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Taking this route sets up a dual goal: (a) from the generic paraphrasing perspective - an objective evaluation of paraphrase acquisition performance on a concrete application dataset, as well as identifying the additional mechanisms needed to match paraphrases in texts; (b) from the RE perspective investigating the feasibility and performance of a generic paraphrase-based approach for RE. Our configuration assumes a set of entailing templates (non-symmetric “paraphrases”) for the target relation. For example, for the target relation “X interact with Y” we would assume a set of entailing templates as in Tables 3 and 7. . | Investigating a Generic Paraphrase-based Approach for Relation Extraction Lorenza Romano ITC-irst via Sommarive 18 38050 Povo TN Italy romano@itc.it Milen Kouylekov ITC-irst via Sommarive 18 38050 Povo TN Italy kouylekov@itc.it Idan Szpektor Department of Computer Science Bar Ilan University Ramat Gan 52900 Israel szpekti@cs.biu.ac.il Ido Dagan Department of Computer Science Bar Ilan University Ramat Gan 52900 Israel dagan@cs.biu.ac.il Abstract Unsupervised paraphrase acquisition has been an active research field in recent years but its effective coverage and performance have rarely been evaluated. We propose a generic paraphrase-based approach for Relation Extraction RE aiming at a dual goal obtaining an applicative evaluation scheme for paraphrase acquisition and obtaining a generic and largely unsupervised configuration for RE. We analyze the potential of our approach and evaluate an implemented prototype of it using an RE dataset. Our findings reveal a high potential for unsupervised paraphrase acquisition. We also identify the need for novel robust models for matching paraphrases in texts which should address syntactic complexity and variability. 1 Introduction A crucial challenge for semantic NLP applications is recognizing the many different ways for expressing the same information. This semantic variability phenomenon was addressed within specific applications such as question answering information extraction and information retrieval. Recently the problem was investigated within generic application-independent paradigms such as paraphrasing and textual entailment. Eventually it would be most appealing to apply generic models for semantic variability to concrete applications. This paper investigates the applicability of a generic paraphrase-based approach to the Relation Extraction RE task using an available RE dataset of protein interactions. RE is Alberto Lavelli ITC-irst via Sommarive 18 38050 Povo TN Italy lavelli@itc.it highly suitable for such .