings of the 4th Conference on Language, Data and Knowledge, pp. 239\u2013244. NOVA CLUNL, Portugal (2023)"},{"key":"16_CR12","unstructured":"Lewis, P., et al.: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (2020). arXiv Version Number: 4"},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Li, X.L., Kuncoro, A., Hoffmann, J., de\u00a0Masson\u00a0d\u2019Autume, C., Blunsom, P., Nematzadeh, A.: A systematic investigation of commonsense knowledge in large language models. In: Goldberg, Y., Kozareva, Z., Zhang, Y. (eds.) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 11838\u201311855. Association for Computational Linguistics, Abu Dhabi (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.812"},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Liu, X., et al.: P-tuning: prompt tuning can be comparable to fine-tuning across scales and tasks. In: Muresan, S., Nakov, P., Villavicencio, A. (eds.) Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, vol. 2: Short Papers, pp. 61\u201368. Association for Computational Linguistics, Dublin (2022)","DOI":"10.18653\/v1\/2022.acl-short.8"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"MacNeil, S., et al.: Automatically generating CS learning materials with large language models. In: SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education, vol. 2. p.\u00a01176. Association for Computing Machinery, New York (2023)","DOI":"10.1145\/3545947.3569630"},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Mosbach, M., Pimentel, T., Ravfogel, S., Klakow, D., Elazar, Y.: Few-shot fine-tuning vs. in-context learning: a fair comparison and evaluation. In: Rogers, A., Boyd-Graber, J., Okazaki, N. (eds.) Findings of the Association for Computational Linguistics: ACL 2023, pp. 12284\u201312314. Association for Computational Linguistics, Toronto (2023)","DOI":"10.18653\/v1\/2023.findings-acl.779"},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Rocca, R., de\u00a0la Vega, A.: Evaluating the role of non-lexical markers in GPT-2\u2019s language modeling behavior. In: Deutsch, D., Udomcharoenchaikit, C., Opitz, J., Gao, Y., Fomicheva, M., Eger, S. (eds.) Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems, pp. 96\u2013102. Association for Computational Linguistics (2022)","DOI":"10.18653\/v1\/2022.eval4nlp-1.10"},{"issue":"10","key":"16_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3560260","volume":"55","author":"A Rogers","year":"2023","unstructured":"Rogers, A., Gardner, M., Augenstein, I.: QA Dataset explosion: a taxonomy of NLP resources for question answering and reading comprehension. ACM Comput. Surv. 55(10), 1\u201345 (2023)","journal-title":"ACM Comput. Surv."},{"issue":"2","key":"16_CR19","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1515\/zgl-2022-2060","volume":"50","author":"R Schneider","year":"2022","unstructured":"Schneider, R., Lang, C.: Das grammatische Informationssystem grammis \u2013 Inhalte, Anwendungen und Perspektiven. Zeitschrift f\u00fcr germanistische Linguistik 50(2), 407\u2013427 (2022)","journal-title":"Zeitschrift f\u00fcr germanistische Linguistik"},{"key":"16_CR20","doi-asserted-by":"publisher","first-page":"3784","DOI":"10.18653\/v1\/2021.findings-emnlp.320","volume-title":"Findings of the Association for Computational Linguistics: EMNLP 2021","author":"K Shuster","year":"2021","unstructured":"Shuster, K., Poff, S., Chen, M., Kiela, D., Weston, J.: Retrieval augmentation reduces Hallucination in conversation. In: Moens, M.F., Huang, X., Specia, L., Wen-tau Yih, S. (eds.) Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 3784\u20133803. Association for Computational Linguistics, Punta Cana (2021)"},{"key":"16_CR21","doi-asserted-by":"crossref","unstructured":"Su, H., et al.: One embedder, any task: instruction-finetuned text embeddings. In: Rogers, A., Boyd-Graber, J., Okazaki, N. (eds.) Findings of the Association for Computational Linguistics: ACL 2023, pp. 1102\u20131121. Association for Computational Linguistics, Toronto (2023)","DOI":"10.18653\/v1\/2023.findings-acl.71"},{"key":"16_CR22","unstructured":"Touvron, H., et al.: Llama 2: open foundation and fine-tuned chat models (2023)"},{"key":"16_CR23","volume-title":"\u201cHallo ChatGPT, ist das Komma in folgendem Satz richtig?\u201d \u2014 K\u00f6nnen leistungsstarke Chatbots traditionelle Sprachberatung ersetzen?","author":"NDT Tu","year":"2023","unstructured":"Tu, N.D.T.: \u201cHallo ChatGPT, ist das Komma in folgendem Satz richtig?\u2019\u2019 \u2014 K\u00f6nnen leistungsstarke Chatbots traditionelle Sprachberatung ersetzen? Staats- und Universit\u00e4tsbibliothek G\u00f6ttingen, DHd-Blog \u2013 Digital Humanities im deutschsprachigen Raum (2023)"},{"issue":"5","key":"16_CR24","first-page":"360","volume":"37","author":"AJ Viera","year":"2005","unstructured":"Viera, A.J., Garrett, J.M.: Understanding interobserver agreement: the Kappa statistic. Fam. Med. 37(5), 360\u2013363 (2005)","journal-title":"Fam. Med."},{"key":"16_CR25","unstructured":"Zhao, W.X., et al.: A Survey of Large Language Models (2023)"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70242-6_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T12:19:27Z","timestamp":1740399567000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70242-6_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031702419","9783031702426"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70242-6_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"20 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Turin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/nldb2024.di.unito.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}