Investigating a Generic Paraphrase-based Approach for Relation Extraction
Lorenza Romano, Milen Kouylekov, Idan Szpektor, Ido Dagan and Alberto Lavelli
In: EACL 2006, 5-7 April 2006, Trento, Italy.
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.