{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:08:22Z","timestamp":1792757302255,"version":"4.5.0"},"reference-count":55,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,2,2]],"date-time":"2020-02-02T00:00:00Z","timestamp":1580601600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Named entity recognition (NER) is a fundamental step for many natural language processing tasks and hence enhancing the performance of NER models is always appreciated. With limited resources being available, NER for South-East Asian languages like Telugu is quite a challenging problem. This paper attempts to improve the NER performance for Telugu using gazetteer-related features, which are automatically generated using Wikipedia pages. We make use of these gazetteer features along with other well-known features like contextual, word-level, and corpus features to build NER models. NER models are developed using three well-known classifiers\u2014conditional random field (CRF), support vector machine (SVM), and margin infused relaxed algorithms (MIRA). The gazetteer features are shown to improve the performance, and theMIRA-based NER model fared better than its counterparts SVM and CRF.<\/jats:p>","DOI":"10.3390\/info11020082","type":"journal-article","created":{"date-parts":[[2020,2,3]],"date-time":"2020-02-03T11:28:31Z","timestamp":1580729311000},"page":"82","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Enhancing the Performance of Telugu Named Entity Recognition Using Gazetteer Features"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7383-5234","authenticated-orcid":false,"given":"SaiKiranmai","family":"Gorla","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Systems, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Telangana 500078, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lalita Bhanu Murthy","family":"Neti","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Systems, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Telangana 500078, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aruna","family":"Malapati","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Systems, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Telangana 500078, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Grishman, R. (1995, January 5\u20139). The NYU System for MUC-6 or Where\u2019s the Syntax?. Proceedings of the 6th Conference on Message Understanding. Association for Computational Linguistics, Center for Sprogteknologi, Copenhagen, Denmark.","DOI":"10.3115\/1072399.1072415"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Guo, J., Xu, G., Cheng, X., and Li, H. (2009, January 19\u201323). Named Entity Recognition in Query. Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in information retrieval, Boston, MA, USA.","DOI":"10.1145\/1571941.1571989"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1109\/TASL.2009.2019927","article-title":"Arabic Named Entity Recognition: A Feature-Driven Study","volume":"17","author":"Benajiba","year":"2009","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Babych, B., and Hartley, A. (2003, January 12\u201317). Improving Machine Translation Quality with Automatic Named Entity Recognition. Proceedings of the 7th International EAMT Workshop on MT and Other Language Technology Tools, Improving MT through Other Language Technology Tools, Resource and Tools for Building MT at EACL, Budapest, Hungary.","DOI":"10.3115\/1609822.1609823"},{"key":"ref_5","unstructured":"H\u00e1lek, O., Rosa, R., Tamchyna, A., and Bojar, O. (2011, January 25\u201329). Named entities from Wikipedia for machine translation. Proceedings of the CEUR Workshop Proceedings 584, Horsk\u00fd hotel Kralova studna, Harmanec, Slovakia."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1162\/COLI_a_00122","article-title":"A joint model to identify and align bilingual named entities","volume":"39","author":"Chen","year":"2013","journal-title":"Comput. Linguist."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Indurkhya, N., and Damerau, F.J. (2010). Handbook of Natural Language Processing, Chapman & Hall\/CRC. [2nd ed.].","DOI":"10.1201\/9781420085938"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Srihari, R., and Li, W. (1999). Information Extraction Supported Question Answering, Cymfony Net Inc.. Technical Report.","DOI":"10.21236\/ADA460042"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Toral, A., Noguera, E., Llopis, F., and Mu\u00f1oz, R. (2005). Improving Question Answering Using Named Entity Recognition. Natural Language Processing and Information Systems, Springer.","DOI":"10.1007\/11428817_17"},{"key":"ref_10","unstructured":"Moll\u00e1, D., Van Zaanen, M., and Smith, D. (December, January 30). Named Entity Recognition for Question Answering. Proceedings of the Australasian Language Technology workshop, Sydney, Australia."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5811","DOI":"10.1016\/j.eswa.2013.05.008","article-title":"Answering questions about European legislation","volume":"40","author":"Rodrigo","year":"2013","journal-title":"Expert Syst. Appl."},{"key":"ref_12","unstructured":"Nobata, C., Sekine, S., Isahara, H., and Grishman, R. (2002, January 29\u201331). Summarization System Integrated with Named Entity Tagging and IE pattern Discovery. Proceedings of the European Language Resources Association (ELRA), Las Palmas, Canary Island, Spain."},{"key":"ref_13","unstructured":"Hassel, M. (2003, January 30\u201331). Exploitation of named entities in automatic text summarization for swedish. Proceedings of the NODALIDA\u201903\u201314th Nordic Conference on Computational Linguistics, Reykjavik, Iceland."