{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T12:24:03Z","timestamp":1764937443723,"version":"3.41.0"},"reference-count":97,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T00:00:00Z","timestamp":1677542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2023,2,28]]},"abstract":"<jats:p>\n            Relation classification (sometimes called\n            <jats:italic>relation extraction<\/jats:italic>\n            ) requires trustworthy datasets for fine-tuning large language models, as well as for evaluation. Data collection is challenging for Indian languages, because they are syntactically and morphologically diverse, as well as different from resource-rich languages like English. Despite recent interest in deep generative models for Indian languages, relation classification is still not well served by public datasets. In response, we present\n            <jats:sc>IndoRE<\/jats:sc>\n            , a dataset with 21K entity- and relation-tagged gold sentences in three Indian languages (Bengali, Hindi, and Telugu), plus English. We start with a multilingual BERT (mBERT)-based system that captures entity span positions and type information, and provides competitive performance on monolingual relation classification. Using this baseline system, we explore transfer mechanisms between languages and the scope to reduce expensive data annotation while achieving reasonable relation extraction performance. Specifically, we\n            <jats:list list-type=\"ordered\">\n              <jats:list-item>\n                <jats:label>(a)<\/jats:label>\n                <jats:p>study the accuracy-efficiency trade-off between expensive, manually labeled gold instances vs. automatically translated and aligned silver instances to train a relation extractor,<\/jats:p>\n              <\/jats:list-item>\n              <jats:list-item>\n                <jats:label>(b)<\/jats:label>\n                <jats:p>device a simple mechanism for budgeted gold data annotation by intelligently converting distant-supervised silver training instances to gold training instances with human annotators using active learning, and finally<\/jats:p>\n              <\/jats:list-item>\n              <jats:list-item>\n                <jats:label>(c)<\/jats:label>\n                <jats:p>propose an ensemble model to provide a performance boost over that achieved via limited gold training instances.<\/jats:p>\n              <\/jats:list-item>\n            <\/jats:list>\n            We release the dataset for future research.\n            <jats:xref ref-type=\"fn\">\n              <jats:sup>1<\/jats:sup>\n            <\/jats:xref>\n          <\/jats:p>","DOI":"10.1145\/3554734","type":"journal-article","created":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T12:04:43Z","timestamp":1659960283000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Transfer Learning for Low-Resource Multilingual Relation Classification"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2483-4475","authenticated-orcid":false,"given":"Arijit","family":"Nag","sequence":"first","affiliation":[{"name":"Indian Institute of Technology, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0000-2650","authenticated-orcid":false,"given":"Bidisha","family":"Samanta","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4534-0044","authenticated-orcid":false,"given":"Animesh","family":"Mukherjee","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3967-186X","authenticated-orcid":false,"given":"Niloy","family":"Ganguly","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9419-7486","authenticated-orcid":false,"given":"Soumen","family":"Chakrabarti","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Kharagpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,3,23]]},"reference":[{"issue":"4","key":"e_1_3_2_2_2","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/BF00116828","article-title":"Queries and concept learning","volume":"2","author":"Angluin Dana","year":"1988","unstructured":"Dana Angluin. 1988. 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In Proceedings of the Web Conference 2021 (WWW\u201921) . 10.48550\/ARXIV.2009.08694","DOI":"10.1145\/3442381.3449917"},{"key":"e_1_3_2_7_2","doi-asserted-by":"crossref","first-page":"2830","DOI":"10.18653\/v1\/D18-1307","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"Bekoulis Giannis","year":"2018","unstructured":"Giannis Bekoulis, Johannes Deleu, Thomas Demeester, and Chris Develder. 2018. Adversarial training for multi-context joint entity and relation extraction. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2830\u20132836. 