Pairwise FastText Classifier for Entity Disambiguation

Abstract

For the Australasian Language Technology Association (ALTA) 2016 Shared Task, we devised Pairwise FastText Classifier (PFC), an efficient embedding-based text classifier, and used it for entity disambiguation. Compared with a few baseline algorithms, PFC achieved a higher F1 score at 0.72 (under the team name BCJR). To generalise the model, we also created a method to bootstrap the training set deterministically without human labelling and at no financial cost. By releasing PFC and the dataset augmentation software to the public1, we hope to invite more collaboration. Show more