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"6976","DOI":"10.1016\/j.eswa.2013.06.047","article-title":"Multi-document summarization based on the Yago ontology","volume":"40","author":"Baralis","year":"2013","journal-title":"Expert Syst. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Mikheev, A., Moens, M., and Grover, C. (1999, January 8\u201312). Named Entity Recognition Without Gazetteers. Proceedings of the Ninth Conference on European Chapter of the Association for Computational, Association for Computational Linguistics, Bergen, Norway.","DOI":"10.3115\/977035.977037"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-11-85","article-title":"LINNAEUS: A species name identification system for biomedical literature","volume":"11","author":"Gerner","year":"2010","journal-title":"Bmc Bioinform."},{"key":"ref_17","unstructured":"Cucerzan, S., and Yarowsky, D. (1999, January 21\u201322). Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence. Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, College Park, MD, USA."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1023\/A:1007558221122","article-title":"An algorithm that learns what\u2019s in a name","volume":"34","author":"Bikel","year":"1999","journal-title":"Mach. Learn."},{"key":"ref_19","unstructured":"Borthwick, A., Sterling, J., Agichtein, E., and Grishman, R. (1998, January 15\u201316). Exploiting diverse knowledge sources via maximum entropy in named entity recognition. Proceedings of the Sixth Workshop on Very Large Corpora, Montreal, QC, Canada."},{"key":"ref_20","unstructured":"Sekine, S., Grishman, R., and Shinnou, H. (1998, January 15\u201316). A decision tree method for finding and classifying names in Japanese texts. Proceedings of the Sixth Workshop on Very Large Corpora, Montreal, QC, Canada."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"McCallum, A., and Li, W. (June, January 27). Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. Proceedings of the 7th Conference on Natural Language Learning at HLT-NAACL 2003-Volume 4: Association for Computational Linguistics, Edmonton, AB, Canada.","DOI":"10.3115\/1119176.1119206"},{"key":"ref_22","unstructured":"Kazama, J., and Torisawa, K. (2007, January 28\u201330). A New Perceptron Algorithm for Sequence Labeling with Non-Local Features. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Prague, Czech Republic."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Mohit, B., and Hwa, R. (2005, January 25\u201330). Syntax-based Semi-Supervised Named Entity Tagging. Proceedings of the ACL Interactive Poster and Demonstration Sessions. Association for Computational Linguistics, Ann Arbor, MI, USA.","DOI":"10.3115\/1225753.1225768"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Isozaki, H., and Kazawa, H. (2002, January 26\u201330). Efficient support vector classifiers for named entity recognition. Proceedings of the 19th International Conference on Computational Linguistics-Volume 1: Association for Computational Linguistics, Taipei, Taiwan.","DOI":"10.3115\/1072228.1072282"},{"key":"ref_25","unstructured":"Collins, M., and Singer, Y. (1999, January 21\u201322). Unsupervised models for named entity classification. Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, College Park, MD, USA."},{"key":"ref_26","unstructured":"Nadeau, D. (2007). Semi-supervised named entity recognition: Learning to recognize 100 entity types with little supervision. [Ph.D. Thesis, University of Ottawa]."},{"key":"ref_27","unstructured":"(2020, January 20). List of Languages by Number of Native Speakers in India. Available online: https:\/\/en.wikipedia.org\/wiki\/List_of_languages_by_number_of_native_speakers_in_India."},{"key":"ref_28","unstructured":"Shishtla, P., Gali, K., Pingali, P., and Varma, V. (2008, January 7\u201312). Experiments in Telugu NER: A Conditional Random Field Approach. Proceedings of the Third International Joint Conference on Natural Language Processing, IJCNLP, Hyderabad, India."},{"key":"ref_29","unstructured":"Das, A., and Garain, U. (2014). CRF-Based Named Entity Recognition @ICON 2013. arXiv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.datak.2012.06.003","article-title":"Combining Multiple Classifiers Using Vote Based Classifier Ensemble Technique for Named Entity Recognition","volume":"85","author":"Saha","year":"2013","journal-title":"Data Knowl. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"14760","DOI":"10.1016\/j.eswa.2011.05.004","article-title":"A Multiobjective Simulated Annealing Approach for Classifier Ensemble: Named Entity Recognition in Indian Languages As Case Studies","volume":"38","author":"Ekbal","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1075\/li.30.1.03nad","article-title":"A survey of named entity recognition and classification","volume":"30","author":"Nadeau","year":"2007","journal-title":"Lingvisticae Investig."},{"key":"ref_33","unstructured":"Srikanth, P., and Murthy, K.N. (, January 7\u201312). Named Entity Recognition for Telugu. Proceedings of the Third International Joint Conference on Natural Language Processing, IJCNLP, Hyderabad, India."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ciravegna, F., Chapman, S., Dingli, A., and Wilks, Y. (2004). Learning to harvest information for the semantic web. European Semantic Web Symposium, Springer.","DOI":"10.1007\/978-3-540-25956-5_22"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Gorla, S., Murthy, N.L.B., and Malapati, A. (2017, January 6\u20139). A Comparative Study of Named Entity Recognition for Telugu. Proceedings of the 9th Annual Meeting of the Forum for Information Retrieval Evaluation, Gandhinagar, India.","DOI":"10.1145\/3158354.3158358"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Gorla, S., Velivelli, S., Murthy, N.B., and Malapati, A. (2018, January 26). Named Entity Recognition for Telugu News Articles using Na\u00efve Bayes Classifier. Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval co-located with 40th European Conference on Information Retrieval(ECIR), Grenoble, France.","DOI":"10.1145\/3158354.3158358"},{"key":"ref_37","first-page":"39","article-title":"TelNEClus: Telugu Named Entity Clustering Using Semantic Similarity","volume":"Volume II","author":"Gorla","year":"2019","journal-title":"Proceedings of the International Conference on Computational Intelligence: Theories, Applications and Future Directions"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Li, W., and McCallum, A. (2003). Rapid Development of Hindi Named Entity Recognition Using Conditional Random Fields and Feature Induction. ACM Transactions on Asian Language Information Processing (TALIP), Association for Computing Machinery.","DOI":"10.1145\/979872.979879"},{"key":"ref_39","unstructured":"Saha, S.K., Sarkar, S., and Mitra, P. (2008, January 12). A hybrid feature set based maximum entropy Hindi named entity recognition. Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I, Hyderabad, India."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1016\/j.patrec.2010.05.004","article-title":"A composite kernel for named entity recognition","volume":"31","author":"Saha","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ekbal, A., and Bandyopadhyay, S. (2008, January 12). Bengali named entity recognition using support vector machine. Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages, Hyderabad, India.","DOI":"10.1109\/ICAPR.2009.86"},{"key":"ref_42","first-page":"155","article-title":"Named entity recognition using support vector machine: A language independent approach","volume":"4","author":"Ekbal","year":"2010","journal-title":"Int. J. Electr. Comput. Syst. Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.33011\/lilt.v2i.1203","article-title":"A conditional random field approach for named entity recognition in Bengali and Hindi","volume":"2","author":"Ekbal","year":"2009","journal-title":"Linguist. Issues Lang. Technol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Banerjee, S., Naskar, S.K., and Bandyopadhyay, S. (2014, January 8\u201312). Bengali named entity recognition using margin infused relaxed algorithm. Proceedings of the International Conference on Text, Speech, and Dialogue, Brno, Czech Republic.","DOI":"10.1007\/978-3-319-10816-2_16"},{"key":"ref_45","unstructured":"Vijayakrishna, R., and Sobha, L. (2008, January 12). Domain Focused Named Entity Recognizer for Tamil Using Conditional Random Fields. Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages, Hyderabad, India."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.17485\/ijst\/2015\/v8i24\/85350","article-title":"Randomized kernel approach for named entity recognition in Tamil","volume":"8","author":"Abinaya","year":"2015","journal-title":"Indian J. Sci. Technol."},{"key":"ref_47","unstructured":"Krishnamurti, B., and Gwynn, J.P.L. (1985). A Grammar of Modern Telugu, Oxford University Press."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Robert, C. (2014). Machine Learning, a Probabilistic Perspective, MIT Press.","DOI":"10.1080\/09332480.2014.914768"},{"key":"ref_49","unstructured":"Reddy, S., and Sharoff, S. (2011, January 8\u201312). Cross language POS taggers (and other tools) for Indian languages: An experiment with Kannada using Telugu resources. Proceedings of the Fifth International Workshop On Cross Lingual Information Access, Chiang Mai, Thailand."},{"key":"ref_50","first-page":"1","article-title":"Statistical Analyses of Telugu Text Corpora","volume":"36","author":"Kumar","year":"2007","journal-title":"Int. J. Dravid. Lang."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Gorla, S., Velivelli, S., Satpathi, D.K., Murthy, N.L.B., and Malapati, A. (2020). Named Entity Recognition Using Part-of-Speech Rules for Telugu. Smart Computing Paradigms: New Progresses and Challenges, Springer.","DOI":"10.1007\/978-981-13-9683-0_16"},{"key":"ref_52","unstructured":"Zesch, T., Gurevych, I., and M\u00fchlh\u00e4user, M. (2007). Analyzing and accessing Wikipedia as a lexical semantic resource. Data Structures for Linguistic Resources and Applications, Gunter Narr."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, Z., and Iria, J. (2009, January 7). A Novel Approach to Automatic Gazetteer Generation using Wikipedia. Proceedings of the 2009 Workshop on The People\u2019s Web Meets NLP: Collaboratively Constructed Semantic Resources (People\u2019s Web), Suntec, Singapore.","DOI":"10.3115\/1699765.1699766"},{"key":"ref_54","unstructured":"Attia, M., Toral, A., Tounsi, L., Monachini, M., and van Genabith, J. (2010, January 17\u201323). An Automatically Built Named Entity Lexicon for Arabic. Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC\u201910), Valletta, Malta."},{"key":"ref_55","first-page":"951","article-title":"Ultraconservative online algorithms for multiclass problems","volume":"3","author":"Crammer","year":"2003","journal-title":"J. Mach. Learn. Res."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/11\/2\/82\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:53:57Z","timestamp":1760172837000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/11\/2\/82"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,2]]},"references-count":55,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["info11020082"],"URL":"https:\/\/doi.org\/10.3390\/info11020082","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,2]]}}}