Societal values are polysemous and its dimensions are imported into advertising to give it rich content. The polysemous character makes it sensitive and complex phenomena. For instance, value that is acceptable in the...Societal values are polysemous and its dimensions are imported into advertising to give it rich content. The polysemous character makes it sensitive and complex phenomena. For instance, value that is acceptable in the western part of Nigeria may be unacceptable in the north or east. This clearly implies that value, although may be of the people, is relative and subjective. This study made use of survey research design with a single research question set to guide it. Data were collected from 362 respondents who were purposively selected in the study area （Lagos State, Nigeria） as sample size. Data gathering were done on the field with the aid of questionnaire and analyzed with descriptive statistics. Specifically, a Table of frequency and percentage distribution was employed and scoring of variables was done vis-h-vis the responses of the consumers of staple commodities to look at the extent to which societal values have influenced product advertisements in the State. The Mean and standard deviation was calculated. The result of the study presented in Table 1 shows that all the societal values scoped for this study （culture, moral, religion, taste, language and color） influence consumers in one way or the other but the portrayal of religious design concept to influence consumers to patronize staple commodities ranked best of all. The study observed that of all the societal values traceable to advertising campaign in Lagos State, religion-inclined advertising designs are gaining a rising number of influences. It therefore concludes that religious and cultural designs, when appropriately applied help outdoor advertising to thrive well in Lagos State.展开更多
Phrasal verbs, accounting for a large proportion in modem language, pose numerous challenges to foreign language learners of English, who usually view verb ＋ particle combinations random. The issue of unpredictabilit...Phrasal verbs, accounting for a large proportion in modem language, pose numerous challenges to foreign language learners of English, who usually view verb ＋ particle combinations random. The issue of unpredictability is obviously a problem for English learners. Making things worse, many phrasal verbs are polysemous. For one thing, one phrasal verb may have multiple meanings; for another, several phrasal verbs may have the same or similar meanings. While the fast development of cognitive linguistics theory provides a new perspective for the study of English polysemous phrasal verbs. Researchers apply cognitive linguistic theory into second language acquisition and find that the multiple senses of phrasal verbs are actually systematic and motivated. The present study summarizes studies of polysemous phrasal verbs from the perspective of traditional approaches and cognitive approaches as well as the empirical studies based on it and analyzes the shortage of traditional approaches on phrasal verbs. Lastly, this paper illustrates some drawbacks of empirical study based on the assessment of Boers （2011） and points out some suggestions on further studies.展开更多
The researcher analyzes the distribution and types of image-schema-based metaphorical extension(or IS-based meta-extension) in the semantic extension of 203 polysemous verbs,which can be named as PVs and are randomly ...The researcher analyzes the distribution and types of image-schema-based metaphorical extension(or IS-based meta-extension) in the semantic extension of 203 polysemous verbs,which can be named as PVs and are randomly selected from Longman Dictionary of Contemporary English(2nd Edition,1993).She finds that IS-based meta-extension is pervasive in the semantic extension of verbal polysemy.Specif ically,she f inds 77.83% of the samples can be analyzed in terms of IS-based Meta-extension,and PVs that can be analyzed in terms of path-IS-based,force-IS-based,containerIS-based,path+force-IS-based,and path+container-IS-based metaphorical extension,together making up 70.44% of the samples.展开更多
Polysemic words appear in news English with high-frequency.So,how to determine the exact meaning of a polysemic word in the news and put it into proper Chinese causes much trouble and frustration to readers.This paper...Polysemic words appear in news English with high-frequency.So,how to determine the exact meaning of a polysemic word in the news and put it into proper Chinese causes much trouble and frustration to readers.This paper summarizes some effective translating strategies of polysemic words from English to Chinese.They include:translating based on collocation,translating based on grammar,translating based on background knowledge,translating based on logical relation,and translating based on register.展开更多
Event extraction(EE)is a complex natural language processing(NLP)task that aims at identifying and classifying triggers and arguments in raw text.The polysemy of triggers and arguments stands out as one of the key cha...Event extraction(EE)is a complex natural language processing(NLP)task that aims at identifying and classifying triggers and arguments in raw text.The polysemy of triggers and arguments stands out as one of the key challenges affecting the precise extraction of events.Existing approaches commonly consider the semantic distribution of triggers and arguments to be balanced.However,the sample quantities of different semantics in the same trigger or argument vary in real-world scenarios,leading to a biased semantic distribution.The bias introduces two challenges:(1)low-frequency semantics is difficult to identify;(2)high-frequency semantics is often mistakenly identified.To tackle these challenges,we propose an adaptive learning method with the reward-penalty mechanism for balancing the semantic distribution in polysemous triggers and arguments.The reward-penalty mechanism balances the semantic distribution by enlarging the gap between the target and nontarget semantics by rewarding correct classifications and penalizing incorrect classifications.Additionally,we propose a sentencelevel event situation awareness(SA)mechanism to guide the encoder to accurately learn the knowledge of events mentioned in the sentence,thereby enhancing target event semantics in the distribution of polysemous triggers and arguments.Finally,for various semantics in different tasks,we propose task-specific semantic decoders to precisely identify the boundaries of the predicted triggers and arguments for the semantics.Our experimental results on ACE2005 and its variants,along with the rich Entities,Relations,and Events(ERE),demonstrate the superiority of our approach over single-task and multi-task EE baselines.展开更多
