The paper reports the approaches utilized and results achieved for our system in the shared task (in FIRE-2016) for paraphrase identification in Indian languages (DPIL). Since Indian languages have a complex inherent nature, paraphrase identification in these languages becomes a challenging task. In the DPIL task, the challenge is to detect and identify whether a given sentence pairs paraphrase...

Paraphrase detection has numerous important applications in natural language processing (such as clustering, summarizing, and detecting plagiarism). One approach to detecting paraphrases is to use predicate argument tuples. Although this approach achieves high paraphrase recall, its accuracy is generally low. Other approaches focus on matching similar words, but word meaning is often contextual...

This study tackles the problem of paraphrase acquisition: achieving high coverage as well as accuracy. Our method first induces paraphrase patterns from given seed paraphrases, exploiting the generality of paraphrases exhibited by pairs of lexical variants, e.g., “amendment” and “amending,” in a fully empirical way. It then searches monolingual corpora for new paraphrases that match the pattern...

Paraphrase detection is the task of examining two sentences and determining whether they have the same meaning. In order to obtain high accuracy on this task, thorough syntactic and semantic analysis of the two statements is needed. We introduce a method for paraphrase detection based on recursive autoencoders (RAE). Our unsupervised RAEs are based on a novel unfolding objective and learn featu...

In this work, we evaluate different sentence encoders with emphasis on examining their embedding spaces. Specifically, we hypothesize that a “high-quality” embedding aids in generalization, promoting transfer learning as well as zero-shot and one-shot learning. To investigate this, we modify Skipthought vectors to learn a more generalizable space by exploiting a small amount of supervision. The...

Paraphrase extraction and coreference resolution have applications in Question Answering, Information Extraction, Machine Translation, and so forth. Paraphrase pairs might be coreferential, and coreference relations are sometimes paraphrases. The two overlap considerably (Hirst 1981), but their definitionsmake them significantly different in essence: Paraphrasing concerns meaning, whereas coref...

Paraphrase recognition is used in a number of applications such as tutoring systems, question answering systems, and information retrieval systems. The context of our research is the iSTART reading strategy trainer for science texts, which needs to understand and recognize the trainee’s input and respond appropriately. This paper describes the motivation for paraphrase recognition and develops ...

We present a solution to the problem of paraphrase identification of questions. We focus on a recent dataset of question pairs annotated with binary paraphrase labels and show that a variant of the decomposable attention model (Parikh et al., 2016) results in accurate performance on this task, while being far simpler than many competing neural architectures. Furthermore, when the model is pretr...

This paper describes our ongoing research project on text simplification for congenitally deaf people. Text simplification we are aiming at is the task of offering a deaf reader a syntactic and lexical paraphrase of a given text for assisting her/him to understand what it means. In this paper, we discuss the issues we should address to realize text simplification and report on the present resul...

This paper describes a study on the impact of the original signal (text, speech, visual scene, event) of a text pair on the task of both manual and automatic sub-sentential paraphrase acquisition. A corpus of 2,500 annotated sentences in English and French is described, and performance on this corpus is reported for an efficient system combination exploiting a large set of features for paraphra...