Semantic Operator Prediction and Applications
- URL: http://arxiv.org/abs/2301.00399v1
- Date: Sun, 1 Jan 2023 13:20:57 GMT
- Title: Semantic Operator Prediction and Applications
- Authors: Farshad Noravesh
- Abstract summary: 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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- 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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