Iterative Paraphrastic Augmentation with Discriminative Span Alignment

1 Jul 2020  ·  Ryan Culkin, J. Edward Hu, Elias Stengel-Eskin, Guanghui Qin, Benjamin Van Durme ·

We introduce a novel paraphrastic augmentation strategy based on sentence-level lexically constrained paraphrasing and discriminative span alignment. Our approach allows for the large-scale expansion of existing resources, or the rapid creation of new resources from a small, manually-produced seed corpus. We illustrate our framework on the Berkeley FrameNet Project, a large-scale language understanding effort spanning more than two decades of human labor. Based on roughly four days of collecting training data for the alignment model and approximately one day of parallel compute, we automatically generate 495,300 unique (Frame, Trigger) combinations annotated in context, a roughly 50x expansion atop FrameNet v1.7.

PDF Abstract
No code implementations yet. Submit your code now


  Add Datasets introduced or used in this paper

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.


No methods listed for this paper. Add relevant methods here