SynKB: Semantic Search for Chemical Synthesis Procedures

This repo provides the code and data to replicate our system "SynKB: Semantic Search for Synthetic Procedures", which is accepted to EMNLP 2022 Demo track.

@article{bai-etal-2022-synkb,
  title={SynKB: Semantic Search for Synthetic Procedures},
  author={Bai, Fan and Ritter, Alan and Madrid, Peter and Freitag, Dayne and Niekrasz, John},
  journal={arXiv preprint arXiv:2208.07400},
  year={2022}
}

System Overview

SYNKB is an open-source web-based search engine that allows users, like chemists, to perform structured queries over a large corpus of synthesis procedures extracted from chemical patents.

Demo URL: https://tinyurl.com/synkb
Introduction video: https://screencast-o-matic.com/watch/c3jVQsVZwOV

Installation

Create conda environment

git clone https://github.com/bflashcp3f/SynKB.git
cd SynKB
conda env create -f environment.yml
conda activate synkb

Set up Odinson search

1. Clone the Odinson repo

git clone https://github.com/bflashcp3f/odinson.git
cd odinson
git checkout synkb

2. Set up indexed data path

mkdir -p extra/data/pets/
cd extra/data/pets/

3. Download indexed data (index.tar.gz) and extract files

tar -xvzf index.tar.gz

4. Launch Odinson (Java 11 is required)

cd ../../../
sbt backend/run

Set up Elasticsearch

1. Download Elasticsearch folder (elastic_data.tar.gz), and extract files.

tar -xvzf elastic_data.tar.gz

2. Launch Elasticsearch

cd elasticsearch-6.8.19
./bin/elasticsearch

Usage

Launch the demo

cd SynKB
python manage.py runserver YOUR_PORT_NUMBER

Customization

If you want to customize SynKB for your own data, check out this tutorial.