WIEN : Wordwise Inference and Entailment Now Or : How We Taught Machines to Recognize Natural Language Inference

@inproceedings{Billovits2015WIENW,
  title={WIEN : Wordwise Inference and Entailment Now Or : How We Taught Machines to Recognize Natural Language Inference},
  author={Chris Billovits and Mihail Eric and Chris R. Guthrie},
  year={2015}
}
The problem of inferring textual entailment relations is a fundamental challenge in natural language understanding. Building systems with the ability to recognize entailment relationships across sentences is a crucial step in achieving complete machine-level semantic understanding. We propose a multi-label classification model, implementing a random forest classifier with a carefully engineered and selected collection of linguistic and semantic features, to tackle this problem. Our system… CONTINUE READING

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