10.18653\/v1\/D18-1307"},{"key":"e_1_3_2_8_2","first-page":"9368","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Beluch William H.","year":"2018","unstructured":"William H. Beluch, Tim Genewein, Andreas N\u00fcrnberger, and Jan M. K\u00f6hler. 2018. The power of ensembles for active learning in image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 9368\u20139377."},{"key":"e_1_3_2_9_2","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1145\/1553374.1553381","volume-title":"Proceedings of the 26th Annual International Conference on Machine Learning","author":"Beygelzimer Alina","year":"2009","unstructured":"Alina Beygelzimer, Sanjoy Dasgupta, and John Langford. 2009. Importance weighted active learning. In Proceedings of the 26th Annual International Conference on Machine Learning. 49\u201356."},{"key":"e_1_3_2_10_2","volume-title":"Proceedings of the NIPS Workshop on Analyzing Networks and Learning with Graphs","volume":"4","author":"Bilgic Mustafa","year":"2009","unstructured":"Mustafa Bilgic and Lise Getoor. 2009. Link-based active learning. 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In Proceedings of the International Conference on Machine Learning. 1613\u20131622."},{"key":"e_1_3_2_13_2","doi-asserted-by":"crossref","first-page":"756","DOI":"10.18653\/v1\/P16-1072","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Cai Rui","year":"2016","unstructured":"Rui Cai, Xiaodong Zhang, and Houfeng Wang. 2016. Bidirectional recurrent convolutional neural network for relation classification. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 756\u2013765. 10.18653\/v1\/P16-1072"},{"key":"e_1_3_2_14_2","unstructured":"Jun Chen Robert Hoehndorf Mohamed Elhoseiny and Xiangliang Zhang. 2020. Efficient long-distance relation extraction with DG-SpanBERT. arXiv preprint arXiv:2004.03636 . 10.48550\/ARXIV.2004.03636"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","first-page":"234","DOI":"10.18653\/v1\/2020.clinicalnlp-1.26","volume-title":"Proceedings of the 3rd Clinical Natural Language Processing Workshop","author":"Chen Miao","year":"2020","unstructured":"Miao Chen, Ganhui Lan, Fang Du, and Victor Lobanov. 2020. Joint learning with pre-trained transformer on named entity recognition and relation extraction tasks for clinical analytics. In Proceedings of the 3rd Clinical Natural Language Processing Workshop. 234\u2013242. 10.18653\/v1\/2020.clinicalnlp-1.26"},{"key":"e_1_3_2_16_2","first-page":"150","volume-title":"Proceedings of the 12th International Conference on Machine Learning","author":"Dagan Ido","year":"1995","unstructured":"Ido Dagan and Sean P. Engelson. 1995. Committee-based sampling for training probabilistic classifiers. In Proceedings of the 12th International Conference on Machine Learning. 150\u2013157."},{"key":"e_1_3_2_17_2","first-page":"249","volume-title":"Proceedings of the International Conference on Computational Learning Theory","author":"Dasgupta Sanjoy","year":"2005","unstructured":"Sanjoy Dasgupta, Adam Tauman Kalai, and Claire Monteleoni. 2005. Analysis of perceptron-based active learning. In Proceedings of the International Conference on Computational Learning Theory. 249\u2013263."},{"key":"e_1_3_2_18_2","first-page":"626","volume-title":"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)","author":"Santos C\u00edcero dos","year":"2015","unstructured":"C\u00edcero dos Santos, Bing Xiang, and Bowen Zhou. 2015. Classifying relations by ranking with convolutional neural networks. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 626\u2013634. 10.3115\/v1\/P15-1061"},{"key":"e_1_3_2_19_2","unstructured":"Markus Eberts and Adrian Ulges. 2019. Span-based joint entity and relation extraction with transformer pre-training. arxiv:cs.CL\/1909.07755."},{"issue":"5","key":"e_1_3_2_20_2","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1136\/amiajnl-2011-000648","article-title":"Active learning for clinical text classification: Is it better than random sampling?","volume":"19","author":"Figueroa Rosa L.","year":"2012","unstructured":"Rosa L. Figueroa, Qing Zeng-Treitler, Long H. Ngo, Sergey Goryachev, and Eduardo P. Wiechmann. 2012. Active learning for clinical text classification: Is it better than random sampling? 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In Proceedings of the European Conference on Computer Vision. 562\u2013577."},{"key":"e_1_3_2_23_2","first-page":"1409","volume-title":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","author":"Fu Tsu-Jui","year":"2019","unstructured":"Tsu-Jui Fu, Peng-Hsuan Li, and Wei-Yun Ma. 2019. GraphRel: Modeling text as relational graphs for joint entity and relation extraction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 1409\u20131418. 10.18653\/v1\/P19-1136"},{"key":"e_1_3_2_24_2","first-page":"1050","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Gal Yarin","year":"2016","unstructured":"Yarin Gal and Zoubin Ghahramani. 