Message Understanding Conference-6: a brief history

Nomen Omen. Enhancing the Latin Morphological Analyser Lemlat with an Onomasticon

Budassi, M., & Passarotti, M. (2016) · SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities · doi:10.18653/v1/w16-2110 · Cited by 23

Transfer Learning for Entity Recognition of Novel Classes

Rodríguez, J. D., Adam, C., & Liu, A. (2018) · International Conference on Computational Linguistics · Cited by 23

Assessing the impact of OCR noise on multilingual event detection over digitised documents

Boroş, E., Nguyen, N. K., Lejeune, G., & Doucet, A. (2022) · International Journal on Digital Libraries · doi:10.1007/s00799-022-00325-2 · Cited by 23

Nudging the Envelope of Direct Transfer Methods for Multilingual Named Entity Recognition

Täckström, O. (2012) · Cited by 24

Text Understanding Agents and the Semantic Web

Java, A., Finin, T., & Nirenburg, S. (2006) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2006.452 · Cited by 23

Declarative Cleaning of Inconsistencies in Information Extraction

Fagin, R., Kimelfeld, B., Reiss, F. R., & Vansummeren, S. (2016) · ACM Transactions on Database Systems · doi:10.1145/2877202 · Cited by 23

SlinkET: A Partial Modal Parser for Events

Sauri, R. S., Verhagen, M., & Pustejovsky, J. D. (2006) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/4rmue4sc6bax · Cited by 23

Ontologies as facilitators for repurposing web documents

Weal, M. J., Alani, H., Kim, S., Lewis, P. H., Millard, D. E., Sinclair, P. A. S., Roure, D. D., & Shadbolt, N. R. (2007) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2007.02.001 · Cited by 23

Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing

Constant, M., Andreas Maletti, A., & Savary, A. (2011) · Cited by 23

Named Entity Extraction and Disambiguation: The Reinforcement Effect

Habib, M. B., & van Keulen, M. (2011) · University of Twente Research Information · Cited by 22

A 2-phase frame-based knowledge extraction framework

Corcoglioniti, F., Rospocher, M., & Aprosio, A. P. (2016) · ACM Symposium on Applied Computing · doi:10.1145/2851613.2851845 · Cited by 22

B-NER: A Novel Bangla Named Entity Recognition Dataset With Largest Entities and Its Baseline Evaluation

Haque, M. Z., Zaman, S., Saurav, J. R., Haque, S., Islam, M. S., & Amin, M. R. (2023) · IEEE Access · doi:10.1109/access.2023.3267746 · Cited by 24

Open-Domain Multi-Document Summarization via Information Extraction: Challenges and Prospects

Ji, H., Favre, B., Lin, W.-P., Gillick, D., Hakkani-Tur, D. Z., & Grishman, R. (2012) · Theory and applications of natural language processing · doi:10.1007/978-3-642-28569-1_9 · Cited by 22

A hybrid approach to protein name identification in biomedical texts

Seki, K., & Mostafa, J. (2004) · Information Processing & Management · doi:10.1016/j.ipm.2004.02.006 · Cited by 22

Event Linking: Grounding Event Reference in a News Archive

Nothman, J., Honnibal, M., Hachey, B., & Curran, J. (2012) · Cited by 22

Development and Evaluation of a Web Based Question Answering System for Arabic Language

Kurdi, H. A., Alkhaider, S., & Alfaifi, N. (2014) · doi:10.5121/csit.2014.4216 · Cited by 22

OTyper: A Neural Architecture for Open Named Entity Typing

Yuan, Z., & Downey, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.12070 · Cited by 22

REPENTINO – A Wide-Scope Gazetteer for Entity Recognition in Portuguese

Sarmento, L., Pinto, A. S., & Cabral, L. (2006) · Lecture notes in computer science · doi:10.1007/11751984_4 · Cited by 22

A probabilistic model for identifying protein names and their name boundaries

Seki, K., & Mostafa, J. (2004) · IEEE Computational Systems Bioinformatics Conference (CSB) · doi:10.1109/csb.2003.1227325 · Cited by 22

Prospects for in-depth story understanding by computerPreprint

Mueller, E. T. (2000) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0003003 · Cited by 22

A Machine Learning Approach to Anaphora Resolution Including Named Entity Recognition, PP Attachment Disambiguation, and Animacy Detection

Nøklestad, A. (2009) · NORA - Norwegian Open Research Archives · Cited by 22

Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition ModelsPreprint

Agarwal, O., Yang, Y., Wallace, B., & Nenkova, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.04123 · Cited by 24

