| lr,4-1-P05-1074,ak | Previous work has used <term> monolingual parallel corpora </term> to extract and generate <term> paraphrases </term> . | #10147 Previous work has usedmonolingual parallel corpora to extract and generate paraphrases. | |
| other,11-1-P05-1074,ak | Previous work has used <term> monolingual parallel corpora </term> to extract and generate <term> paraphrases </term> . | #10154 Previous work has used monolingual parallel corpora to extract and generateparaphrases. | |
| lr,9-2-P05-1074,ak | We show that this task can be done using <term> bilingual parallel corpora </term> , a much more commonly available resource . | #10165 We show that this task can be done usingbilingual parallel corpora, a much more commonly available resource. | |
| tech,1-3-P05-1074,ak | Using <term> alignment techniques </term> from <term> phrase-based statistical machine translation </term> , we show how <term> paraphrases </term> in one language can be identified using a <term> phrase </term> in another language as a pivot . | #10177 Usingalignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot. | |
| tech,4-3-P05-1074,ak | Using <term> alignment techniques </term> from <term> phrase-based statistical machine translation </term> , we show how <term> paraphrases </term> in one language can be identified using a <term> phrase </term> in another language as a pivot . | #10180 Using alignment techniques fromphrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot. | |
| other,12-3-P05-1074,ak | Using <term> alignment techniques </term> from <term> phrase-based statistical machine translation </term> , we show how <term> paraphrases </term> in one language can be identified using a <term> phrase </term> in another language as a pivot . | #10188 Using alignment techniques from phrase-based statistical machine translation, we show howparaphrases in one language can be identified using a phrase in another language as a pivot. | |
| other,21-3-P05-1074,ak | Using <term> alignment techniques </term> from <term> phrase-based statistical machine translation </term> , we show how <term> paraphrases </term> in one language can be identified using a <term> phrase </term> in another language as a pivot . | #10197 Using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using aphrase in another language as a pivot. | |
| measure(ment),3-4-P05-1074,ak | We define a <term> paraphrase probability </term> that allows <term> paraphrases </term> extracted from a <term> bilingual parallel corpus </term> to be ranked using <term> translation probabilities </term> , and show how it can be refined to take <term> contextual information </term> into account . | #10208 We define aparaphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account. | |
| other,7-4-P05-1074,ak | We define a <term> paraphrase probability </term> that allows <term> paraphrases </term> extracted from a <term> bilingual parallel corpus </term> to be ranked using <term> translation probabilities </term> , and show how it can be refined to take <term> contextual information </term> into account . | #10212 We define a paraphrase probability that allowsparaphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account. | |
| lr,11-4-P05-1074,ak | We define a <term> paraphrase probability </term> that allows <term> paraphrases </term> extracted from a <term> bilingual parallel corpus </term> to be ranked using <term> translation probabilities </term> , and show how it can be refined to take <term> contextual information </term> into account . | #10216 We define a paraphrase probability that allows paraphrases extracted from abilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account. | |
| measure(ment),18-4-P05-1074,ak | We define a <term> paraphrase probability </term> that allows <term> paraphrases </term> extracted from a <term> bilingual parallel corpus </term> to be ranked using <term> translation probabilities </term> , and show how it can be refined to take <term> contextual information </term> into account . | #10223 We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked usingtranslation probabilities, and show how it can be refined to take contextual information into account. | |
| other,30-4-P05-1074,ak | We define a <term> paraphrase probability </term> that allows <term> paraphrases </term> extracted from a <term> bilingual parallel corpus </term> to be ranked using <term> translation probabilities </term> , and show how it can be refined to take <term> contextual information </term> into account . | #10235 We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to takecontextual information into account. | |
| tech,3-5-P05-1074,ak | We evaluate our <term> paraphrase extraction and ranking methods </term> using a set of <term> manual word alignments </term> , and contrast the quality with <term> paraphrases </term> extracted from <term> automatic alignments </term> . | #10243 We evaluate ourparaphrase extraction and ranking methods using a set of manual word alignments, and contrast the quality with paraphrases extracted from automatic alignments. | |
| lr,12-5-P05-1074,ak | We evaluate our <term> paraphrase extraction and ranking methods </term> using a set of <term> manual word alignments </term> , and contrast the quality with <term> paraphrases </term> extracted from <term> automatic alignments </term> . | #10252 We evaluate our paraphrase extraction and ranking methods using a set ofmanual word alignments, and contrast the quality with paraphrases extracted from automatic alignments. | |
| other,21-5-P05-1074,ak | We evaluate our <term> paraphrase extraction and ranking methods </term> using a set of <term> manual word alignments </term> , and contrast the quality with <term> paraphrases </term> extracted from <term> automatic alignments </term> . | #10261 We evaluate our paraphrase extraction and ranking methods using a set of manual word alignments, and contrast the quality withparaphrases extracted from automatic alignments. | |
| lr,24-5-P05-1074,ak | We evaluate our <term> paraphrase extraction and ranking methods </term> using a set of <term> manual word alignments </term> , and contrast the quality with <term> paraphrases </term> extracted from <term> automatic alignments </term> . | #10264 We evaluate our paraphrase extraction and ranking methods using a set of manual word alignments, and contrast the quality with paraphrases extracted fromautomatic alignments. |
