The most critical issue in generating and recognizing paraphrases is development of wide-coverage paraphrase knowledge. Previous work on paraphrase acquisition has collected lexicalized pairs of expressions; however, the results do not ensure full coverage of the various paraphrase phenomena. This paper focuses on productive paraphrases realized by general transformation patterns, and addresses...

We figure out a trap that is not carefully addressed in the previous works using lexicons or ontologies to train or improve distributed word representations: For polysemous words and utterances changing meaning in different contexts, their paraphrases or related entities in a lexicon or an ontology are unreliable and sometimes deteriorate the learning of word representations. Thus, we propose a...

This paper addresses the problem of ranking a list of paraphrases associated with a noun-noun compound as closely as possible to human raters (Butnariu et al., 2010). UCD-Goggle tackles this task using semantic knowledge learnt from the Google n-grams together with human-preferences for paraphrases mined from training data. Empirical evaluation shows that UCDGoggle achieves 0.432 Spearman corre...

Paraphrases are useful for statistical machine translation (SMT) and natural language processing tasks. Distributional paraphrase generation is independent of parallel texts and syntactic parses, and hence is suitable also for resource-poor languages, but tends to erroneously rank antonyms, trend-contrasting, and polarity-dissimilar candidates as good paraphrases. We present here a novel method...

We present a Question Answering system for technical domains which makes an intelligent use of paraphrases to increase the likelihood of finding the answer to the user’s question. The system implements a simple and efficient logic representation of questions and answers that maps paraphrases to the same underlying semantic representation. Further, paraphrases of technical terminology are dealt ...

Mismatch between queries and documents is a key issue for the web search task. In order to narrow down such mismatch, in this paper, we present an in-depth investigation on adapting a paraphrasing technique to web search from three aspects: a search-oriented paraphrasing model; an NDCG-based parameter optimization algorithm; an enhanced ranking model leveraging augmented features computed on pa...

We present a new release of the Paraphrase Database. PPDB 2.0 includes a discriminatively re-ranked set of paraphrases that achieve a higher correlation with human judgments than PPDB 1.0’s heuristic rankings. Each paraphrase pair in the database now also includes finegrained entailment relations, word embedding similarities, and style annotations.

We propose a method that automatically generates paraphrase sets from seed sentences to be used as reference sets in objective machine translation evaluation measures like BLEU and NIST. We measured the quality of the paraphrases produced in an experiment, i.e., (i) their grammaticality: at least 99% correct sentences; (ii) their equivalence in meaning: at least 96% correct paraphrases either b...