An Approach for Named Entity Recognition in Poorly Structured Data

Freire, N., Borbinha, J. L., & Calado, P. P. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-30284-8_55 · Cited by 21

Spanners

Fagin, R., Kimelfeld, B., Reiss, F. R., & Vansummeren, S. (2013) · ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS) · doi:10.1145/2463664.2463665 · Cited by 21

Cleaning inconsistencies in information extraction via prioritized repairs

Fagin, R., Kimelfeld, B., Reiss, F. R., & Vansummeren, S. (2014) · ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS) · doi:10.1145/2594538.2594540 · Cited by 21

A Hybrid Approach for Entity Extraction in Code-Mixed Social Media Data.

Gupta, D. K., Shweta, S., Tripathi, S., Ekbal, A., & Bhattacharyya, P. (2016) · FIRE (Working Notes) · Cited by 21

Text Mining of Hazard and Operability Analysis Reports Based on Active Learning

Wang, Z., Zhang, B., & Gao, D. Q. (2021) · Processes · doi:10.3390/pr9071178 · Cited by 21

EventKGE: Event knowledge graph embedding with event causal transfer

Li, D., Li, Y., Zhang, X., Jia, W. P., & Ma, Z. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110917 · Cited by 21

Supersense Tagger for Italian

Picca, D., Gliozzo, A., & Ciaramita, M. (2008) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/4gj4mzyf6j6n · Cited by 21

Named Entity Recognition in Estonian

Tkachenko, A. I., Petmanson, T., & Laur, S. (2013) · Cited by 21

The effect of morphology in named entity recognition with sequence tagging

Güngör, O., Güngör, T., & Üsküdarlı, S. (2018) · Natural Language Engineering · doi:10.1017/s1351324918000281 · Cited by 22

Structured Named Entities in two distinct press corpora: Contemporary Broadcast News and Old Newspapers

Rosset, S., Grouin, C., Fort, K., Galibert, O., Kahn, J., & Zweigenbaum, P. (2012) · HAL · Cited by 21

Re-ranking algorithms for name tagging

Ji, H., Rudin, C. D., & Grishman, R. (2006) · doi:10.3115/1631828.1631835 · Cited by 21

Resource-aware annotation through active learning

Tomanek, K. (2010) · Technische Universität Dortmund Eldorado (Technische Universität Dortmund) · doi:10.17877/de290r-15670 · Cited by 21

A survey on natural language processing (nlp) and applications in insurancePreprint

Ly, A., Uthayasooriyar, B., & Wang, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.00462 · Cited by 27

Discovering latent commercial networks from online financial news articles

Xia, Y., Su, W., Lau, R. Y. K., & Liu, Y. (2011) · Enterprise Information Systems · doi:10.1080/17517575.2011.621093 · Cited by 20

Extraction of Temporal Information from Clinical Narratives

Moharasan, G., & Ho, T.-B. (2019) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-019-00049-0 · Cited by 20

Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence

Halterman, A., Keith, K. A., Sarwar, S. M., & O’Connor, B. (2021) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2021.findings-acl.371 · Cited by 20

Automatic Software Engineering Position Resume Screening using Natural Language Processing, Word Matching, Character Positioning, and Regex

Pant, D., Pokhrel, D., & Poudyal, P. (2022) · IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) · doi:10.1109/ic_aset53395.2022.9765916 · Cited by 20

What is policy content and how is the public's policy support? A policy cognition study based on natural language processing and social psychology

Zhou, L., Dai, D., Ren, J., Chen, X., & Chen, S. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.941762 · Cited by 22

Semi-Supervised Bootstrapped Syntax-Semantics-Based Approach for Agriculture Relation Extraction for Knowledge Graph Creation and Reasoning

Veena, G., Gupta, D., & Kanjirangat, V. (2023) · IEEE Access · doi:10.1109/access.2023.3339552 · Cited by 21

Extracting and Displaying Temporal and Geospatial Entities from Articles on Historical Events

Chasin, R., Woodward, D., Witmer, J., & Kalita, J. (2013) · The Computer Journal · doi:10.1093/comjnl/bxt112 · Cited by 20

Combining Visual and Textual Features for Information Extraction from Online Flyers

Apostolova, E., & Tomuro, N. (2014) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1206 · Cited by 20

Named Entity Recognition for Ontology Population using Background Knowledge from Wikipedia

