Database Reasoning over Text

This repository contains the code for the Database Reasoning Over Text paper, to appear at ACL2021. Work is performed in collaboration with James Thorne, Majid Yazdani, Marzieh Saeidi, Fabrizio Silvestri, Sebastian Riedel, and Alon Halevy.

Data

The completed NeuralDB datasets can be downloaded here and are released under a CC BY-SA 3.0 license.

The dataset includes entity names from Wikidata which are released under a CC BY-SA 3.0 license. This dataset includes sentences from the KELM corpus. KELM is released under the CC BY-SA 2.0 license

Repository Structure

The repository is structured in 3 sub-folders:

  • Tools for mapping the KELM data to Wikidata identifiers are provided in the dataset construction folder ,
  • The information retrieval system for the support set generator are provided in the ssg folder
  • The models for Neural SPJ, the baseline retrieval (TF-IDF and DPR), and evaluation scripts are provided in the modelling folder.

Instructions for running each component are provided in the README files in the respective sub-folders.

Setup

All sub-folders were set up with one Python environment per folder. Requirements for each environment can be installed by running a pip install:

pip install -r requirements.txt

In the dataset-construction and modelling folders, the src folder should be included in the python path.

export PYTHONPATH=src

GitHub

https://github.com/facebookresearch/NeuralDB