2016. Dropout as a Bayesian approximation: Representing model uncertainty in deep learning. In Proceedings of the International Conference on Machine Learning. 1050\u20131059."},{"key":"e_1_3_2_25_2","first-page":"1183","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Gal Yarin","year":"2017","unstructured":"Yarin Gal, Riashat Islam, and Zoubin Ghahramani. 2017. Deep Bayesian active learning with image data. In Proceedings of the International Conference on Machine Learning. 1183\u20131192."},{"key":"e_1_3_2_26_2","article-title":"An empirical investigation of catastrophic forgetting in gradient-based neural networks","author":"Goodfellow Ian J.","year":"2013","unstructured":"Ian J. Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio. 2013. An empirical investigation of catastrophic forgetting in gradient-based neural networks. arXiv preprint arXiv:1312.6211.","journal-title":"arXiv preprint arXiv:1312.6211."},{"key":"e_1_3_2_27_2","first-page":"802","volume-title":"Advances in Neural Information Processing Systems (NIPS\u201910)","author":"Guo Yuhong","year":"2010","unstructured":"Yuhong Guo. 2010. Active instance sampling via matrix partition. In Advances in Neural Information Processing Systems (NIPS\u201910). 802\u2013810."},{"key":"e_1_3_2_28_2","first-page":"415","volume-title":"Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics","author":"Haffari Gholamreza","year":"2009","unstructured":"Gholamreza Haffari, Maxim Roy, and Anoop Sarkar. 2009. Active learning for statistical phrase-based machine translation. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics. 415\u2013423."},{"key":"e_1_3_2_29_2","doi-asserted-by":"crossref","first-page":"2236","DOI":"10.18653\/v1\/D18-1247","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"Han Xu","year":"2018","unstructured":"Xu Han, Pengfei Yu, Zhiyuan Liu, Maosong Sun, and Peng Li. 2018. Hierarchical relation extraction with coarse-to-fine grained attention. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2236\u20132245. 10.18653\/v1\/D18-1247"},{"key":"e_1_3_2_30_2","doi-asserted-by":"crossref","first-page":"4803","DOI":"10.18653\/v1\/D18-1514","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"Han Xu","year":"2018","unstructured":"Xu Han, Hao Zhu, Pengfei Yu, Ziyun Wang, Yuan Yao, Zhiyuan Liu, and Maosong Sun. 2018. FewRel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 4803\u20134809. 10.18653\/v1\/D18-1514"},{"key":"e_1_3_2_31_2","first-page":"33","volume-title":"Proceedings of the 5th International Workshop on Semantic Evaluation","author":"Hendrickx Iris","year":"2010","unstructured":"Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid \u00d3. S\u00e9aghdha, Sebastian Pad\u00f3, Marco Pennacchiotti, Lorenza Romano, and Stan Szpakowicz. 2010. SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals. In Proceedings of the 5th International Workshop on Semantic Evaluation. 33\u201338. https:\/\/www.aclweb.org\/anthology\/S10-1006."},{"key":"e_1_3_2_32_2","first-page":"541","volume-title":"Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies","author":"Hoffmann Raphael","year":"2011","unstructured":"Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, and Daniel S. Weld. 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. 541\u2013550. https:\/\/www.aclweb.org\/anthology\/P11-1055."},{"key":"e_1_3_2_33_2","first-page":"1471","volume-title":"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers","author":"Jiang Xiaotian","year":"2016","unstructured":"Xiaotian Jiang, Quan Wang, Peng Li, and Bin Wang. 2016. Relation extraction with multi-instance multi-label convolutional neural networks. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 1471\u20131480. https:\/\/www.aclweb.org\/anthology\/C16-1139."},{"key":"e_1_3_2_34_2","unstructured":"Zhijing Jin Yongyi Yang Xipeng Qiu and Zheng Zhang. 2020. Relation of the relations: A new paradigm of the relation extraction problem. arXiv preprint arXiv:2006.03719 . 10.48550\/ARXIV.2006.03719"},{"key":"e_1_3_2_35_2","doi-asserted-by":"crossref","first-page":"2372","DOI":"10.1109\/CVPR.2009.5206627","volume-title":"Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition","author":"Joshi Ajay J.","year":"2009","unstructured":"Ajay J. Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos. 2009. Multi-class active learning for image classification. In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, Los Alamitos, CA, 2372\u20132379."},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00300"},{"key":"e_1_3_2_37_2","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"32","author":"Kemker Ronald","year":"2018","unstructured":"Ronald Kemker, Marc McClure, Angelina Abitino, Tyler Hayes, and Christopher Kanan. 