{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T15:36:13Z","timestamp":1767108973320,"version":"3.40.3"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031475450"},{"type":"electronic","value":"9783031475467"}],"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\/978-3-031-47546-7_13","type":"book-chapter","created":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:03:15Z","timestamp":1698883395000},"page":"187-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Named Entity Recognition and Linking for Entity Extraction from Italian Civil Judgements"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4954-3837","authenticated-orcid":false,"given":"Riccardo","family":"Pozzi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0955-6721","authenticated-orcid":false,"given":"Riccardo","family":"Rubini","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8655-4446","authenticated-orcid":false,"given":"Christian","family":"Bernasconi","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1801-5118","authenticated-orcid":false,"given":"Matteo","family":"Palmonari","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Ayoola, T., Tyagi, S., Fisher, J., Christodoulopoulos, C., Pierleoni, A.: ReFinED: an efficient zero-shot-capable approach to end-to-end entity linking. In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track. Association for Computational Linguistics (2022)","DOI":"10.18653\/v1\/2022.naacl-industry.24"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Basile, P., Caputo, A., Gentile, A.L., Rizzo, G.: Overview of the EVALITA 2016 named entity recognition and linking in Italian tweets (NEEL-IT) task. In: of the Final Workshop, vol. 7 (2016)","DOI":"10.4000\/books.aaccademia.1935"},{"key":"13_CR3","doi-asserted-by":"crossref","unstructured":"Batini, C., Bellandi, V., Ceravolo, P., Moiraghi, F., Palmonari, M., Siccardi, S.: Semantic data integration for investigations: lessons learned and open challenges. In: 2021 IEEE International Conference on Smart Data Services (SMDS) (2021)","DOI":"10.1109\/SMDS53860.2021.00031"},{"key":"13_CR4","doi-asserted-by":"crossref","unstructured":"Cardellino, C., Teruel, M., Alemany, L.A., Villata, S.: A low-cost, high-coverage legal named entity recognizer, classifier and linker. In: Proceedings of the 16th Edition of the International Conference on Artificial Intelligence and Law. ICAIL 2017, Association for Computing Machinery (2017)","DOI":"10.1145\/3086512.3086514"},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"101842","DOI":"10.1016\/j.is.2021.101842","volume":"106","author":"S Castano","year":"2022","unstructured":"Castano, S., Falduti, M., Ferrara, A., Montanelli, S.: A knowledge-centered framework for exploration and retrieval of legal documents. Inf. Syst. 106, 101842 (2022)","journal-title":"Inf. Syst."},{"key":"13_CR6","doi-asserted-by":"publisher","first-page":"106779","DOI":"10.1016\/j.asoc.2020.106779","volume":"97","author":"R Catelli","year":"2020","unstructured":"Catelli, R., Gargiulo, F., Casola, V., De Pietro, G., Fujita, H., Esposito, M.: Crosslingual named entity recognition for clinical de-identification applied to a COVID-19 Italian data set. Appl. Soft Comput. 97, 106779 (2020)","journal-title":"Appl. Soft Comput."},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Aletras, N., Androutsopoulos, I.: LEGAL-BERT: the Muppets straight out of law school. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.261"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Daiber, J., Jakob, M., Hokamp, C., Mendes, P.N.: Improving efficiency and accuracy in multilingual entity extraction. In: Proceedings of the 9th International Conference on Semantic Systems. I-SEMANTICS 2013, Association for Computing Machinery (2013)","DOI":"10.1145\/2506182.2506198"},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1162\/tacl_a_00460","volume":"10","author":"N De Cao","year":"2022","unstructured":"De Cao, N., et al.: Multilingual autoregressive entity linking. Trans. Assoc. Comput. Linguist. 10, 274\u2013290 (2022)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"13_CR10","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics (2019)"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Elnaggar, A., Otto, R., Matthes, F.: Deep learning for named-entity linking with transfer learning for legal documents. In: Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference. AICCC 2018, Association for Computing Machinery (2018)","DOI":"10.1145\/3299819.3299846"},{"key":"13_CR12","unstructured":"He, Z., Liu, S., Li, M., Zhou, M., Zhang, L., Wang, H.: Learning entity representation for entity disambiguation. