A Survey of Paraphrasing and Textual Entailment Methods

• Published in: The Journal of artificial intelligence research Vol. 38; pp. 135 - 187
• Main Authors: Androutsopoulos, I., Malakasiotis, P.
• Format: Journal Article
• Language: English
• Published: San Francisco AI Access Foundation 28.05.2010
• Subjects: Artificial intelligence; Machine translation; Natural language; Natural language processing; Sentences
• ISSN: 1076-9757; 1076-9757; 1943-5037
• DOI: 10.1613/jair.2985

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.