2018. Measuring catastrophic forgetting in neural networks. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 32."},{"key":"e_1_3_2_38_2","doi-asserted-by":"crossref","unstructured":"Simran Khanuja Melvin Johnson and Partha Talukdar. 2021. MergeDistill: Merging pre-trained language models using distillation. arxiv:cs.CL\/2106.02834.","DOI":"10.18653\/v1\/2021.findings-acl.254"},{"issue":"6971","key":"e_1_3_2_39_2","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1038\/nature02236","article-title":"Functional genomic hypothesis generation and experimentation by a robot scientist","volume":"427","author":"King Ross D.","year":"2004","unstructured":"Ross D. King, Kenneth E. Whelan, Ffion M. Jones, Philip G. K. Reiser, Christopher H. Bryant, Stephen H. Muggleton, Douglas B. Kell, and Stephen G. Oliver. 2004. Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427, 6971 (2004), 247\u2013252.","journal-title":"Nature"},{"issue":"13","key":"e_1_3_2_40_2","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1073\/pnas.1611835114","article-title":"Overcoming catastrophic forgetting in neural networks","volume":"114","author":"Kirkpatrick James","year":"2017","unstructured":"James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, et\u00a0al. 2017. Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences 114, 13 (2017), 3521\u20133526.","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"e_1_3_2_41_2","doi-asserted-by":"crossref","first-page":"579","DOI":"10.3115\/v1\/P14-2095","volume-title":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"Kozhevnikov Mikhail","year":"2014","unstructured":"Mikhail Kozhevnikov and Ivan Titov. 2014. Cross-lingual model transfer using feature representation projection. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 579\u2013585. 10.3115\/v1\/P14-2095"},{"issue":"6","key":"e_1_3_2_42_2","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1109\/TSP.2002.1003062","article-title":"Algorithms for optimal scheduling and management of hidden Markov model sensors","volume":"50","author":"Krishnamurthy Vikram","year":"2002","unstructured":"Vikram Krishnamurthy. 2002. Algorithms for optimal scheduling and management of hidden Markov model sensors. IEEE Transactions on Signal Processing 50, 6 (2002), 1382\u20131397.","journal-title":"IEEE Transactions on Signal Processing"},{"key":"e_1_3_2_43_2","unstructured":"Joohong Lee Sangwoo Seo and Yong Suk Choi. 2019. Semantic relation classification via bidirectional LSTM networks with entity-aware attention using latent entity typing. arXiv preprint arXiv:1901.08163 . 10.48550\/ARXIV.1901.08163"},{"key":"e_1_3_2_44_2","first-page":"978","volume-title":"Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval\u201917)","author":"Lee Ji Young","year":"2017","unstructured":"Ji Young Lee, Franck Dernoncourt, and Peter Szolovits. 2017. MIT at SemEval-2017 task 10: Relation extraction with convolutional neural networks. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval\u201917). 978\u2013984. 10.18653\/v1\/S17-2171"},{"key":"e_1_3_2_45_2","doi-asserted-by":"crossref","unstructured":"David D. Lewis and William A. Gale. 1995. A sequential algorithm for training text classifiers. ACM SIGIR Forum 29 2 (1995) 13\u201319.","DOI":"10.1145\/219587.219592"},{"key":"e_1_3_2_46_2","first-page":"2124","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Lin Yankai","year":"2016","unstructured":"Yankai Lin, Shiqi Shen, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. 2016. Neural relation extraction with selective attention over instances. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2124\u20132133. 10.18653\/v1\/P16-1200"},{"key":"e_1_3_2_47_2","first-page":"2195","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"Liu Tianyi","year":"2018","unstructured":"Tianyi Liu, Xinsong Zhang, Wanhao Zhou, and Weijia Jia. 2018. Neural relation extraction via inner-sentence noise reduction and transfer learning. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2195\u20132204. 10.18653\/v1\/D18-1243"},{"key":"e_1_3_2_48_2","first-page":"285","volume-title":"Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)","author":"Liu Yang","year":"2015","unstructured":"Yang Liu, Furu Wei, Sujian Li, Heng Ji, Ming Zhou, and Houfeng Wang. 2015. A dependency-based neural network for relation classification. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). 285\u2013290. 10.3115\/v1\/P15-2047"},{"key":"e_1_3_2_49_2","first-page":"359","volume-title":"Proceedings of the International Conference on Machine Learning (ICML\u201998)","author":"McCallumzy Andrew Kachites","year":"1998","unstructured":"Andrew Kachites McCallumzy and Kamal Nigamy. 1998. Employing EM and pool-based active learning for text classification. In Proceedings of the International Conference on Machine Learning (ICML\u201998). 