Most word embedding models have the following problems:(1)In the models based on bag-of-words contexts,the structural relations of sentences are completely neglected;(2)Each word uses a single embedding,which makes th...Most word embedding models have the following problems:(1)In the models based on bag-of-words contexts,the structural relations of sentences are completely neglected;(2)Each word uses a single embedding,which makes the model indiscriminative for polysemous words;(3)Word embedding easily tends to contextual structure similarity of sentences.To solve these problems,we propose an easy-to-use representation algorithm of syntactic word embedding(SWE).The main procedures are:(1)A polysemous tagging algorithm is used for polysemous representation by the latent Dirichlet allocation(LDA)algorithm;(2)Symbols‘+’and‘-’are adopted to indicate the directions of the dependency syntax;(3)Stopwords and their dependencies are deleted;(4)Dependency skip is applied to connect indirect dependencies;(5)Dependency-based contexts are inputted to a word2vec model.Experimental results show that our model generates desirable word embedding in similarity evaluation tasks.Besides,semantic and syntactic features can be captured from dependency-based syntactic contexts,exhibiting less topical and more syntactic similarity.We conclude that SWE outperforms single embedding learning models.展开更多
This paper reports how the polysemous word TAKE is treated in the junior high school textbooks in Japan and its semantic distributions. Also, it looks into the ways in which Japanese junior high school students actual...This paper reports how the polysemous word TAKE is treated in the junior high school textbooks in Japan and its semantic distributions. Also, it looks into the ways in which Japanese junior high school students actually use TAKE in their compositions and analyses its semantic distributions in their writings. This paper uses the BBC 500 Word essay compositions(BBC 500 words) to compare these compositions with the ones written by English native speakers. Comparing the different semantic distributions of the word TAKE in Japanese junior high school textbooks, Japanese students' compositions and BBC 500 words, it is clear that compositions in BBC 500 words have a better balance. This result suggests that the English native speaking children use TAKE to convey various meanings. Also the core meaning of TAKE is the highest among the three contexts under investigation. This paper suggests the textbooks should include many more various objects to enable students to learn to use them in various situations and the core meaning of TAKE should be presented in the textbooks more often. Furthermore, the semantic features of the polysemous words and their semiotic value in English should be introduced in the textbooks and taught in intentional ways.展开更多
文摘Societal values are polysemous and its dimensions are imported into advertising to give it rich content. The polysemous character makes it sensitive and complex phenomena. For instance, value that is acceptable in the western part of Nigeria may be unacceptable in the north or east. This clearly implies that value, although may be of the people, is relative and subjective. This study made use of survey research design with a single research question set to guide it. Data were collected from 362 respondents who were purposively selected in the study area （Lagos State, Nigeria） as sample size. Data gathering were done on the field with the aid of questionnaire and analyzed with descriptive statistics. Specifically, a Table of frequency and percentage distribution was employed and scoring of variables was done vis-h-vis the responses of the consumers of staple commodities to look at the extent to which societal values have influenced product advertisements in the State. The Mean and standard deviation was calculated. The result of the study presented in Table 1 shows that all the societal values scoped for this study （culture, moral, religion, taste, language and color） influence consumers in one way or the other but the portrayal of religious design concept to influence consumers to patronize staple commodities ranked best of all. The study observed that of all the societal values traceable to advertising campaign in Lagos State, religion-inclined advertising designs are gaining a rising number of influences. It therefore concludes that religious and cultural designs, when appropriately applied help outdoor advertising to thrive well in Lagos State.
文摘Phrasal verbs, accounting for a large proportion in modem language, pose numerous challenges to foreign language learners of English, who usually view verb ＋ particle combinations random. The issue of unpredictability is obviously a problem for English learners. Making things worse, many phrasal verbs are polysemous. For one thing, one phrasal verb may have multiple meanings; for another, several phrasal verbs may have the same or similar meanings. While the fast development of cognitive linguistics theory provides a new perspective for the study of English polysemous phrasal verbs. Researchers apply cognitive linguistic theory into second language acquisition and find that the multiple senses of phrasal verbs are actually systematic and motivated. The present study summarizes studies of polysemous phrasal verbs from the perspective of traditional approaches and cognitive approaches as well as the empirical studies based on it and analyzes the shortage of traditional approaches on phrasal verbs. Lastly, this paper illustrates some drawbacks of empirical study based on the assessment of Boers （2011） and points out some suggestions on further studies.
