{"title":"法语小说中人物与地点识别的简单规则","authors":"Cyril Bornet, F. Kaplan","doi":"10.3389/fdigh.2017.00006","DOIUrl":null,"url":null,"abstract":"This article describes a simple system for automatically extracting and classifying named entities in French novels. The solution presented combines a set of different standalone classifiers within a meta-recognition system. The system is tested on 35 classic French novels, representing 5 million words and 3 700 names of people and places. The results demonstrate that although none of the standalone methods clearly outperform the others, their combined classification offers a robust solution in this context.","PeriodicalId":227954,"journal":{"name":"Frontiers Digit. Humanit.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"A Simple Set of Rules for Characters and Place Recognition in French Novels\",\"authors\":\"Cyril Bornet, F. Kaplan\",\"doi\":\"10.3389/fdigh.2017.00006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes a simple system for automatically extracting and classifying named entities in French novels. The solution presented combines a set of different standalone classifiers within a meta-recognition system. The system is tested on 35 classic French novels, representing 5 million words and 3 700 names of people and places. The results demonstrate that although none of the standalone methods clearly outperform the others, their combined classification offers a robust solution in this context.\",\"PeriodicalId\":227954,\"journal\":{\"name\":\"Frontiers Digit. Humanit.\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers Digit. Humanit.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/fdigh.2017.00006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers Digit. Humanit.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdigh.2017.00006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Simple Set of Rules for Characters and Place Recognition in French Novels
This article describes a simple system for automatically extracting and classifying named entities in French novels. The solution presented combines a set of different standalone classifiers within a meta-recognition system. The system is tested on 35 classic French novels, representing 5 million words and 3 700 names of people and places. The results demonstrate that although none of the standalone methods clearly outperform the others, their combined classification offers a robust solution in this context.