359\u2013367."},{"key":"e_1_3_2_50_2","first-page":"1003","volume-title":"Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP","author":"Mintz Mike","year":"2009","unstructured":"Mike Mintz, Steven Bills, Rion Snow, and Daniel Jurafsky. 2009. Distant supervision for relation extraction without labeled data. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. 1003\u20131011. https:\/\/www.aclweb.org\/anthology\/P09-1113."},{"key":"e_1_3_2_51_2","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.18653\/v1\/P16-1105","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Miwa Makoto","year":"2016","unstructured":"Makoto Miwa and Mohit Bansal. 2016. End-to-end relation extraction using LSTMs on sequences and tree structures. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1105\u20131116. 10.18653\/v1\/P16-1105"},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.48"},{"key":"e_1_3_2_53_2","first-page":"575","volume-title":"Proceedings of the 25th Conference on Computational Natural Language Learning","author":"Nag Arijit","year":"2021","unstructured":"Arijit Nag, Bidisha Samanta, Animesh Mukherjee, Niloy Ganguly, and Soumen Chakrabarti. 2021. A data bootstrapping recipe for low-resource multilingual relation classification. In Proceedings of the 25th Conference on Computational Natural Language Learning. 575\u2013587."},{"key":"e_1_3_2_54_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-15712-8_47"},{"key":"e_1_3_2_55_2","first-page":"79","volume-title":"Proceedings of the 21st International Conference on Machine Learning","author":"Nguyen Hieu T.","year":"2004","unstructured":"Hieu T. Nguyen and Arnold Smeulders. 2004. Active learning using pre-clustering. In Proceedings of the 21st International Conference on Machine Learning. 79."},{"key":"e_1_3_2_56_2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.3115\/v1\/W15-1506","volume-title":"Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing","author":"Nguyen Thien Huu","year":"2015","unstructured":"Thien Huu Nguyen and Ralph Grishman. 2015. Relation extraction: Perspective from convolutional neural networks. In Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing. 39\u201348. 10.3115\/v1\/W15-1506"},{"key":"e_1_3_2_57_2","unstructured":"Jian Ni Taesun Moon Parul Awasthy and Radu Florian. 2020. Cross-lingual relation extraction with transformers. arxiv:cs.CL\/2010.08652."},{"key":"e_1_3_2_58_2","doi-asserted-by":"crossref","first-page":"46","DOI":"10.18653\/v1\/2020.emnlp-demos.7","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Systems Demonstrations (EMNLP\u201920)","author":"Pfeiffer Jonas","year":"2020","unstructured":"Jonas Pfeiffer, Andreas R\u00fcckl\u00e9, Clifton Poth, Aishwarya Kamath, Ivan Vuli\u0107, Sebastian Ruder, Kyunghyun Cho, and Iryna Gurevych. 2020. AdapterHub: A framework for adapting transformers. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Systems Demonstrations (EMNLP\u201920). 46\u201354. https:\/\/www.aclweb.org\/anthology\/2020.emnlp-demos.7."},{"key":"e_1_3_2_59_2","doi-asserted-by":"crossref","unstructured":"Jonas Pfeiffer Ivan Vuli\u0107 Iryna Gurevych and Sebastian Ruder. 2020. MAD-X: An adapter-based framework for multi-task cross-lingual transfer. arxiv:cs.CL\/2005.00052.","DOI":"10.18653\/v1\/2020.emnlp-main.617"},{"key":"e_1_3_2_60_2","doi-asserted-by":"crossref","unstructured":"Telmo Pires Eva Schlinger and Dan Garrette. 2019. How multilingual is multilingual BERT? arxiv:cs.CL\/1906.01502.","DOI":"10.18653\/v1\/P19-1493"},{"key":"e_1_3_2_61_2","first-page":"3934","volume-title":"Proceedings of the 2017 IEEE International Conference on Image Processing (ICIP\u201917)","author":"Ranganathan Hiranmayi","year":"2017","unstructured":"Hiranmayi Ranganathan, Hemanth Venkateswara, Shayok Chakraborty, and Sethuraman Panchanathan. 2017. Deep active learning for image classification. In Proceedings of the 2017 IEEE International Conference on Image Processing (ICIP\u201917). IEEE, Los Alamitos, CA, 3934\u20133938."},{"key":"e_1_3_2_62_2","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Riedel Sebastian","year":"2010","unstructured":"Sebastian Riedel, Limin Yao, and Andrew McCallum. 2010. Modeling relations and their mentions without labeled text. In Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science, Vol. 10535. Springer, 148\u2013163."},{"key":"e_1_3_2_63_2","first-page":"441","article-title":"Toward optimal active learning through Monte Carlo estimation of error reduction","volume":"2","author":"Roy Nicholas","year":"2001","unstructured":"Nicholas Roy and Andrew McCallum. 