文摘The researcher analyzes the distribution and types of image-schema-based metaphorical extension(or IS-based meta-extension) in the semantic extension of 203 polysemous verbs,which can be named as PVs and are randomly selected from Longman Dictionary of Contemporary English(2nd Edition,1993).She finds that IS-based meta-extension is pervasive in the semantic extension of verbal polysemy.Specif ically,she f inds 77.83% of the samples can be analyzed in terms of IS-based Meta-extension,and PVs that can be analyzed in terms of path-IS-based,force-IS-based,containerIS-based,path+force-IS-based,and path+container-IS-based metaphorical extension,together making up 70.44% of the samples.
文摘Polysemic words appear in news English with high-frequency.So,how to determine the exact meaning of a polysemic word in the news and put it into proper Chinese causes much trouble and frustration to readers.This paper summarizes some effective translating strategies of polysemic words from English to Chinese.They include:translating based on collocation,translating based on grammar,translating based on background knowledge,translating based on logical relation,and translating based on register.
基金supported by the National Natural Science Foundation of China(Nos.62306330 and 62106275),the Young Elite Scientist Sponsorship Program by China Association for Science and Technology(No.YESS20230367),and the Natural Science Foundation of Hunan Province,China(Nos.2022JJ40558 and WDZC20235250103)。
文摘Event extraction(EE)is a complex natural language processing(NLP)task that aims at identifying and classifying triggers and arguments in raw text.The polysemy of triggers and arguments stands out as one of the key challenges affecting the precise extraction of events.Existing approaches commonly consider the semantic distribution of triggers and arguments to be balanced.However,the sample quantities of different semantics in the same trigger or argument vary in real-world scenarios,leading to a biased semantic distribution.The bias introduces two challenges:(1)low-frequency semantics is difficult to identify;(2)high-frequency semantics is often mistakenly identified.To tackle these challenges,we propose an adaptive learning method with the reward-penalty mechanism for balancing the semantic distribution in polysemous triggers and arguments.The reward-penalty mechanism balances the semantic distribution by enlarging the gap between the target and nontarget semantics by rewarding correct classifications and penalizing incorrect classifications.Additionally,we propose a sentencelevel event situation awareness(SA)mechanism to guide the encoder to accurately learn the knowledge of events mentioned in the sentence,thereby enhancing target event semantics in the distribution of polysemous triggers and arguments.Finally,for various semantics in different tasks,we propose task-specific semantic decoders to precisely identify the boundaries of the predicted triggers and arguments for the semantics.Our experimental results on ACE2005 and its variants,along with the rich Entities,Relations,and Events(ERE),demonstrate the superiority of our approach over single-task and multi-task EE baselines.
基金Project supported by the National Natural Science Foundation of China(Nos.61663041 and 61763041)the Program for Changjiang Scholars and Innovative Research Team in Universities,China(No.IRT_15R40)+2 种基金the Research Fund for the Chunhui Program of Ministry of Education of China(No.Z2014022)the Natural Science Foundation of Qinghai Province,China(No.2014-ZJ-721)the Fundamental Research Funds for the Central Universities,China(No.2017TS045)
文摘Most word embedding models have the following problems:(1)In the models based on bag-of-words contexts,the structural relations of sentences are completely neglected;(2)Each word uses a single embedding,which makes the model indiscriminative for polysemous words;(3)Word embedding easily tends to contextual structure similarity of sentences.To solve these problems,we propose an easy-to-use representation algorithm of syntactic word embedding(SWE).The main procedures are:(1)A polysemous tagging algorithm is used for polysemous representation by the latent Dirichlet allocation(LDA)algorithm;(2)Symbols‘+’and‘-’are adopted to indicate the directions of the dependency syntax;(3)Stopwords and their dependencies are deleted;(4)Dependency skip is applied to connect indirect dependencies;(5)Dependency-based contexts are inputted to a word2vec model.Experimental results show that our model generates desirable word embedding in similarity evaluation tasks.Besides,semantic and syntactic features can be captured from dependency-based syntactic contexts,exhibiting less topical and more syntactic similarity.We conclude that SWE outperforms single embedding learning models.
文摘This paper reports how the polysemous word TAKE is treated in the junior high school textbooks in Japan and its semantic distributions. Also, it looks into the ways in which Japanese junior high school students actually use TAKE in their compositions and analyses its semantic distributions in their writings. This paper uses the BBC 500 Word essay compositions(BBC 500 words) to compare these compositions with the ones written by English native speakers. Comparing the different semantic distributions of the word TAKE in Japanese junior high school textbooks, Japanese students' compositions and BBC 500 words, it is clear that compositions in BBC 500 words have a better balance. This result suggests that the English native speaking children use TAKE to convey various meanings. Also the core meaning of TAKE is the highest among the three contexts under investigation. This paper suggests the textbooks should include many more various objects to enable students to learn to use them in various situations and the core meaning of TAKE should be presented in the textbooks more often. Furthermore, the semantic features of the polysemous words and their semiotic value in English should be introduced in the textbooks and taught in intentional ways.
