{"title":"自然语言处理在古代语言教学中的应用","authors":"K. Schulz","doi":"10.38072/2703-0784/p19","DOIUrl":null,"url":null,"abstract":"\n Konstantin Schulz shows various applications of natural language processing (NLP) to the field of Classics, especially to Latin texts. He addresses different levels of linguistic \n analysis while also highlighting educational benefits and important theoretical pitfalls, especially in vocabulary learning. NLP can solve some problems reasonably well, like tailoring \n exercises to the learners' current state of knowledge. However, some tasks still prove to be too difficult for machines at the moment, e.g. reliable and highly accurate parsing of syntax \n for historical languages.\n","PeriodicalId":422231,"journal":{"name":"Teaching Classics in the Digital Age","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Natural Language Processing for Teaching Ancient Languages\",\"authors\":\"K. Schulz\",\"doi\":\"10.38072/2703-0784/p19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Konstantin Schulz shows various applications of natural language processing (NLP) to the field of Classics, especially to Latin texts. He addresses different levels of linguistic \\n analysis while also highlighting educational benefits and important theoretical pitfalls, especially in vocabulary learning. NLP can solve some problems reasonably well, like tailoring \\n exercises to the learners' current state of knowledge. However, some tasks still prove to be too difficult for machines at the moment, e.g. reliable and highly accurate parsing of syntax \\n for historical languages.\\n\",\"PeriodicalId\":422231,\"journal\":{\"name\":\"Teaching Classics in the Digital Age\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teaching Classics in the Digital Age\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38072/2703-0784/p19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teaching Classics in the Digital Age","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38072/2703-0784/p19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Natural Language Processing for Teaching Ancient Languages
Konstantin Schulz shows various applications of natural language processing (NLP) to the field of Classics, especially to Latin texts. He addresses different levels of linguistic
analysis while also highlighting educational benefits and important theoretical pitfalls, especially in vocabulary learning. NLP can solve some problems reasonably well, like tailoring
exercises to the learners' current state of knowledge. However, some tasks still prove to be too difficult for machines at the moment, e.g. reliable and highly accurate parsing of syntax
for historical languages.