Snowball: Extracting Relations from Large Plain-Text Collections

This is my own implementation of the the Snowball system to bootstrap relationship instances. You can find more details about the original system here:

• Eugene Agichtein and Luis Gravano, Snowball: Extracting Relations from Large Plain-Text Collections. In Proceedings of the fifth ACM conference on Digital libraries. ACM, 200.

• H Yu, E Agichtein, Extracting synonymous gene and protein terms from biological literature. In Bioinformatics, 19(suppl 1), 2003 - Oxford University Press

For more details about this particular implementation please refer to:

• David S Batista, Bruno Martins, and Mário J Silva. , Semi-Supervised Bootstrapping of Relationship Extractors with Distributional Semantics. In Empirical Methods in Natural Language Processing. ACL, 2015. (Honorable Mention for Best Short Paper)

• David S Batista, Ph.D. Thesis, Large-Scale Semantic Relationship Extraction for Information Discovery (Chapter 5), Instituto Superior Técnico, University of Lisbon, 2016

A sample file containing sentences where the named-entities are already tagged can be downloaded, which has 1 million sentences taken from the New York Times articles part of the English Gigaword Collection.

NOTE: look at the desription of BREDS to understand how to give a tagged document collection and seeds to setup the bootstrapping of relationship instances with Snowball, both systems have a similar setup.