| other,28-3-I05-5003,bq | matches and non-matches </term> in the <term> | sentence | </term> . Our results show that <term> MT | #8395 We also introduce a novel classification method based on PER which leverages part of speech information of the words contributing to the word matches and non-matches in the sentence . |
| tech,21-4-I05-5003,bq | classification </term> and to a lesser extent <term> | entailment | </term> . Our <term> technique </term> gives | #8418 Our results show that MT evaluation techniques are able to produce useful features for paraphrase classification and to a lesser extent entailment . |
| tech,1-5-I05-5003,bq | extent <term> entailment </term> . Our <term> | technique | </term> gives a substantial improvement | #8421 Our technique gives a substantial improvement in paraphrase classification accuracy over all of the other models used in the experiments. |
| measure(ment),9-3-I05-5003,bq | classification method </term> based on <term> | PER | </term> which leverages <term> part of speech | #8376 We also introduce a novel classification method based on PER which leverages part of speech information of the words contributing to the word matches and non-matches in the sentence. |
| other,28-2-I05-5003,bq | <term> semantic equivalence </term> and <term> | entailment | </term> . We also introduce a novel <term> | #8365 This paper investigates the utility of applying standard MT evaluation methods (BLEU, NIST, WER and PER) to building classifiers to predict semantic equivalence and entailment . |
