{"type":"ScholarlyArticle","title":"Relation Adaptation: Learning to Extract Novel Relations with Minimum Supervision","authors":[{"name":"Danushka Bollegala","slug":"danushka-bollegala","given":"Danushka","family":"Bollegala","affiliation":""},{"name":"Yutaka Matsuo","slug":"yutaka-matsuo","given":"Yutaka","family":"Matsuo","affiliation":""},{"name":"Mitsuru Ishizuka","slug":"mitsuru-ishizuka","given":"Mitsuru","family":"Ishizuka","affiliation":""}],"abstract":"Extracting the relations that exist between two entities is an important step in numerousWeb-related tasks such as information extraction.A supervised relation extraction system that is trained to extract a particular relation type might not accurately extract a new type of a relation for which it has not been trained.However, it is costly to create training data manually for every new relation type that one might want to extract.We propose a method to adapt an existing relation extraction system to extractnew relation types with minimum supervision. Our proposed method comprises two stages: learning a lower-dimensional projection between different relations, and learning a relational classifier for the target relation type with instance sampling. We evaluate the proposed method using a dataset that contains 2000 instances for 20 different relation types. Our experimental results show that the proposed method achieves a statistically significant macro-average F-score of 62.77. Moreover, the proposed method outperforms numerous baselines and a previously proposed weakly-supervised relation extraction method.","doi":"10.5591/978-1-57735-516-8/IJCAI11-368","url":"https://ijcai.org/proceedings/2011/368","pdf":"https://ijcai.org/proceedings/2011/0368.pdf","markdown":"https://ijcai.org/proceedings/2011/368.md","bibtex":"https://ijcai.org/proceedings/2011/bibtex/368","volume":{"slug":"2011","title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2011","url":"https://ijcai.org/proceedings/2011/","year":2011,"location":"Barcelona, Catalonia, Spain","dates":"16–22 July 2011","editors":"Toby Walsh","isbn":"978-1-57735-512-0; 978-1-57735-513-7; 978-1-57735-514-4; 978-1-57735-515-1; 978-1-57735-516-8","publisher":"AAAI Press/International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":368,"pages":{"first":2205,"last":2209},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}