Zhang, Z., & Ciravegna, F. (2011) · IGI Global eBooks · doi:10.4018/978-1-60960-625-1.ch005 · Cited by 20

Semantically linking events for massive scientific literature research

Zhang, J., Sun, Y., & Yao, C. (2017) · The Electronic Library · doi:10.1108/el-09-2016-0198 · Cited by 20

GRU based Named Entity Recognition System for Bangla Online Newspapers

Banik, N., & Rahman, M. H. H. (2018) · doi:10.1109/ciet.2018.8660795 · Cited by 21

Semantic Relations Between Nominals

Năstase, V., Nakov, P., Séaghdha, D. Ó., & Śzpakowicz, S. (2013) · Synthesis lectures on human language technologies · doi:10.2200/s00489ed1v01y201303hlt019 · Cited by 23

Maximum Entropy Named Entity Recognition for Czech Language

Konkol, M., & Konopík, M. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23538-2_26 · Cited by 20

A Novel Technique for Name Identification from Homeopathy Diagnosis Discussion Forum

Majumder, M., Barman, U., Prasad, R., Saurabh, K., & Saha, S. K. (2012) · Procedia Technology · doi:10.1016/j.protcy.2012.10.045 · Cited by 20

An annotation type system for a data-driven NLP pipeline

Hahn, U., Buyko, E., Tomanek, K., Piao, S. S., McNaught, J., Tsuruoka, Y., & Ananiadou, S. (2007) · Linguistic Annotation Workshop · doi:10.3115/1642059.1642064 · Cited by 20

Experience using GATE for NLP R&D

Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V., & Wilks, Y. A. (2000) · International Conference on Computational Linguistics · Cited by 20

Multi-Document Relationship Fusion via Constraints on Probabilistic Databases

Mann, G. (2007) · doi:10.21236/ada464777 · Cited by 20

New Methods, Current Trends and Software Infrastructure for NLPPreprint

Cunningham, H., Wilks, Y. A., & Gaizauskas, R. (1996) · arXiv (Cornell University) · doi:10.48550/arxiv.cmp-lg/9607025 · Cited by 20

Introduction: The Handbook of Linguistic Annotation

Ide, N. (2017) · Springer eBooks · doi:10.1007/978-94-024-0881-2_1 · Cited by 19

On the Use of Parsing for Named Entity Recognition

Alonso, M. Á., Gómez‐Rodríguez, C., & Vilares, J. (2021) · Applied Sciences · doi:10.3390/app11031090 · Cited by 23

Named Entity Recognition Architecture Combining Contextual and Global Features

Tran, H. T. H., Doucet, A., Sidère, N., Moreno, J. G., & Pollak, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-91669-5_21 · Cited by 19

Saga: A Platform for Continuous Construction and Serving of Knowledge at Scale

Ilyas, I. F., Rekatsinas, T., Konda, V., Pound, J., Qi, X., & Soliman, M. A. (2022) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/3514221.3526049 · Cited by 19

A Named Entity Labeler for German: Exploiting Wikipedia and Distributional Clusters

Chrupała, G., & Klakow, D. (2010) · Language Resources and Evaluation · Cited by 19

Incident threading for news passages

Feng, A., & Allan, J. (2009) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/1645953.1646118 · Cited by 19

Government Domain Named Entity Recognition for South African Languages

Eiselen, R. (2016) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/5mcyozqscxag · Cited by 19

Named entity recognition on Indonesian Twitter posts using long short-term memory networks

Rachman, V., Savitri, S., Augustianti, F., & Mahendra, R. (2017) · International Conference on Advanced Computer Science and Information Systems · doi:10.1109/icacsis.2017.8355038 · Cited by 19

Extraction of risk factors for cardiovascular diseases from Chinese electronic medical records

Su, J., Hu, J., Jiang, J., Xie, J., Yang, Y., He, B., Yang, J., & Guan, Y. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.01.007 · Cited by 19

A Golden Resource for Named Entity Recognition in Portuguese

Santos, D., & Cardoso, N. (2006) · Lecture notes in computer science · doi:10.1007/11751984_8 · Cited by 20

Automated Information Extraction from Empirical Software Engineering Literature: Is that possible?