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Association for Computational Linguistics (2013)"},{"key":"13_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/978-3-031-33455-9_11","volume-title":"The Semantic Web, ESWC 2023","author":"N Heist","year":"2023","unstructured":"Heist, N., Paulheim, H.: NASTyLinker: NIL-aware scalable transformer-based entity linker. In: Pesquita, C., et al. (eds.) The Semantic Web, ESWC 2023. Lecture Notes in Computer Science, vol. 13870, pp. 174\u2013191. Springer, Switzerland (2023). https:\/\/doi.org\/10.1007\/978-3-031-33455-9_11"},{"key":"13_CR14","unstructured":"Humeau, S., Shuster, K., Lachaux, M.A., Weston, J.: Poly-encoders: Architectures and pre-training strategies for fast and accurate multi-sentence scoring. In: International Conference on Learning Representations (2019)"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Kassner, N., Petroni, F., Plekhanov, M., Riedel, S., Cancedda, N.: EDIN: an end-to-end benchmark and pipeline for unknown entity discovery and indexing. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.593"},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Keshavarz, H., et al.: Named entity recognition in long documents: an end-to-end case study in the legal domain. In: 2022 IEEE International Conference on Big Data (Big Data) (2022)","DOI":"10.1109\/BigData55660.2022.10020873"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Klie, J.C., Eckart de Castilho, R., Gurevych, I.: From zero to hero: human-in-the-loop entity linking in low resource domains. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.acl-main.624"},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Kolitsas, N., Ganea, O.E., Hofmann, T.: End-to-end neural entity linking. In: Proceedings of the 22nd Conference on Computational Natural Language Learning. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/K18-1050"},{"key":"13_CR19","unstructured":"Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the Eighteenth International Conference on Machine Learning. ICML 2001, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2001)"},{"key":"13_CR20","unstructured":"Licari, D., Comand\u00e8, G.: ITALIAN-LEGAL-BERT: a pre-trained transformer language model for Italian law. In: Companion Proceedings of the 23rd International Conference on Knowledge Engineering and Knowledge Management. CEUR Workshop Proceedings, vol. 3256. CEUR (2022)"},{"key":"13_CR21","unstructured":"McNamee, P., Dang, H.T.: Overview of the tac 2009 knowledge base population track. In: Second Text Analysis Conference (TAC 2009), vol. 2 (2009)"},{"key":"13_CR22","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.artint.2012.03.006","volume":"194","author":"J Nothman","year":"2013","unstructured":"Nothman, J., Ringland, N., Radford, W., Murphy, T., Curran, J.R.: Learning multilingual named entity recognition from Wikipedia. Artif. Intell. 194, 151\u2013175 (2013)","journal-title":"Artif. Intell."},{"key":"13_CR23","doi-asserted-by":"crossref","unstructured":"Aprosio, A.P., Moretti, G.: Tint 2.0: an all-inclusive suite for NLP in Italian. In: Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it, vol. 10 (2018)","DOI":"10.4000\/books.aaccademia.3571"},{"key":"13_CR24","doi-asserted-by":"crossref","unstructured":"Pozzi, R., Moiraghi, F., Lodi, F., Palmonari, M.: Evaluation of incremental entity extraction with background knowledge and entity linking. In: Proceedings of the 11th International Joint Conference on Knowledge Graphs. IJCKG 2022, Association for Computing Machinery (2023)","DOI":"10.1145\/3579051.3579063"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Procopio, L., Conia, S., Barba, E., Navigli, R.: Entity disambiguation with entity definitions. In: Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics (2023)","DOI":"10.18653\/v1\/2023.eacl-main.93"},{"key":"13_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1007\/978-3-030-00668-6_11","volume-title":"The Semantic Web \u2013 ISWC 2018","author":"H Rosales-M\u00e9ndez","year":"2018","unstructured":"Rosales-M\u00e9ndez, H., Hogan, A., Poblete, B.: VoxEL: a benchmark dataset for multilingual entity linking. In: Vrande\u010di\u0107, D., et al. (eds.) ISWC 2018. LNCS, vol. 11137, pp. 170\u2013186. