The present study investigates the effects of congruency and frequency on adjective-noun collocational processing for Chinese learners of English at two proficiency levels based on the data obtained in an online accep...The present study investigates the effects of congruency and frequency on adjective-noun collocational processing for Chinese learners of English at two proficiency levels based on the data obtained in an online acceptability judgment task.The subject pool of this research included 60 English majors studying at a university in China;30 were selected as a higher-proficiency group and 30 as a lower-proficiency group according to their Vocabulary Levels Test(Schmitt et al.,2001)scores and their self-reported proficiency in English.The experimental materials were programmed to E-prime 2.0 and included six types of collocations:(1)15 high-frequency congruent collocations,(2)15 low-frequency congruent collocations,(3)15 high-frequency incongruent collocations,(4)15 low-frequency incongruent collocations,(5)15 Chinese-only items,and(6)75 unrelated items for baseline data.The collected response times(RTs)and accuracy rates data were statistically analyzed by the use of an ANOVA test and pairwise comparisons through SPSS 16.0 software.The results revealed that:(1)the adjective-noun collocational processing of Chinese English learners is influenced by collocational frequency,congruency and L2 proficiency;(2)the processing time is affected by the interaction of congruency and frequency;and(3)the interactive effect of L2 proficiency in conjunction with congruency and frequency also influences the processing quality.展开更多
In this work,an approach is proposed to acquire synonymous attribute phrases of named entities(NEs) from an online encyclopedia.Synonymous attribute phrases are the phrases that express the same attribute with differe...In this work,an approach is proposed to acquire synonymous attribute phrases of named entities(NEs) from an online encyclopedia.Synonymous attribute phrases are the phrases that express the same attribute with different surface forms for a class of NEs.Specifically,the proposed approach is composed of three stages.Firstly,the entries related to a given NE class are automatically selected from an online encyclopedia.Secondly,attribute phrases are extracted based on the statistics of phrase frequency.Thirdly,synonymous attributes are identified in a pairwise manner through a classification framework combining multiple features.The proposed approach is applied on Baidu Baike,a Chinese online encyclopedia,for four different NE classes.Experimental results show that the approach obtains an average precision of 74%and an average F-value of 65%for the four NE classes.In particular,thousands of synonymous attribute phrase pairs are acquired for each class,which demonstrates the effectiveness of the proposed approach.展开更多
A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn...A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn from a small amount of data and handle unknown words for the purpose of machine translation.A small size of 998 k English annotated corpus in business domain is built semi-automatically based on a new tagset;the maximum entropy model is adopted,and rule-based approach is used in post-processing.The tagger is further applied in Noun Phrase(NP) chunking.Experiments show that our tagger achieves an accuracy of 98.14%,which is a quite satisfactory result.In the application to NP chunking,the tagger gives rise to 2.21% increase in F-score,compared with the results using Stanford tagger.展开更多
文摘The present study investigates the effects of congruency and frequency on adjective-noun collocational processing for Chinese learners of English at two proficiency levels based on the data obtained in an online acceptability judgment task.The subject pool of this research included 60 English majors studying at a university in China;30 were selected as a higher-proficiency group and 30 as a lower-proficiency group according to their Vocabulary Levels Test(Schmitt et al.,2001)scores and their self-reported proficiency in English.The experimental materials were programmed to E-prime 2.0 and included six types of collocations:(1)15 high-frequency congruent collocations,(2)15 low-frequency congruent collocations,(3)15 high-frequency incongruent collocations,(4)15 low-frequency incongruent collocations,(5)15 Chinese-only items,and(6)75 unrelated items for baseline data.The collected response times(RTs)and accuracy rates data were statistically analyzed by the use of an ANOVA test and pairwise comparisons through SPSS 16.0 software.The results revealed that:(1)the adjective-noun collocational processing of Chinese English learners is influenced by collocational frequency,congruency and L2 proficiency;(2)the processing time is affected by the interaction of congruency and frequency;and(3)the interactive effect of L2 proficiency in conjunction with congruency and frequency also influences the processing quality.
基金Supported by the National High Technology Research and Development Programme of China(No.2008AA01Z144)the National NaturalScience Foundation of China(No.61073126,61073129)
文摘In this work,an approach is proposed to acquire synonymous attribute phrases of named entities(NEs) from an online encyclopedia.Synonymous attribute phrases are the phrases that express the same attribute with different surface forms for a class of NEs.Specifically,the proposed approach is composed of three stages.Firstly,the entries related to a given NE class are automatically selected from an online encyclopedia.Secondly,attribute phrases are extracted based on the statistics of phrase frequency.Thirdly,synonymous attributes are identified in a pairwise manner through a classification framework combining multiple features.The proposed approach is applied on Baidu Baike,a Chinese online encyclopedia,for four different NE classes.Experimental results show that the approach obtains an average precision of 74%and an average F-value of 65%for the four NE classes.In particular,thousands of synonymous attribute phrase pairs are acquired for each class,which demonstrates the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China under Grant No.61173100the Fundamental Research Funds for the Central Universities under Grant No.GDUT10RW202
文摘A hybrid approach to English Part-of-Speech(PoS) tagging with its target application being English-Chinese machine translation in business domain is presented,demonstrating how a present tagger can be adapted to learn from a small amount of data and handle unknown words for the purpose of machine translation.A small size of 998 k English annotated corpus in business domain is built semi-automatically based on a new tagset;the maximum entropy model is adopted,and rule-based approach is used in post-processing.The tagger is further applied in Noun Phrase(NP) chunking.Experiments show that our tagger achieves an accuracy of 98.14%,which is a quite satisfactory result.In the application to NP chunking,the tagger gives rise to 2.21% increase in F-score,compared with the results using Stanford tagger.
