{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T03:21:47Z","timestamp":1769829707602,"version":"3.49.0"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T00:00:00Z","timestamp":1670371200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T00:00:00Z","timestamp":1670371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003524","name":"Ministry of Business, Innovation and Employment","doi-asserted-by":"publisher","award":["PROP-70215-CNZSDS-MAU"],"award-info":[{"award-number":["PROP-70215-CNZSDS-MAU"]}],"id":[{"id":"10.13039\/501100003524","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1007\/s10115-022-01793-3","type":"journal-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T13:04:20Z","timestamp":1670418260000},"page":"1221-1242","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Exploiting anonymous entity mentions for named entity linking"],"prefix":"10.1007","volume":"65","author":[{"given":"Feng","family":"Hou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruili","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"See-Kiong","family":"Ng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Witbrock","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangyi","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyun","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,7]]},"reference":[{"key":"1793_CR1","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1162\/tacl\\_a_00034","volume":"6","author":"S Arora","year":"2018","unstructured":"Arora S, Li Y, Liang Y, Ma T, Risteski A (2018) Linear algebraic structure of word senses, with applications to polysemy. Trans Assoc Comput Linguist 6:483\u2013495. https:\/\/doi.org\/10.1162\/tacl_a_00034","journal-title":"Trans Assoc Comput Linguist"},{"key":"1793_CR2","doi-asserted-by":"publisher","unstructured":"Bhowmik R, de\u00a0Melo G (2018) Generating fine-grained open vocabulary entity type descriptions. In: Proceedings of the 56th annual meeting of the association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/P18-1081","DOI":"10.18653\/v1\/P18-1081"},{"key":"1793_CR3","doi-asserted-by":"publisher","unstructured":"Chen S, Wang J, Jiang F, Lin CY (2020) Improving entity linking by modeling latent entity type information. In: Proceedings of the 34th AAAI conference on artificial intelligence, pp 7529\u20137537 . https:\/\/doi.org\/10.1609\/aaai.v34i05.6251","DOI":"10.1609\/aaai.v34i05.6251"},{"key":"1793_CR4","unstructured":"Cheng X, Roth D (2013) Relational inference for wikification. In: Proceedings of the 2013 conference on empirical methods in natural language processing, pp 1787\u20131796. https:\/\/www.aclweb.org\/anthology\/D13-1184"},{"key":"1793_CR5","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1162\/tacl\\_a\\_00129","volume":"3","author":"A Chisholm","year":"2015","unstructured":"Chisholm A, Hachey B (2015) Entity disambiguation with web links. Trans Assoc Comput Linguist 3:145\u2013156. https:\/\/doi.org\/10.1162\/tacl_a_00129","journal-title":"Trans Assoc Comput Linguist"},{"key":"1793_CR6","doi-asserted-by":"publisher","unstructured":"Choi E, Levy Omer, Choi Yejin, Zettlemoyer Luke (2018) Ultra-fine entity typing. In: Proceedings of the 56th annual meeting of the association for computational linguistics. Assoc Comput Linguist, pp 87\u201396. https:\/\/doi.org\/10.18653\/v1\/P18-1009","DOI":"10.18653\/v1\/P18-1009"},{"issue":"10","key":"1793_CR7","doi-asserted-by":"publisher","first-page":"2741","DOI":"10.1007\/s10115-021-01609-w","volume":"63","author":"H Cui","year":"2021","unstructured":"Cui H, Peng T, Feng L, Bao T, Liu L (2021) Simple question answering over knowledge graph enhanced by question pattern classification. Knowl Inf Syst 63(10):2741\u20132761","journal-title":"Knowl Inf Syst"},{"key":"1793_CR8","doi-asserted-by":"crossref","unstructured":"Durrett G, Klein D (2014) A joint model for entity analysis: coreference, typing, and linking. Trans Assoc Comput Linguist","DOI":"10.1162\/tacl_a_00197"},{"issue":"3","key":"1793_CR9","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/s10115-018-1190-1","volume":"58","author":"F Ensan","year":"2019","unstructured":"Ensan F, Du W (2019) Ad hoc retrieval via entity linking and semantic similarity. Knowl Inf Syst 58(3):551\u2013583","journal-title":"Knowl Inf