Generating Natural Language Inference Chains

@article{Kolesnyk2016GeneratingNL,
  title={Generating Natural Language Inference Chains},
  author={Vladyslav Kolesnyk and Tim Rockt{\"a}schel and Sebastian Riedel},
  journal={CoRR},
  year={2016},
  volume={abs/1606.01404}
}
The ability to reason with natural language is a fundamental prerequisite for many NLP tasks such as information extraction, machine translation and question answering. To quantify this ability, systems are commonly tested whether they can recognize textual entailment, i.e., whether one sentence can be inferred from another one. However, in most NLP applications only single source sentences instead of sentence pairs are available. Hence, we propose a new task that measures how well a model can… CONTINUE READING
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