Automatic Extraction and Linking of Person Names in Legal Text Export

@inproceedings{citeulike:3988319, abstract = {This paper describes an application that creates hypertext links in text from named individuals to personal biographies. Our system creates these links by extracting MUC-style templates from text and linking them to biographical information in a relational database. The linking technique we use is based on a na\"{i}ve Bayesian inference network. In particular, our application involves the extraction of attorney and judge names from American caselaw and the creation of links between the names and a file containing their biographies. It is a real world commercial application that involves the automatic creation of millions of reliable hypertext links in millions of documents. The techniques described in this paper could be applied to other domains besides law. Our experiments show that, by combining information extraction and Bayesian record linkage techniques, we can automatically extract and match attorney and judge names in caselaw to biographies with an accuracy rivaling that of a human expert.}, author = {Dozier, Christopher and Haschart, Robert}, booktitle = {in Proceedings of RIAO \&\#039;2000; Content Based Multimedia Information Access}, citeulike-article-id = {3988319}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.7431}, keywords = {legal, ner}, pages = {1305--1321}, posted-at = {2009-01-31 18:11:24}, priority = {2}, title = {Automatic Extraction and Linking of Person Names in Legal Text}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.7431}, year = {2000} }

TY - CONF ID - citeulike:3988319 L3 - citeulike-article-id:3988319 N2 - This paper describes an application that creates hypertext links in text from named individuals to personal biographies. Our system creates these links by extracting MUC-style templates from text and linking them to biographical information in a relational database. The linking technique we use is based on a naïve Bayesian inference network. In particular, our application involves the extraction of attorney and judge names from American caselaw and the creation of links between the names and a file containing their biographies. It is a real world commercial application that involves the automatic creation of millions of reliable hypertext links in millions of documents. The techniques described in this paper could be applied to other domains besides law. Our experiments show that, by combining information extraction and Bayesian record linkage techniques, we can automatically extract and match attorney and judge names in caselaw to biographies with an accuracy rivaling that of a human expert. EP - 1321 TI - Automatic Extraction and Linking of Person Names in Legal Text T2 - in Proceedings of RIAO '2000; Content Based Multimedia Information Access SP - 1305 KW - legal KW - ner AU - Dozier, Christopher AU - Haschart, Robert PY - 2000/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.7431 ER -