{"_id":"g4BFu64jHGtSdjRMH","bibbaseid":"rssler-usingmarkovmodelsfornamedentityrecognitioningermannewspapers-2002","authorIDs":[],"author_short":["Rössler, M."],"bibdata":{"title":"Using markov models for named entity recognition in German newspapers","type":"inProceedings","year":"2002","pages":"29–37","websites":"http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.8562&rep=rep1&type=pdf","publisher":"Citeseer","id":"93de4aff-1b3b-35f7-8d55-836b2773ec2c","created":"2012-01-21T12:35:31.000Z","file_attached":false,"profile_id":"5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6","group_id":"066b42c8-f712-3fc3-abb2-225c158d2704","last_modified":"2017-03-14T14:36:19.698Z","tags":"named entity recognition","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Rossler2002","private_publication":false,"abstract":"This paper describes preliminary experiments for a system of named entity recognition in German newspapers. The approach is based on second order Markov Models trained on a tagged corpus. No gazetteers are used, only a list of words providing evidence is integrated. These words are extracted by statistical methods from an annotated corpus. The input basically consists of a part of speech tagged text, except the words occurring in the gained list, which replace the tags with their word form. The experiments investigate in how far such a limited approach is suitable for German and show that it provides some evidence. However, of course, it has to be enhanced.","bibtype":"inProceedings","author":"Rössler, Marc","booktitle":"Proceedings of the Workshop on Machine Learning Approaches in Computational Linguistics","bibtex":"@inProceedings{\n title = {Using markov models for named entity recognition in German newspapers},\n type = {inProceedings},\n year = {2002},\n pages = {29–37},\n websites = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.8562&rep=rep1&type=pdf},\n publisher = {Citeseer},\n id = {93de4aff-1b3b-35f7-8d55-836b2773ec2c},\n created = {2012-01-21T12:35:31.000Z},\n file_attached = {false},\n profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},\n group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},\n last_modified = {2017-03-14T14:36:19.698Z},\n tags = {named entity recognition},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Rossler2002},\n private_publication = {false},\n abstract = {This paper describes preliminary experiments for a system of named entity recognition in German newspapers. The approach is based on second order Markov Models trained on a tagged corpus. No gazetteers are used, only a list of words providing evidence is integrated. These words are extracted by statistical methods from an annotated corpus. The input basically consists of a part of speech tagged text, except the words occurring in the gained list, which replace the tags with their word form. The experiments investigate in how far such a limited approach is suitable for German and show that it provides some evidence. However, of course, it has to be enhanced.},\n bibtype = {inProceedings},\n author = {Rössler, Marc},\n booktitle = {Proceedings of the Workshop on Machine Learning Approaches in Computational Linguistics}\n}","author_short":["Rössler, M."],"urls":{"Website":"http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.92.8562&rep=rep1&type=pdf"},"bibbaseid":"rssler-usingmarkovmodelsfornamedentityrecognitioningermannewspapers-2002","role":"author","downloads":0,"html":""},"bibtype":"inProceedings","creationDate":"2020-02-06T23:48:11.925Z","downloads":0,"keywords":[],"search_terms":["using","markov","models","named","entity","recognition","german","newspapers","rössler"],"title":"Using markov models for named entity recognition in German newspapers","year":2002}