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00668-6_11"},{"key":"13_CR27","unstructured":"Schweter, S.: Italian BERT and Electra models. Zenodo (2020)"},{"key":"13_CR28","doi-asserted-by":"publisher","first-page":"527","DOI":"10.3233\/SW-222986","volume":"13","author":"O Sevgili","year":"2020","unstructured":"Sevgili, O., Shelmanov, A., Arkhipov, M.V., Panchenko, A., Biemann, C.: Neural entity linking: a survey of models based on deep learning. Semant. Web 13, 527\u2013570 (2020)","journal-title":"Semant. Web"},{"key":"13_CR29","doi-asserted-by":"crossref","unstructured":"Tamper, M., Oksanen, A., Tuominen, J., Hietanen, A., Hyv\u00f6nen, E.: Automatic annotation service APPI: named entity linking in legal domain. In: The Semantic Web: ESWC 2020 Satellite Events. Springer International Publishing (2020)","DOI":"10.1007\/978-3-030-62327-2_36"},{"key":"13_CR30","doi-asserted-by":"crossref","unstructured":"Tedeschi, S., Navigli, R.: MultiNERD: a multilingual, multi-genre and fine-grained dataset for named entity recognition (and disambiguation). In: Findings of the Association for Computational Linguistics: NAACL 2022. Association for Computational Linguistics (2022)","DOI":"10.18653\/v1\/2022.findings-naacl.60"},{"key":"13_CR31","unstructured":"Sang, E.F.T.K., De Meulder, F.: Introduction to the CoNLL-2003 shared task: language-independent named entity recognition. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003 (2003)"},{"key":"13_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-7-92","volume":"7","author":"RTH Tsai","year":"2006","unstructured":"Tsai, R.T.H., et al.: Various criteria in the evaluation of biomedical named entity recognition. BMC Bioinform. 7, 1\u20138 (2006)","journal-title":"BMC Bioinform."},{"key":"13_CR33","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30. Curran Associates, Inc. (2017)"},{"key":"13_CR34","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Automated concatenation of embeddings for structured prediction. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) (2021)","DOI":"10.18653\/v1\/2021.acl-long.206"},{"key":"13_CR35","doi-asserted-by":"crossref","unstructured":"Wu, L., Petroni, F., Josifoski, M., Riedel, S., Zettlemoyer, L.: Scalable zero-shot entity linking with dense entity retrieval. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.519"},{"key":"13_CR36","doi-asserted-by":"crossref","unstructured":"Yamada, I., Shindo, H., Takeda, H., Takefuji, Y.: Joint learning of the embedding of words and entities for named entity disambiguation. In: Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning. Association for Computational Linguistics (2016)","DOI":"10.18653\/v1\/K16-1025"},{"key":"13_CR37","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1017\/S1351324922000304","volume":"29","author":"C \u00c7etinda\u011f","year":"2023","unstructured":"\u00c7etinda\u011f, C., Yaz\u0131c\u0131o\u011flu, B., Ko\u00e7, A.: Named-entity recognition in Turkish legal texts. Nat. Lang. Eng. 29, 615\u2013642 (2023)","journal-title":"Nat. Lang. Eng."}],"container-title":["Lecture Notes in Computer Science","AIxIA 2023 \u2013 Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-47546-7_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:12:38Z","timestamp":1698883958000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-47546-7_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031475450","9783031475467"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-47546-7_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"2 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIxIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of the Italian Association for Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rome","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiia2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.aixia2023.cnr.it\/","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.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"53","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":"33","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":"0","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":"62% - 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)"}},{"value":"20 external reviewers.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}