Concordance

Query I05-2014 18 (839.2 per million)

measure(ment),1-1-I05-2014,bq	Automatic <term> evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established .	#7679 Automaticevaluation metrics for Machine Translation (MT) systems, such as BLEU or NIST, are now well established.
tech,4-1-I05-2014,bq	Automatic <term> evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established .	#7682 Automatic evaluation metrics forMachine Translation ( MT ) systems, such as BLEU or NIST, are now well established.
measure(ment),13-1-I05-2014,bq	Automatic <term> evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established .	#7691 Automatic evaluation metrics for Machine Translation (MT) systems, such asBLEU or NIST, are now well established.
measure(ment),15-1-I05-2014,bq	Automatic <term> evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established .	#7693 Automatic evaluation metrics for Machine Translation (MT) systems, such as BLEU orNIST, are now well established.
other,10-2-I05-2014,bq	Yet , they are scarcely used for the assessment of <term> language pairs </term> like <term> English-Chinese </term> or <term> English-Japanese </term> , because of the <term> word segmentation problem </term> .	#7710 Yet, they are scarcely used for the assessment oflanguage pairs like English-Chinese or English-Japanese, because of the word segmentation problem.
other,13-2-I05-2014,bq	Yet , they are scarcely used for the assessment of <term> language pairs </term> like <term> English-Chinese </term> or <term> English-Japanese </term> , because of the <term> word segmentation problem </term> .	#7713 Yet, they are scarcely used for the assessment of language pairs likeEnglish-Chinese or English-Japanese, because of the word segmentation problem.
other,15-2-I05-2014,bq	Yet , they are scarcely used for the assessment of <term> language pairs </term> like <term> English-Chinese </term> or <term> English-Japanese </term> , because of the <term> word segmentation problem </term> .	#7715 Yet, they are scarcely used for the assessment of language pairs like English-Chinese orEnglish-Japanese, because of the word segmentation problem.
other,20-2-I05-2014,bq	Yet , they are scarcely used for the assessment of <term> language pairs </term> like <term> English-Chinese </term> or <term> English-Japanese </term> , because of the <term> word segmentation problem </term> .	#7720 Yet, they are scarcely used for the assessment of language pairs like English-Chinese or English-Japanese, because of theword segmentation problem.
measure(ment),10-3-I05-2014,bq	This study establishes the equivalence between the standard use of <term> BLEU </term> in <term> word n-grams </term> and its application at the <term> character </term> level .	#7734 This study establishes the equivalence between the standard use ofBLEU in word n-grams and its application at the character level.
other,12-3-I05-2014,bq	This study establishes the equivalence between the standard use of <term> BLEU </term> in <term> word n-grams </term> and its application at the <term> character </term> level .	#7736 This study establishes the equivalence between the standard use of BLEU inword n-grams and its application at the character level.
other,19-3-I05-2014,bq	This study establishes the equivalence between the standard use of <term> BLEU </term> in <term> word n-grams </term> and its application at the <term> character </term> level .	#7743 This study establishes the equivalence between the standard use of BLEU in word n-grams and its application at thecharacter level.
measure(ment),3-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7749 The use ofBLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance, statistical MT systems which usually segment their outputs.
other,6-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7752 The use of BLEU at thecharacter level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance, statistical MT systems which usually segment their outputs.
other,10-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7756 The use of BLEU at the character level eliminates theword segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance, statistical MT systems which usually segment their outputs.
tech,22-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7768 The use of BLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercialsystems outputting unsegmented texts with, for instance, statistical MT systems which usually segment their outputs.
other,24-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7770 The use of BLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputtingunsegmented texts with, for instance, statistical MT systems which usually segment their outputs.
tech,31-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7777 The use of BLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance,statistical MT systems which usually segment their outputs.
other,38-4-I05-2014,bq	The use of <term> BLEU </term> at the <term> character </term> level eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial <term> systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical MT systems </term> which usually segment their <term> outputs </term> .	#7784 The use of BLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance, statistical MT systems which usually segment theiroutputs.


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