{"title":"从非结构化文本中提取语义角色信息","authors":"Diana Trandabat, A. Trandabăț","doi":"10.1109/SMAP.2011.20","DOIUrl":null,"url":null,"abstract":"Shallow semantic parsing of natural language processing is an important component in all kind of NLP applications and Semantic Role Labeling in particular, is an active research topic. This paper describes a rule-based Semantic Role Labeling system aimed at extracting semantic information from texts. The input text is processed by exploiting part of speech information and syntactic dependencies in order to identify semantic roles. The system's architecture is presented and the results and further developments are discussed.","PeriodicalId":346975,"journal":{"name":"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization","volume":"179 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extracting Semantic Role Information from Unstructured Texts\",\"authors\":\"Diana Trandabat, A. Trandabăț\",\"doi\":\"10.1109/SMAP.2011.20\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Shallow semantic parsing of natural language processing is an important component in all kind of NLP applications and Semantic Role Labeling in particular, is an active research topic. This paper describes a rule-based Semantic Role Labeling system aimed at extracting semantic information from texts. The input text is processed by exploiting part of speech information and syntactic dependencies in order to identify semantic roles. The system's architecture is presented and the results and further developments are discussed.\",\"PeriodicalId\":346975,\"journal\":{\"name\":\"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization\",\"volume\":\"179 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMAP.2011.20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Workshop on Semantic Media Adaptation and Personalization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMAP.2011.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting Semantic Role Information from Unstructured Texts
Shallow semantic parsing of natural language processing is an important component in all kind of NLP applications and Semantic Role Labeling in particular, is an active research topic. This paper describes a rule-based Semantic Role Labeling system aimed at extracting semantic information from texts. The input text is processed by exploiting part of speech information and syntactic dependencies in order to identify semantic roles. The system's architecture is presented and the results and further developments are discussed.
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