| measure(ment),0-1-I05-2014,ak | Other tasks using the method developed for <term> ILIMP </term> are described briefly , as well as the use of <term> ILIMP </term> in a modular <term> syntactic analysis system </term> . <term> Automatic evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established . | #6221 Other tasks using the method developed for ILIMP are described briefly, as well as the use of ILIMP in a modular syntactic analysis system.Automatic evaluation metrics for Machine Translation (MT) systems, such as BLEU or NIST, are now well established. | |
| tech,4-1-I05-2014,ak | <term> Automatic evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established . | #6225 Automatic evaluation metrics forMachine Translation ( MT ) systems, such as BLEU or NIST, are now well established. | |
| measure(ment),13-1-I05-2014,ak | <term> Automatic evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established . | #6234 Automatic evaluation metrics for Machine Translation (MT) systems, such asBLEU or NIST, are now well established. | |
| measure(ment),15-1-I05-2014,ak | <term> Automatic evaluation metrics </term> for <term> Machine Translation ( MT ) systems </term> , such as <term> BLEU </term> or <term> NIST </term> , are now well established . | #6236 Automatic evaluation metrics for Machine Translation (MT) systems, such as BLEU orNIST, are now well established. | |
| other,10-2-I05-2014,ak | Yet , they are scarcely used for the assessment of <term> language pairs </term> like English-Chinese or English-Japanese , because of the <term> word segmentation problem </term> . | #6253 Yet, they are scarcely used for the assessment oflanguage pairs like English-Chinese or English-Japanese, because of the word segmentation problem. | |
| other,20-2-I05-2014,ak | Yet , they are scarcely used for the assessment of <term> language pairs </term> like English-Chinese or English-Japanese , because of the <term> word segmentation problem </term> . | #6263 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,ak | 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 level </term> . | #6277 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,ak | 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 level </term> . | #6279 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,ak | 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 level </term> . | #6286 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,ak | The use of <term> BLEU </term> at the <term> character level </term> eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial systems outputting unsegmented texts with , for instance , <term> statistical MT systems </term> which usually segment their outputs . | #6292 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,ak | The use of <term> BLEU </term> at the <term> character level </term> eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial systems outputting unsegmented texts with , for instance , <term> statistical MT systems </term> which usually segment their outputs . | #6295 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,ak | The use of <term> BLEU </term> at the <term> character level </term> eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial systems outputting unsegmented texts with , for instance , <term> statistical MT systems </term> which usually segment their outputs . | #6299 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,31-4-I05-2014,ak | The use of <term> BLEU </term> at the <term> character level </term> eliminates the <term> word segmentation problem </term> : it makes it possible to directly compare commercial systems outputting unsegmented texts with , for instance , <term> statistical MT systems </term> which usually segment their outputs . | #6320 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. |
