Corpus ID: 218581125

Temporal Common Sense Acquisition with Minimal Supervision

@article{Zhou2020TemporalCS,
  title={Temporal Common Sense Acquisition with Minimal Supervision},
  author={Ben Zhou and Qiang Ning and Daniel Khashabi and Dan Roth},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.04304}
}
  • Ben Zhou, Qiang Ning, +1 author Dan Roth
  • Published in ArXiv 2020
  • Computer Science
  • Temporal common sense (e.g., duration and frequency of events) is crucial for understanding natural language. However, its acquisition is challenging, partly because such information is often not expressed explicitly in text, and human annotation on such concepts is costly. This work proposes a novel sequence modeling approach that exploits explicit and implicit mentions of temporal common sense, extracted from a large corpus, to build TACOLM,1 a temporal common sense language model. Our method… CONTINUE READING

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    SHOWING 1-10 OF 46 REFERENCES

    Determining Event Durations: Models and Error Analysis

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    English gigaword

    • David Graff, Junbo Kong, Ke Chen, Kazuaki Maeda.
    • Linguistic Data Consortium, Philadelphia, 4(1):34.
    • 2003
    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Defending Against Neural Fake News

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Extending TimeML With Typical Durations Of Events

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    English gigaword. Linguistic Data Consortium

    • David Graff, Junbo Kong, Ke Chen, Kazuaki Maeda
    • 2003
    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL