{"title":"使用Φ2 Statistics构建括号语料库","authors":"Yue-Shi Lee, Hsin-Hsi Chen","doi":"10.30019/IJCLCLP.199708.0001","DOIUrl":null,"url":null,"abstract":"Research based on treebanks is ongoing for many natural language applications. However, the work involved in building a large-scale treebank is laborious and time-consuming. Thus, speeding up the process of building a treebank has become an important task. This paper proposes two versions of probabilistic chunkers to aid the development of a bracketed corpus. The basic version partitions part-of-speech sequences into chunk sequences, which form a partially bracketed corpus. Applying the chunking action recursively, the recursive version generates a fully bracketed corpus. Rather than using a treebank as a training corpus, a corpus, which is tagged with part-of-speech information only, is used. The experimental results show that the probabilistic chunker has a correct rate of more than 94% in producing a partially bracketed corpus and also gives very encouraging results in generating a fully bracketed corpus. These two versions of chunkers are simple but effective and can also be applied to many natural language applications.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building a Bracketed Corpus Using Φ2 Statistics\",\"authors\":\"Yue-Shi Lee, Hsin-Hsi Chen\",\"doi\":\"10.30019/IJCLCLP.199708.0001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research based on treebanks is ongoing for many natural language applications. However, the work involved in building a large-scale treebank is laborious and time-consuming. Thus, speeding up the process of building a treebank has become an important task. This paper proposes two versions of probabilistic chunkers to aid the development of a bracketed corpus. The basic version partitions part-of-speech sequences into chunk sequences, which form a partially bracketed corpus. Applying the chunking action recursively, the recursive version generates a fully bracketed corpus. Rather than using a treebank as a training corpus, a corpus, which is tagged with part-of-speech information only, is used. The experimental results show that the probabilistic chunker has a correct rate of more than 94% in producing a partially bracketed corpus and also gives very encouraging results in generating a fully bracketed corpus. These two versions of chunkers are simple but effective and can also be applied to many natural language applications.\",\"PeriodicalId\":436300,\"journal\":{\"name\":\"Int. J. Comput. Linguistics Chin. Lang. Process.\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Comput. Linguistics Chin. Lang. Process.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30019/IJCLCLP.199708.0001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Linguistics Chin. Lang. Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30019/IJCLCLP.199708.0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research based on treebanks is ongoing for many natural language applications. However, the work involved in building a large-scale treebank is laborious and time-consuming. Thus, speeding up the process of building a treebank has become an important task. This paper proposes two versions of probabilistic chunkers to aid the development of a bracketed corpus. The basic version partitions part-of-speech sequences into chunk sequences, which form a partially bracketed corpus. Applying the chunking action recursively, the recursive version generates a fully bracketed corpus. Rather than using a treebank as a training corpus, a corpus, which is tagged with part-of-speech information only, is used. The experimental results show that the probabilistic chunker has a correct rate of more than 94% in producing a partially bracketed corpus and also gives very encouraging results in generating a fully bracketed corpus. These two versions of chunkers are simple but effective and can also be applied to many natural language applications.