Syst"},{"key":"1793_CR10","unstructured":"Gabrilovich Evgeniy, Ringgaard Michael, Subramanya Amarnag (2013) FACC1: Freebase annotation of ClueWeb corpora, version 1 (release date 2013-06-26, format version 1, correction level 0)"},{"key":"1793_CR11","doi-asserted-by":"publisher","unstructured":"Fang W, Zhang J, Wang D, Chen Z, Li M (2016) Entity disambiguation by knowledge and text jointly embedding. In: Proceedings of The 20th SIGNLL conference on computational natural language learning, pp 260\u2013269. Association for computational linguistics, Berlin, Germany. https:\/\/doi.org\/10.18653\/v1\/K16-1026.https:\/\/www.aclweb.org\/anthology\/K16-1026","DOI":"10.18653\/v1\/K16-1026."},{"key":"1793_CR12","doi-asserted-by":"crossref","unstructured":"Ganea OE, Ganea M, Lucchi A, Eickhof, C, Hofmann T (2016) Probabilistic bag-of-hyperlinks model for entity linking. In: Proceedings of the 25th international conference on world wide web, pp 927\u2013938. International World Wide Web Conferences Steering Committee","DOI":"10.1145\/2872427.2882988"},{"key":"1793_CR13","doi-asserted-by":"publisher","unstructured":"Ganea OE, Hofmann T (2017) Deep joint entity disambiguation with local neural attention. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 2619\u20132629. Association for Computational Linguistics, Copenhagen, Denmark . https:\/\/doi.org\/10.18653\/v1\/D17-1277.https:\/\/www.aclweb.org\/anthology\/D17-1277","DOI":"10.18653\/v1\/D17-1277."},{"key":"1793_CR14","unstructured":"Gillick D, Lazic N, Ganchev K, Kirchner J, Huynh D (2014) Contextdependent fine-grained entity type tagging. arXiv preprint arXiv:1412.1820"},{"key":"1793_CR15","doi-asserted-by":"publisher","unstructured":"Globerson A, Lazic N, Chakrabarti S, Subramanya A, Ringaard M, Pereira F (2016) Collective entity resolution with multi-focal attention. In: Proceedings of the 54th annual meeting of the association for computational linguistics (vol 1: Long Papers), pp 621\u2013631. https:\/\/doi.org\/10.18653\/v1\/P16-1059.https:\/\/www.aclweb.org\/anthology\/P16-1059","DOI":"10.18653\/v1\/P16-1059."},{"issue":"4","key":"1793_CR16","doi-asserted-by":"publisher","first-page":"459","DOI":"10.3233\/SW-170273","volume":"9","author":"Z Guo","year":"2018","unstructured":"Guo Z, Barbosa D (2018) Robust named entity disambiguation with random walks. Sem Web (Preprint) 9(4):459\u2013479","journal-title":"Sem Web (Preprint)"},{"key":"1793_CR17","doi-asserted-by":"publisher","unstructured":"Gupta N, Singh S, Roth D (2017) Entity linking via joint encoding of types, descriptions, and context. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 2681\u20132690. Association for Computational Linguistics, Copenhagen, Denmark . https:\/\/doi.org\/10.18653\/v1\/D17-1284.https:\/\/www.aclweb.org\/anthology\/D17-1284","DOI":"10.18653\/v1\/D17-1284."},{"key":"1793_CR18","unstructured":"Hoffart J, Yosef MA, Bordino I, F\u00fcrstenau H, Pinkal M, Spaniol M, Taneva B, Thater S, Weikum G (2011) Robust disambiguation of named entities in text. In: Proceedings of the 2011 conference on empirical methods in natural language processing, pp 782\u2013792. Association for Computational Linguistics . http:\/\/www.aclweb.org\/anthology\/D11-1072"},{"key":"1793_CR19","unstructured":"Hoffmann R, Zhang C, Ling X, Zettlemoyer L, Weld DS (2011) Knowledge-based weak supervision for information extraction of overlapping relations. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, pp 541\u2013550. Association for Computational Linguistics, Portland, Oregon, USA. https:\/\/www.aclweb.org\/anthology\/P11-1055"},{"key":"1793_CR20","doi-asserted-by":"publisher","unstructured":"Hou F, Wang R, He J, Zhou Y (2020) Improving entity linking through semantic reinforced entity embeddings. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 6843\u20136848. Association for Computational Linguistics, Online . https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.612.https:\/\/www.aclweb.org\/anthology\/2020.acl-main.612","DOI":"10.18653\/v1\/2020.acl-main.612."