Cruzes, D., Mendonca, M., Basili, V. R., Shull, F. J., & Jino, M. (2007) · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · doi:10.1109/esem.2007.62 · Cited by 19

Named entity extraction and disambiguation for informal text : the missing link

Habib, M. B. (2014) · doi:10.3990/1.9789036536479 · Cited by 19

From Entity Recognition to Entity Linking: A Survey of Advanced Entity Linking Techniques

Dai, H.-J., Wu, C.-Y., Tzong-han, R., & Hsu, W. (2013) · Cited by 18

Entity recognition of Chinese medical text based on multi-head self-attention combined with BILSTM-CRF

Li, C., & Ma, K. (2022) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2022103 · Cited by 18

SPARQL-QA-v2 system for Knowledge Base Question Answering

Borroto, M., & Ricca, F. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120383 · Cited by 20

Information Extraction from Invoices

Hamdi, A., Carel, E., Joseph, A., Coustaty, M., & Doucet, A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86331-9_45 · Cited by 24

Semantic Relatedness Approach for Named Entity Disambiguation

Gentile, A. L., Zhang, Z., Xia, L., & Iria, J. (2010) · Communications in computer and information science · doi:10.1007/978-3-642-15850-6_14 · Cited by 18

Incorporating Linguistic Expertise Using ILP for Named Entity Recognition in Data Hungry Indian Languages

Patel, A., Ramakrishnan, G., & Bhattacharya, P. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13840-9_16 · Cited by 18

Named Entity Corpus Construction using Wikipedia and DBpedia Ontology

Hahm, Y., Park, J., Lim, K., Kim, Y., Hwang, D., & Choi, K. (2014) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/2bqndhpkeevt · Cited by 18

Recognizing Named Entities in Turkish Tweets

Eken, B., & Tantug, A. C. (2015) · doi:10.5121/csit.2015.50213 · Cited by 18

A step towards information extraction: Named entity recognition in Bangla using deep learning

Karim, R., Islam, M. A., Simanto, S. R., Chowdhury, S. A., Roy, K., Neon, A. A., Hasan, M. S., Firoze, A., & Rahman, R. M. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-179349 · Cited by 18

Developing NLP Tools for Genome Informatics: An Information Extraction Perspective.

Hishiki, T., Collier, N., Nobata, C., Okazaki-Ohta, T., Ogata, N., Sekimizu, Steiner, R., Park, & Tsujii, J. (1998) · PubMed · Cited by 18

Building a Fine-Grained Entity Typing System Overnight for a New X (X = Language, Domain, Genre)Preprint

Huang, L., May, J., Pan, X., & Ji, H. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1603.03112 · Cited by 18

A BERT-Based Named Entity Recognition in Chinese Electronic Medical Record

Wang, Q., & Haihong, E. (2020) · International Conference on Computing and Pattern Recognition (ICCPR) · doi:10.1145/3436369.3436390 · Cited by 19

Unsupervised Named Entity Recognition and Disambiguation: An Application to Old French Journals

Mosallam, Y., Abi-Haidar, A., & Ganascia, J. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-08976-8_2 · Cited by 18

Mining activation force defined dependency patterns for relation extraction

Zhang, C., Zhang, Y., Xu, W., Ma, Z., Leng, Y., & Guo, J. H. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.06.012 · Cited by 17

Creating an Extended Named Entity Dictionary from Wikipedia

Higashinaka, R., Sadamitsu, K., Saito, K., Makino, T., & Matsuo, Y. (2012) · International Conference on Computational Linguistics · Cited by 17

A Boundary Assembling Method for Nested Biomedical Named Entity Recognition

Chen, Y., Hu, Y., Li, Y., Huang, R., Qin, Y., Wu, Y., Zheng, Q., & Chen, P. (2020) · IEEE Access · doi:10.1109/access.2020.3040182 · Cited by 18

Pattern-based Extraction of Named Entities in Thai News Documents

Tongtep, N., & Theeramunkong, T. (2010) · Science & Technology Asia · Cited by 17

Concepticons vs. lexicons: An architecture for multilingual information extraction

Gaizauskas, R., Humphreys, K., Azzam, S., & Wilks, Y. A. (1997) · Lecture notes in computer science · doi:10.1007/3-540-63438-x_3 · Cited by 17

Focusing on scenario recognition in information extraction

Yankova, M., & Boytcheva, S. (2003) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.3115/1067737.1067744 · Cited by 17

Mining Textual Data to Boost Information Access in OSINT

Neri, F., & Geraci, P. (2009) · International Conference on Information Visualisation (IV) · doi:10.1109/iv.2009.99 · Cited by 17

Coreference Resolution: To What Extent Does It Help NLP Applications?