2001. Toward optimal active learning through Monte Carlo estimation of error reduction. ICML, Williamstown 2 (2001), 441\u2013448.","journal-title":"ICML, Williamstown"},{"key":"e_1_3_2_64_2","first-page":"4548","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Serra Joan","year":"2018","unstructured":"Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou. 2018. Overcoming catastrophic forgetting with hard attention to the task. In Proceedings of the International Conference on Machine Learning. 4548\u20134557."},{"key":"e_1_3_2_65_2","first-page":"1289","article-title":"Multiple-instance active learning","volume":"20","author":"Settles Burr","year":"2007","unstructured":"Burr Settles, Mark Craven, and Soumya Ray. 2007. Multiple-instance active learning. Advances in Neural Information Processing Systems 20 (2007), 1289\u20131296.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_66_2","first-page":"287","volume-title":"Proceedings of the 5th Annual Workshop on Computational Learning Theory","author":"Seung H. Sebastian","year":"1992","unstructured":"H. Sebastian Seung, Manfred Opper, and Haim Sompolinsky. 1992. Query by committee. In Proceedings of the 5th Annual Workshop on Computational Learning Theory. 287\u2013294."},{"key":"e_1_3_2_67_2","first-page":"1249","article-title":"Large margin hidden Markov models for automatic speech recognition","volume":"19","author":"Sha Fei","year":"2007","unstructured":"Fei Sha and Lawrence K. Saul. 2007. Large margin hidden Markov models for automatic speech recognition. Advances in Neural Information Processing Systems 19 (2007), 1249.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_68_2","first-page":"2526","volume-title":"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers","author":"Shen Yatian","year":"2016","unstructured":"Yatian Shen and Xuanjing Huang. 2016. Attention-based convolutional neural network for semantic relation extraction. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 2526\u20132536. https:\/\/www.aclweb.org\/anthology\/C16-1238."},{"key":"e_1_3_2_69_2","article-title":"Deep active learning for named entity recognition","author":"Shen Yanyao","year":"2017","unstructured":"Yanyao Shen, Hyokun Yun, Zachary C. Lipton, Yakov Kronrod, and Animashree Anandkumar. 2017. Deep active learning for named entity recognition. arXiv preprint arXiv:1707.05928.","journal-title":"arXiv preprint arXiv:1707.05928."},{"key":"e_1_3_2_70_2","first-page":"1308","volume-title":"Proceedings of the International Conference on Artificial Intelligence and Statistics","author":"Shui Changjian","year":"2020","unstructured":"Changjian Shui, Fan Zhou, Christian Gagn\u00e9, and Boyu Wang. 2020. Deep active learning: Unified and principled method for query and training. In Proceedings of the International Conference on Artificial Intelligence and Statistics. 1308\u20131318."},{"key":"e_1_3_2_71_2","doi-asserted-by":"crossref","unstructured":"Livio Baldini Soares Nicholas FitzGerald Jeffrey Ling and Tom Kwiatkowski. 2019. Matching the blanks: Distributional similarity for relation learning. arxiv:cs.CL\/1906.03158.","DOI":"10.18653\/v1\/P19-1279"},{"key":"e_1_3_2_72_2","first-page":"455","volume-title":"Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning","author":"Surdeanu Mihai","year":"2012","unstructured":"Mihai Surdeanu, Julie Tibshirani, Ramesh Nallapati, and Christopher D. Manning. 2012. Multi-instance multi-label learning for relation extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. 455\u2013465. https:\/\/www.aclweb.org\/anthology\/D12-1042."},{"key":"e_1_3_2_73_2","first-page":"406","volume-title":"Proceedings of the 16th International Conference on Machine Learning (ICML\u201999)","author":"Thompson Cynthia A.","year":"1999","unstructured":"Cynthia A. Thompson, Mary Elaine Califf, and Raymond J. Mooney. 1999. Active learning for natural language parsing and information extraction. In Proceedings of the 16th International Conference on Machine Learning (ICML\u201999). 406\u2013414."},{"key":"e_1_3_2_74_2","first-page":"45","article-title":"Support vector machine active learning with applications to text classification","author":"Tong Simon","year":"2001","unstructured":"Simon Tong and Daphne Koller. 2001. Support vector machine active learning with applications to text classification. Journal of Machine Learning Research 2 (Nov. 2001), 45\u201366.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_75_2","doi-asserted-by":"crossref","first-page":"1257","DOI":"10.18653\/v1\/D18-1157","volume-title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","author":"Vashishth Shikhar","year":"2018","unstructured":"Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, and Partha Talukdar. 2018. RESIDE: Improving distantly-supervised neural relation extraction using side information. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 1257\u20131266. 