},{"issue":"4","key":"1793_CR21","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1007\/s10115-021-01549-5","volume":"63","author":"F Hou","year":"2021","unstructured":"Hou F, Wang R, Zhou Y (2021) Transfer learning for fine-grained entity typing. Knowl Inf Syst 63(4):845\u2013866","journal-title":"Knowl Inf Syst"},{"key":"1793_CR22","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"issue":"3","key":"1793_CR23","doi-asserted-by":"publisher","first-page":"1547","DOI":"10.1007\/s10115-018-1246-2","volume":"61","author":"P Kouki","year":"2019","unstructured":"Kouki P, Pujara J, Marcum C, Koehly L, Getoor L (2019) Collective entity resolution in multi-relational familial networks. Knowl Inf Syst 61(3):1547\u20131581","journal-title":"Knowl Inf Syst"},{"key":"1793_CR24","doi-asserted-by":"publisher","unstructured":"Lazic N, Subramanya A, Ringgaard M, Pereira F (2015) Plato: a selective context model for entity resolution. Trans Assoc Comput Linguist 3:503\u2013515. https:\/\/doi.org\/10.1162\/tacl_a_00154https:\/\/www.aclweb.org\/anthology\/Q15-1036","DOI":"10.1162\/tacl_a_00154"},{"key":"1793_CR25","doi-asserted-by":"publisher","unstructured":"Le P, Titov I (2018) Improving entity linking by modeling latent relations between mentions. In: Proceedings of the 56th annual meeting of the association for computational linguistics (vol 1: Long Papers), pp 1595\u20131604. Association for Computational Linguistics, Melbourne, Australia . https:\/\/doi.org\/10.18653\/v1\/P18-1148.https:\/\/www.aclweb.org\/anthology\/P18-1148","DOI":"10.18653\/v1\/P18-1148."},{"key":"1793_CR26","doi-asserted-by":"crossref","unstructured":"Le P, Titov I (2019) Boosting entity linking performance by leveraging unlabeled documents. In: Proceedings of the 57th annual meeting of the association for computational linguistics, pp 1935\u20131945. Association for Computational Linguistics, Florence, Italy. https:\/\/www.aclweb.org\/anthology\/P19-1187","DOI":"10.18653\/v1\/P19-1187"},{"key":"1793_CR27","unstructured":"Ling X, Weld DS (2012) Fine-grained entity recognition. In: Proceedings of association for the advancement of artificial intelligence"},{"issue":"3","key":"1793_CR28","doi-asserted-by":"publisher","first-page":"1611","DOI":"10.1007\/s10115-018-1273-z","volume":"60","author":"M Liu","year":"2019","unstructured":"Liu M, Zhao Y, Qin B, Liu T (2019) Collective entity linking: a random walk-based perspective. Knowl Inf Syst 60(3):1611\u20131643","journal-title":"Knowl Inf Syst"},{"key":"1793_CR29","unstructured":"Mikolov T, Sutskever Ilya, Chen Kai, Corrado Greg, Dean Jeffrey (2013) Distributed representations of words and phrases and their compositionality. In: Adv Neural Inf Process Syst, pp 3111\u20133119"},{"key":"1793_CR30","doi-asserted-by":"crossref","unstructured":"Milne D, Witten IH (2008) Learning to link with wikipedia. In: Proceedings of the 17th ACM conference on information and knowledge management, pp 509\u2013518. ACM","DOI":"10.1145\/1458082.1458150"},{"key":"1793_CR31","unstructured":"Mu J, Bhat S, Viswanath P (2017) Geometry of polysemy. In: Proceedings of the 5th international conference on learning representations"},{"key":"1793_CR32","unstructured":"Murphy KP (2012) Machine learning: a probabilistic perspective. MIT press"},{"key":"1793_CR33","doi-asserted-by":"publisher","unstructured":"Pennington J, Socher R, Manning C (2014) GloVe: Global vectors for word representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp 1532\u20131543. Association for Computational Linguistics, Doha, Qatar. https:\/\/doi.org\/10.3115\/v1\/D14-1162.https:\/\/www.aclweb.org\/anthology\/D14-1162","DOI":"10.3115\/v1\/D14-1162."},{"issue":"7","key":"1793_CR34","doi-asserted-by":"publisher","first-page":"1383","DOI":"10.1109\/TKDE.2018.2857493","volume":"31","author":"MC Phan","year":"2019","unstructured":"Phan MC, Sun A, Tay Y, Han J, Li C (2019) Pair-linking for collective entity disambiguation: two could be better than all. IEEE Trans Knowl Data Eng 31(7):1383\u20131396","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1793_CR35","unstructured":"Ratinov L, Roth D, Downey D, Anderson M (2011) Local and global algorithms for disambiguation to wikipedia. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, vol 1, pp 1375\u20131384. Association for Computational Linguistics. https:\/\/www.aclweb.org\/anthology\/P11-1138"},{"issue":"2","key":"1793_CR36","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/TKDE.2014.2327028","volume":"27","author":"W Shen","year":"2015","unstructured":"Shen W, Wang J, Han J (2015) Entity linking with a knowledge base: issues, techniques, and solutions. IEEE Trans Knowl Data Eng 27(2):443\u2013460","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1793_CR37","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1613\/jair.5601","volume":"61","author":"Y Yaghoobzadeh","year":"2018","unstructured":"Yaghoobzadeh Y, Adel H, Schutze H (2018) Corpus-level fine-grained entity typing. J Artif Intell Res 61:835\u2013862","journal-title":"J Artif Intell Res"},{"key":"1793_CR38","doi-asserted-by":"crossref","unstructured":"Yaghoobzadeh Y, Kann K, Hazen TJ, Agirre E, Sch\u00fctze H (2019) Probing for semantic classes: Diagnosing the meaning content of word embeddings. In: Proceedings of the 57th Annual meeting of the association for computational linguistics, pp 5740\u20135753. Association for Computational Linguistics, Florence, Italy. https:\/\/www.aclweb.org\/anthology\/P19-1574","DOI":"10.18653\/v1\/P19-1574"},{"key":"1793_CR39","doi-asserted-by":"publisher","unstructured":"Yamada I, Shindo H, Takeda H, Takefuji Y (2016) 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, pp 250\u2013259. Association for Computational Linguistics, Berlin, Germany. https:\/\/doi.org\/10.18653\/v1\/K16-1025.https:\/\/www.aclweb.org\/anthology\/K16-1025","DOI":"10.18653\/v1\/K16-1025."},{"key":"1793_CR40","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1162\/tacl_a_00069","volume":"5","author":"I Yamada","year":"2017","unstructured":"Yamada I, Shindo H, Takeda H, Takefuji Y (2017) Learning distributed representations of texts and entities from knowledge base. Trans Assoc Comput Linguist 5:397\u2013411","journal-title":"Trans Assoc Comput Linguist"},{"key":"1793_CR41","unstructured":"Yamada I, Washio K, Shindo H, Matsumoto Y (2020) Global entity disambiguation with pretrained contextualized embeddings of words and entities. arXiv preprint arXiv:1909.00426"},{"key":"1793_CR42","doi-asserted-by":"publisher","unstructured":"Yang X, Gu X, Lin S, Tang S, Zhuang Y, Wu F, Chen Z, Hu G, Ren X (2019) Learning dynamic context augmentation for global entity linking. In: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), pp 271\u2013281. Association for Computational Linguistics, Hong Kong, China. https:\/\/doi.org\/10.18653\/v1\/D19-1026.https:\/\/www.aclweb.org\/anthology\/D19-1026","DOI":"10.18653\/v1\/D19-1026."},{"key":"1793_CR43","doi-asserted-by":"publisher","unstructured":"Yih Wt, Chang MW, He X, Gao J (2015) Semantic parsing via staged query graph generation: Question answering with knowledge base. In: Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing (vol 1: Long Papers), pp 1321\u20131331. Association for Computational Linguistics, Beijing, China. https:\/\/doi.org\/10.3115\/v1\/P15-1128.https:\/\/www.aclweb.org\/anthology\/P15-1128","DOI":"10.3115\/v1\/P15-1128."},{"key":"1793_CR44","doi-asserted-by":"crossref","unstructured":"Zhou X, Miao Y, Wang W, Qin J (2020) A recurrent model for collective entity linking with adaptive features. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence, vol.\u00a034, pp. 329\u2013336","DOI":"10.1609\/aaai.v34i01.5367"},{"key":"1793_CR45","doi-asserted-by":"crossref","unstructured":"Zwicklbauer S, Seifert C, Granitzer M (2016) Robust and collective entity disambiguation through semantic embeddings. In: Proceedings of the 39th international ACM SIGIR conference, pp 425\u2013434. ACM","DOI":"10.1145\/2911451.2911535"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01793-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-022-01793-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-022-01793-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T07:15:32Z","timestamp":1676618132000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-022-01793-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,7]]},"references-count":45,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,3]]}},"alternative-id":["1793"],"URL":"https:\/\/doi.org\/10.1007\/s10115-022-01793-3","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,7]]},"assertion":[{"value":"30 January 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 October 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 November 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 December 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}