An obstacle to research in automatic paraphrase identification and generation is the lack of large-scale, publiclyavailable labeled corpora of sentential paraphrases. This paper describes the creation of the recently-released Microsoft Research Paraphrase Corpus, which contains 5801 sentence pairs, each hand-labeled with a binary judgment as to whether the pair constitutes a paraphrase. The cor...

We propose a novel approach to improve SMT via paraphrase rules which are automatically extracted from the bilingual training data. Without using extra paraphrase resources, we acquire the rules by comparing the source side of the parallel corpus with the target-to-source translations of the target side. Besides the word and phrase paraphrases, the acquired paraphrase rules mainly cover the str...

This paper proposes a method that leverages multiple machine translation (MT) engines for paraphrase generation (PG). The method includes two stages. Firstly, we use a multi-pivot approach to acquire a set of candidate paraphrases for a source sentence S. Then, we employ two kinds of techniques, namely the selection-based technique and the decoding-based technique, to produce a best paraphrase ...

In this paper we investigate the automatic collection, generation and evaluation of sentential paraphrases. Valuable sources of paraphrases are news article headlines; they tend to describe the same event in various different ways, and can easily be obtained from the web. We describe a method for generating paraphrases by using a large aligned monolingual corpus of news headlines acquired autom...

In this paper we investigate the automatic generation of paraphrases by using machine translation techniques. Three contributions we make are the construction of a large paraphrase corpus for English and Dutch, a re-ranking heuristic to use machine translation for paraphrase generation and a proper evaluation methodology. A large parallel corpus is constructed by aligning clustered headlines th...

Text condensation aims at shortening the length of an utterance without losing essential textual information. In this paper, we report on the implementation and preliminary evaluation of a sentence condensation tool for Greek using a manually constructed table of 450 lexical paraphrases, and a set of rules that delete syntactic subtrees that carry minor semantic information. Evaluation on two s...

In this paper, we propose a method to search the Web for sentence substitutions for a given sentence query. Our method uses only lexico-syntactic patterns dynamically generated from the input sentence query to collect sentence substitutions from the Web on demand. Experimental results show that our method works well and can be used to obtain sentence substitutions for rare sentence queries as w...

One of the limitations of semantic parsing approaches to open-domain question answering is the lexicosyntactic gap between natural language questions and knowledge base entries – there are many ways to ask a question, all with the same answer. In this paper we propose to bridge this gap by generating paraphrases of the input question with the goal that at least one of them will be correctly map...

Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resource for extracting more sophisticated sentential paraphrases, which are more obviously learnable from monolingual parallel corpora. We extend bilingual paraphrase extraction to syntactic paraphrases and demonstrate its a...

Lexical paraphrasing aims at acquiring word-level paraphrases. It is critical for many Natural Language Processing (NLP) applications, such as Question Answering (QA), Information Extraction (IE), and Machine Translation (MT). Since the meaning and usage of a word can vary in distinct contexts, different paraphrases should be acquired according to the contexts. However, most of the existing res...