10.18653\/v1\/D18-1157"},{"key":"e_1_3_2_76_2","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.18653\/v1\/2020.emnlp-main.133","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP\u201920)","author":"Wang Jue","year":"2020","unstructured":"Jue Wang and Wei Lu. 2020. Two are better than one: Joint entity and relation extraction with table-sequence encoders. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP\u201920). 1706\u20131721. 10.18653\/v1\/2020.emnlp-main.133"},{"key":"e_1_3_2_77_2","doi-asserted-by":"crossref","first-page":"1298","DOI":"10.18653\/v1\/P16-1123","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Wang Linlin","year":"2016","unstructured":"Linlin Wang, Zhu Cao, Gerard de Melo, and Zhiyuan Liu. 2016. Relation classification via multi-level attention CNNs. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1298\u20131307. 10.18653\/v1\/P16-1123"},{"key":"e_1_3_2_78_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.63"},{"key":"e_1_3_2_79_2","unstructured":"Shanchan Wu and Yifan He. 2019. Enriching pre-trained language model with entity information for relation classification. arXiv preprint arXiv:1905.08284 . 10.48550\/ARXIV.1905.08284"},{"key":"e_1_3_2_80_2","first-page":"1778","volume-title":"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing","author":"Wu Yi","year":"2017","unstructured":"Yi Wu, David Bamman, and Stuart Russell. 2017. Adversarial training for relation extraction. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 1778\u20131783. 10.18653\/v1\/D17-1187"},{"key":"e_1_3_2_81_2","first-page":"1254","volume-title":"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers","author":"Xiao Minguang","year":"2016","unstructured":"Minguang Xiao and Cong Liu. 2016. Semantic relation classification via hierarchical recurrent neural network with attention. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 1254\u20131263. https:\/\/www.aclweb.org\/anthology\/C16-1119."},{"key":"e_1_3_2_82_2","first-page":"536","volume-title":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","author":"Xu Kun","year":"2015","unstructured":"Kun Xu, Yansong Feng, Songfang Huang, and Dongyan Zhao. 2015. Semantic relation classification via convolutional neural networks with simple negative sampling. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. 536\u2013540. 10.18653\/v1\/D15-1062"},{"key":"e_1_3_2_83_2","first-page":"1461","volume-title":"Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers","author":"Xu Yan","year":"2016","unstructured":"Yan Xu, Ran Jia, Lili Mou, Ge Li, Yunchuan Chen, Yangyang Lu, and Zhi Jin. 2016. Improved relation classification by deep recurrent neural networks with data augmentation. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. 1461\u20131470. https:\/\/www.aclweb.org\/anthology\/C16-1138."},{"key":"e_1_3_2_84_2","first-page":"1785","volume-title":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","author":"Xu Yan","year":"2015","unstructured":"Yan Xu, Lili Mou, Ge Li, Yunchuan Chen, Hao Peng, and Zhi Jin. 2015. Classifying relations via long short term memory networks along shortest dependency paths. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. 1785\u20131794. 10.18653\/v1\/D15-1206"},{"key":"e_1_3_2_85_2","unstructured":"Fuzhao Xue Aixin Sun Hao Zhang and Eng Siong Chng. 2020. GDPNet: Refining latent multi-view graph for relation extraction. arXiv preprint arXiv:2012.06780 . 10.48550\/ARXIV.2012.06780"},{"key":"e_1_3_2_86_2","doi-asserted-by":"crossref","first-page":"6442","DOI":"10.18653\/v1\/2020.emnlp-main.523","volume-title":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP\u201920)","author":"Yamada Ikuya","year":"2020","unstructured":"Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, and Yuji Matsumoto. 2020. LUKE: Deep contextualized entity representations with entity-aware self-attention. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP\u201920). 6442\u20136454. 10.18653\/v1\/2020.emnlp-main.523"},{"key":"e_1_3_2_87_2","first-page":"2810","volume-title":"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)","author":"Ye Zhi-Xiu","year":"2019","unstructured":"Zhi-Xiu Ye and Zhen-Hua Ling. 2019. Distant supervision relation extraction with intra-bag and inter-bag attentions. 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). 2810\u20132819. 10.18653\/v1\/N19-1288"},{"key":"e_1_3_2_88_2","first-page":"575","volume-title":"Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM\u201917)","author":"Yin Changchang","year":"2017","unstructured":"Changchang Yin, Buyue Qian, Shilei Cao, Xiaoyu Li, Jishang Wei, Qinghua Zheng, and Ian Davidson. 2017. Deep similarity-based batch mode active learning with exploration-exploitation. In Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM\u201917). IEEE, Los Alamitos, CA, 575\u2013584."