In this paper we propose a novel method to automatically extract large textual entailment datasets homogeneous to existing ones. The key idea is the combination of two intuitions: (1) the use of Wikipedia to extract a large set of textual entailment pairs; (2) the application of semisupervised machine learning methods to make the extracted dataset homogeneous to the existing ones. We report empirical evidence that our method successfully expands existing textual entailment corpora.
In REF , two versions of Wikipedia and semi-supervised machine learning methods are used to extract large TE data sets similar to the ones provided for the RTE challenges.
Expanding textual entailment corpora fromWikipedia using co-training
Proceedings of the 2nd Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources
Computer Science