Fuzziness, as intrinsic property of natural language, appears to be an extremely pervasive phenomenon in language communication with no exception of news reporting. To some extent, the usage of a great number of fuzzy...Fuzziness, as intrinsic property of natural language, appears to be an extremely pervasive phenomenon in language communication with no exception of news reporting. To some extent, the usage of a great number of fuzzy expressions in news reporting reflects the property of reporter as functional entity. On different occasions, reporters, when reporting news, may play such three kinds of roles as the first information source, the second information source or the virtual interpreter. The different roles-playing determines the pragmatic intention of fuzzy language in news reporting.展开更多
English practice teaching has outstanding superiority over the extension and supplementation of English classroom teaching, and practice teaching is an indispensably important part of college English teaching. To stud...English practice teaching has outstanding superiority over the extension and supplementation of English classroom teaching, and practice teaching is an indispensably important part of college English teaching. To students, cultivation of the ability of practice is vital, affecting students＇ employment and future. To universities, teaching quality has a direct impact on the development prospect of schools and decides the future of schools. Moreover, local normal universities also undertake a more important task to cultivate local high-quality talents teaching primary and junior high schools. These teaching talents undertake the great task of English teaching over primary and junior high school students, and thus the construction and implementation of practice teaching system of English major in normal universities are urgent.展开更多
Named entity recognition （NER） is a core component in many natural language processing applications. Most NER systems rely on supervised machine learning methods, which depend on time-consuming and expensive annotat...Named entity recognition （NER） is a core component in many natural language processing applications. Most NER systems rely on supervised machine learning methods, which depend on time-consuming and expensive annotations in different languages and domains. This paper presents a method for automatically building silver-standard NER corpora from Chinese Wikipedia. We refine novel and language-dependent features by exploiting the text and structure of Chinese Wikipedia. To reduce tagging errors caused by entity classification, we design four types of heuristic rules based on the characteristics of Chinese Wikipedia and train a supervised NE classifier, and a combined method is used to improve the precision and coverage. Then, we realize type identification of implicit mention by using boundary information of outgoing links. By selecting the sentences related with the domains of test data, we can train better NER models. In the experiments, large-scale NER corpora containing 2.3 million sentences are built from Chinese Wikipedia. The results show the effectiveness of automatically annotated corpora, and the trained NER models achieve the best performance when combining our silver-standard corpora with gold-standard corpora.展开更多
文摘Fuzziness, as intrinsic property of natural language, appears to be an extremely pervasive phenomenon in language communication with no exception of news reporting. To some extent, the usage of a great number of fuzzy expressions in news reporting reflects the property of reporter as functional entity. On different occasions, reporters, when reporting news, may play such three kinds of roles as the first information source, the second information source or the virtual interpreter. The different roles-playing determines the pragmatic intention of fuzzy language in news reporting.
文摘English practice teaching has outstanding superiority over the extension and supplementation of English classroom teaching, and practice teaching is an indispensably important part of college English teaching. To students, cultivation of the ability of practice is vital, affecting students＇ employment and future. To universities, teaching quality has a direct impact on the development prospect of schools and decides the future of schools. Moreover, local normal universities also undertake a more important task to cultivate local high-quality talents teaching primary and junior high schools. These teaching talents undertake the great task of English teaching over primary and junior high school students, and thus the construction and implementation of practice teaching system of English major in normal universities are urgent.
基金Project supported by the National Natural Science Foundation of China(No.14BXW028)
文摘Named entity recognition （NER） is a core component in many natural language processing applications. Most NER systems rely on supervised machine learning methods, which depend on time-consuming and expensive annotations in different languages and domains. This paper presents a method for automatically building silver-standard NER corpora from Chinese Wikipedia. We refine novel and language-dependent features by exploiting the text and structure of Chinese Wikipedia. To reduce tagging errors caused by entity classification, we design four types of heuristic rules based on the characteristics of Chinese Wikipedia and train a supervised NE classifier, and a combined method is used to improve the precision and coverage. Then, we realize type identification of implicit mention by using boundary information of outgoing links. By selecting the sentences related with the domains of test data, we can train better NER models. In the experiments, large-scale NER corpora containing 2.3 million sentences are built from Chinese Wikipedia. The results show the effectiveness of automatically annotated corpora, and the trained NER models achieve the best performance when combining our silver-standard corpora with gold-standard corpora.
