Semantic Operator Prediction and Applications

Farshad Noravesh
1/1/2023
cs.CL

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Abstract

In the present paper, semantic parsing challenges are briefly introduced and QDMR formalism in semantic parsing is implemented using sequence to sequence model with attention but uses only part of speech(POS) as a representation of words of a sentence to make the training as simple and as fast as possible and also avoiding curse of dimensionality as well as overfitting. It is shown how semantic operator prediction could be augmented with other models like the CopyNet model or the recursive neural net model.

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Cite this paper

@article{noravesh2023semantic,
  title  = {Semantic Operator Prediction and Applications},
  author = {Farshad Noravesh},
  year   = {2023},
  eprint = {2301.00399},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.00399v1}
}

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