Automatically Constructing a Corpus of Sentential Paraphrases.pdfVIP

Automatically Constructing a Corpus of Sentential Paraphrases William B. Dolan and Chris Brockett Natural Language Processing Group Microsoft Research Redmond, WA, 98052, USA {billdol,chrisbkt}@ Abstract An obstacle to research in automatic paraphrase identification and genera- tion is the lack of large-scale, publicly- available labeled corpora of sentential paraphrases. This paper describes the creation of the recently-released Micro- soft Research Paraphrase Corpus, which contains 5801 sentence pairs, each hand-labeled with a binary judg- ment as to whether the pair constitutes a paraphrase. The corpus was created using heuristic extraction techniques in conjunction with an SVM-based classi- fier to select likely sentence-level para- phrases from a large corpus of topic- clustered news data. These pairs were then submitted to human judges, who confirmed that 67% were in fact se- mantically equivalent. In addition to describing the corpus itself, we explore a number of issues that arose in defin- ing guidelines for the human raters. 1 Introduction The Microsoft Research Paraphrase Corpus (MSRP), available for download at /research/nlp/msr_ paraphrase.htm, consists of 5801 pairs of sen- tences, each accompanied by a binary judgment indicating whether human raters considered the pair of sentences to be similar enough in mean- ing to be considered close paraphrases. This data has been published for the purpose of encourag- ing research in areas relating to paraphrase and sentential synonymy and inference, and to help establish a discourse on the proper construction of paraphrase corpora for training and evalua- tion. It is hoped that by releasing this corpus, we will stimulate the publication of similar cor- pora by others and help move the field toward adoption of a shared dataset that will permit use- ful comparisons of results across research efforts. 2 Motivation The success of Statistical Machine Translation (SMT) has