Mitkov, R., Evans, R., Orǎsan, C., Dornescu, I., & Rios, M. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-32790-2_2 · Cited by 17

Machine Learning for Information Extraction in Genomics — State of the Art and Perspectives

Nédellec, C. (2004) · Studies in fuzziness and soft computing · doi:10.1007/978-3-540-45219-5_8 · Cited by 17

Test-driving tanka: Evaluating a semi-automatic system of text analysis for knowledge acquisition

Barker, K., Delisle, S., & Śzpakowicz, S. (1998) · Lecture notes in computer science · doi:10.1007/3-540-64575-6_40 · Cited by 17

SIEMÊS – A Named-Entity Recognizer for Portuguese Relying on Similarity Rules

Sarmento, L. (2006) · Lecture notes in computer science · doi:10.1007/11751984_10 · Cited by 17

KazNERD: Kazakh Named Entity Recognition Dataset

Yeshpanov, R., Khassanov, Y., & Varol, H. A. (2022) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/5398gpuejb6t · Cited by 24

A Systematic Review of Artificial Intelligence Applied to Compliance: Fraud Detection in Cryptocurrency Transactions

Valencia, L. R., Arellano, M. J. O., Figueroa, S. A. G., Nuño, C. M., Monsalve, B., Corrales-Paredes, A., Rosende, S. B., López-López, J. M., Puertas, E., & Alfaroviz, A. L. (2025) · Journal of risk and financial management · doi:10.3390/jrfm18110612 · Cited by 19

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems

Huang, L., May, J., Pan, X., Ji, H., Ren, X., Han, J., Zhao, L., & Hendler, J. (2017) · Big Data · doi:10.1089/big.2017.0012 · Cited by 16

CasANER: Arabic Named Entity Recognition Tool

Mesmia, F. B., Haddar, K., Friburger, N., & Maurel, D. (2017) · Studies in computational intelligence · doi:10.1007/978-3-319-67056-0_10 · Cited by 16

Named Entity Recognition using Deep Learning: A Review

Ali, S., Masood, K., Riaz, A., & Saud, A. (2022) · International Conference on Business Analytics for Technology and Security (ICBATS) · doi:10.1109/icbats54253.2022.9759051 · Cited by 16

Named Entity Recognition Datasets: A Classification Framework

Zhang, Y., & Xiao, G. (2024) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-024-00456-1 · Cited by 16

VN-KIM IE: Automatic Extraction of Vietnamese Named-Entities on the Web

Nguyen, T.-V. T., & Cao, T. H. (2007) · New Generation Computing · doi:10.1007/s00354-007-0018-4 · Cited by 16

A comparative study between possibilistic and probabilistic approaches for monolingual word sense disambiguation

Elayeb, B., Bounhas, I., Khiroun, O. B., Evrard, F., & Saoud, N. B. B. (2014) · Knowledge and Information Systems · doi:10.1007/s10115-014-0753-z · Cited by 16

Extended Named Entities Annotation on OCRed Documents: From Corpus Constitution to Evaluation Campaign

Galibert, O., Rosset, S., Grouin, C., Zweigenbaum, P., & Quintard, L. (2012) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/4ad43vah7ajs · Cited by 16

Annotated Corpora and Annotation Tools

Poesio, M., Pradhan, S., Recasens, M. V., Rodríguez, K. J., & Versley, Y. (2016) · Theory and applications of natural language processing · doi:10.1007/978-3-662-47909-4_4 · Cited by 16

Building text-based temporally linked event network for scientific big data analytics

Zhang, J., Yao, C., Sun, Y., & Fang, Z. (2016) · Personal and Ubiquitous Computing · doi:10.1007/s00779-016-0940-x · Cited by 19

Design of the MUC-6 evaluation

Grishman, R., & Sundheim, B. M. (1995) · Message Understanding Conference (MUC) · doi:10.3115/1072399.1072401 · Cited by 107

THE MUC EVALUATION S

Ralph Grishma, N., & Beth Sundhei, M. (2014)

grishman©cs, nyu. edu

Grishman, R., & Sundheim, B. (2013)

Evaluating message understanding systems

ChinchorNancy, LewisDavid, D., & HirschmanLynette (1993) · Computational Linguistics · doi:10.5555/972487.972488 · Cited by 13

Message Understanding Conference (MUC) 6 Additional News Text

Chinchor, N. A., & Sundheim, B. (2020) · Americanae (AECID Library) · doi:10.35111/ajtx-gn82