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The MACE-AL-TREE source code is licensed under MIT License.
\r\n\r\nMIT License\r\n\r\nCopyright (c) 2020 Rehbein, Ines; Ruppenhofer, Josef; Steen, Julius\r\n\r\nPermission is hereby granted, free of charge, to any person obtaining a copy\r\nof this software and associated documentation files (the \"Software\"), to deal\r\nin the Software without restriction, including without limitation the rights\r\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\r\ncopies of the Software, and to permit persons to whom the Software is\r\nfurnished to do so, subject to the following conditions:\r\n\r\nThe above copyright notice and this permission notice shall be included in all\r\ncopies or substantial portions of the Software.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\r\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\r\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\r\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\r\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\r\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\r\nSOFTWARE.\r\n\r\n","fileAccessRequest":false,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"MACE-AL"},{"typeName":"subtitle","multiple":false,"typeClass":"primitive","value":"A method for detecting errors in automatic annotations (POS, NER etc.)"},{"typeName":"alternativeURL","multiple":false,"typeClass":"primitive","value":"https://github.com/julmaxi/MACE-AL"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Rehbein, Ines"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Leibniz Institute for the German Language"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Ruppenhofer, Josef"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Leibniz Institute for the German Language"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Steen, Julius"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Department of Computational Linguistics, Heidelberg University, Germany"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Rehbein, Ines"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"Leibniz Institute for the German Language"},"datasetContactEmail":{"typeName":"datasetContactEmail","multiple":false,"typeClass":"primitive","value":"rehbein@cl.uni-heidelberg.de"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Arts and Humanities","Computer and Information Science"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Annotation tool"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Annotation noise"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Error detection"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Automatically annotated text"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Annotation noise"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Error detection in automatic annotations"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Error detection for POS, NER etc."}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Rehbein, I. and Ruppenhofer, J. (2017). Detecting annotation noise in automatically labelled data. In Proceedings of the 55th annual meeting of the Association for Computational Linguistics (ACL'17), pages 1160–1170, July 30-August 4, 2017, Vancouver, Canada."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"url"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://www.aclweb.org/anthology/P17-1107.pdf"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2017"},{"typeName":"productionPlace","multiple":true,"typeClass":"primitive","value":["Leibniz Institute for the German Language"]},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2019-07-31"},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["python code"]},{"typeName":"relatedMaterial","multiple":true,"typeClass":"primitive","value":["MACE (Multi-Annotator Competence Estimation): A generative modelfor Multi-Annotator Competence Estimation
\r\nLink to resource: https://github.com/dirkhovy/MACE
\r\nReference:
\r\nHovy, D., Berg-Kirkpatrick, T., Vaswani, A., and Eduard Hovy (2013). Learning whom to trust with MACE. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1120–1130, June 9–14, 2013, Atlanta, Georgia. https://www.aclweb.org/anthology/N13-1132.pdf
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