{"title":"计算语义学:如何解决超感的悬念","authors":"Aishwarya Asesh","doi":"10.1109/AIKE48582.2020.00024","DOIUrl":null,"url":null,"abstract":"Understanding human language is a difficult task, with varied fields of study which aim at explaining and researching the human language principles. Linguistics, Psychology and Computer Science all use domain specific tools to describe and model language. Natural Language Processing is the field which aims at using computational mechanisms to process naturally occurring human language. Modeling syntax gives language structure. Using general sense classes, or \"supersenses\" one can potentially enrich texts with semantic information. Given a sentence with syntactic information, and a closed set of semantic supersenses, can a supersense tagged sentence be derived? Furthermore, can one demarcate boundaries for multiword expressions? The aim of this research study is to create a multiword expression boundary and supersense labelled sentence by training with Word, part-of-speech (POS), multiword expression (MWE) and supersense tagged training data. The semantically tagged sentences can be used for many tasks such as question answering systems, information retrieval, discourse and sentiment analysis.","PeriodicalId":370671,"journal":{"name":"2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Semantics: How to solve the suspense of supersense\",\"authors\":\"Aishwarya Asesh\",\"doi\":\"10.1109/AIKE48582.2020.00024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding human language is a difficult task, with varied fields of study which aim at explaining and researching the human language principles. Linguistics, Psychology and Computer Science all use domain specific tools to describe and model language. Natural Language Processing is the field which aims at using computational mechanisms to process naturally occurring human language. Modeling syntax gives language structure. Using general sense classes, or \\\"supersenses\\\" one can potentially enrich texts with semantic information. Given a sentence with syntactic information, and a closed set of semantic supersenses, can a supersense tagged sentence be derived? Furthermore, can one demarcate boundaries for multiword expressions? The aim of this research study is to create a multiword expression boundary and supersense labelled sentence by training with Word, part-of-speech (POS), multiword expression (MWE) and supersense tagged training data. The semantically tagged sentences can be used for many tasks such as question answering systems, information retrieval, discourse and sentiment analysis.\",\"PeriodicalId\":370671,\"journal\":{\"name\":\"2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIKE48582.2020.00024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIKE48582.2020.00024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computational Semantics: How to solve the suspense of supersense
Understanding human language is a difficult task, with varied fields of study which aim at explaining and researching the human language principles. Linguistics, Psychology and Computer Science all use domain specific tools to describe and model language. Natural Language Processing is the field which aims at using computational mechanisms to process naturally occurring human language. Modeling syntax gives language structure. Using general sense classes, or "supersenses" one can potentially enrich texts with semantic information. Given a sentence with syntactic information, and a closed set of semantic supersenses, can a supersense tagged sentence be derived? Furthermore, can one demarcate boundaries for multiword expressions? The aim of this research study is to create a multiword expression boundary and supersense labelled sentence by training with Word, part-of-speech (POS), multiword expression (MWE) and supersense tagged training data. The semantically tagged sentences can be used for many tasks such as question answering systems, information retrieval, discourse and sentiment analysis.