Learning to Exploit Structured Resources for Lexical Inference

Learning to Exploit Structured Resources for Lexical Inference.
Vered Shwartz, Omer Levy, Ido Dagan and Jacob Goldberger. CoNLL 2015. [pdf] [supplementary]

This paper presents a supervised framework for automatically selecting an optimized subset of resource relations for a given target inference task. Our approach enables the use of large-scale knowledge resources, thus providing a rich source of high-precision inferences over proper-names.

Code

The code used in this paper is publicly available on GitHub.

Data

The proper-names dataset used in this paper, as well as their train/test splits, is available for download here.

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