{"title":"基于依赖语法规则的人际关系抽取本体","authors":"Long He, Likun Qiu","doi":"10.1145/3106426.3109050","DOIUrl":null,"url":null,"abstract":"This paper proposed a novel scheme for extracting character relation from unstructured text based on dependency grammar rules. First of all, we took the Three Kingdoms characters as our research object, then selected articles containing target relationships and thus constructed a corpus consisting of 1000 sentences. Secondly, We analyzed the corpus and developed a set of dependent grammar rules for relation extraction. Finally, we proposed a system, which makes it possible for computers to automatically extract and identify character relationships.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ontology of human relation extraction based on dependency syntax rules\",\"authors\":\"Long He, Likun Qiu\",\"doi\":\"10.1145/3106426.3109050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed a novel scheme for extracting character relation from unstructured text based on dependency grammar rules. First of all, we took the Three Kingdoms characters as our research object, then selected articles containing target relationships and thus constructed a corpus consisting of 1000 sentences. Secondly, We analyzed the corpus and developed a set of dependent grammar rules for relation extraction. Finally, we proposed a system, which makes it possible for computers to automatically extract and identify character relationships.\",\"PeriodicalId\":20685,\"journal\":{\"name\":\"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3106426.3109050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3106426.3109050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontology of human relation extraction based on dependency syntax rules
This paper proposed a novel scheme for extracting character relation from unstructured text based on dependency grammar rules. First of all, we took the Three Kingdoms characters as our research object, then selected articles containing target relationships and thus constructed a corpus consisting of 1000 sentences. Secondly, We analyzed the corpus and developed a set of dependent grammar rules for relation extraction. Finally, we proposed a system, which makes it possible for computers to automatically extract and identify character relationships.
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