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SmBoP: Semi-autoregressive Bottom-up Semantic Parsing

Author implementation of this NAACL 2021 paper.

Install & Configure

  1. Install pytorch 1.8.1 that fits your CUDA version

  2. Install the rest of required packages

    pip install -r requirements.txt
    
  3. Run this command to install NLTK punkt.

python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords')"
  1. Download the dataset from the official Spider dataset website

  2. Edit the config files configs/defaults.jsonnet to update the location of the dataset:

local dataset_path = "dataset/";

Training the parser

Use the following command to train:

python exec.py 

First time loading of the dataset might take a while (a few hours) since the model first loads values from tables and calculates similarity features with the relevant question. It will then be cached for subsequent runs.

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  • Python 96.9%
  • Jsonnet 2.8%
  • Shell 0.3%