},{"key":"e_1_3_2_89_2","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.18653\/v1\/D15-1203","volume-title":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","author":"Zeng Daojian","year":"2015","unstructured":"Daojian Zeng, Kang Liu, Yubo Chen, and Jun Zhao. 2015. Distant supervision for relation extraction via piecewise convolutional neural networks. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. 1753\u20131762. 10.18653\/v1\/D15-1203"},{"key":"e_1_3_2_90_2","first-page":"2335","volume-title":"Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers","author":"Zeng Daojian","year":"2014","unstructured":"Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. 2014. Relation classification via convolutional deep neural network. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers. 2335\u20132344. https:\/\/www.aclweb.org\/anthology\/C14-1220."},{"key":"e_1_3_2_91_2","first-page":"1768","volume-title":"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing","author":"Zeng Wenyuan","year":"2017","unstructured":"Wenyuan Zeng, Yankai Lin, Zhiyuan Liu, and Maosong Sun. 2017. Incorporating relation paths in neural relation extraction. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 1768\u20131777. 10.18653\/v1\/D17-1186"},{"key":"e_1_3_2_92_2","first-page":"1856","volume-title":"Proceedings of the Conference on Learning Theory","author":"Zhang Chicheng","year":"2018","unstructured":"Chicheng Zhang. 2018. Efficient active learning of sparse halfspaces. In Proceedings of the Conference on Learning Theory. 1856\u20131880."},{"key":"e_1_3_2_93_2","unstructured":"Dongxu Zhang and Dong Wang. 2015. Relation classification via recurrent neural network. arXiv preprint arXiv:1508.01006 . 10.48550\/ARXIV.1508.01006"},{"key":"e_1_3_2_94_2","first-page":"73","volume-title":"Proceedings of the 29th Pacific Asia Conference on Language, Information, and Computation","author":"Zhang Shu","year":"2015","unstructured":"Shu Zhang, Dequan Zheng, Xinchen Hu, and Ming Yang. 2015. Bidirectional long short-term memory networks for relation classification. In Proceedings of the 29th Pacific Asia Conference on Language, Information, and Computation. 73\u201378. https:\/\/www.aclweb.org\/anthology\/Y15-1009."},{"key":"e_1_3_2_95_2","first-page":"35","volume-title":"Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing","author":"Zhang Yuhao","year":"2017","unstructured":"Yuhao Zhang, Victor Zhong, Danqi Chen, Gabor Angeli, and Christopher D. Manning. 2017. Position-aware attention and supervised data improve slot filling. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 35\u201345. 10.18653\/v1\/D17-1004"},{"key":"e_1_3_2_96_2","article-title":"Diverse mini-batch active learning","author":"Zhdanov Fedor","year":"2019","unstructured":"Fedor Zhdanov. 2019. Diverse mini-batch active learning. arXiv preprint arXiv:1901.05954.","journal-title":"arXiv preprint arXiv:1901.05954."},{"key":"e_1_3_2_97_2","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.18653\/v1\/P17-1113","volume-title":"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Zheng Suncong","year":"2017","unstructured":"Suncong Zheng, Feng Wang, Hongyun Bao, Yuexing Hao, Peng Zhou, and Bo Xu. 2017. Joint extraction of entities and relations based on a novel tagging scheme. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1227\u20131236. 10.18653\/v1\/P17-1113"},{"key":"e_1_3_2_98_2","doi-asserted-by":"crossref","first-page":"207","DOI":"10.18653\/v1\/P16-2034","volume-title":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","author":"Zhou Peng","year":"2016","unstructured":"Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, and Bo Xu. 2016. Attention-based bidirectional long short-term memory networks for relation classification. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 207\u2013212. 10.18653\/v1\/P16-2034"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3554734","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3554734","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:29Z","timestamp":1750182569000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3554734"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,28]]},"references-count":97,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2,28]]}},"alternative-id":["10.1145\/3554734"],"URL":"https:\/\/doi.org\/10.1145\/3554734","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"type":"print","value":"2375-4699"},{"type":"electronic","value":"2375-4702"}],"subject":[],"published":{"date-parts":[[2023,2,28]]},"assertion":[{"value":"2022-03-22","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-07-21","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}