Reasoning about Actions and State Changes by Injecting Commonsense Knowledge

@inproceedings{Tandon2018ReasoningAA,
  title={Reasoning about Actions and State Changes by Injecting Commonsense Knowledge},
  author={Niket Tandon and Bhavana Dalvi and Joel Grus and Wen-tau Yih and Antoine Bosselut and Peter Clark},
  booktitle={Conference on Empirical Methods in Natural Language Processing},
  year={2018}
}
Comprehending procedural text, e.g., a paragraph describing photosynthesis, requires modeling actions and the state changes they produce, so that questions about entities at different timepoints can be answered. [] Key Method Unlike earlier methods, we treat the problem as a neural structured prediction task, allowing hard and soft constraints to steer the model away from unlikely predictions. We show that the new model significantly outperforms earlier systems on a benchmark dataset for procedural text…

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