KQA Pro is a large-scale dataset of complex question answering over knowledge base, which provides strong supervision of SPARQL and program for each question. Here is its homepage website.

This repo implements several baselines for the dataset:

• Blind GRU. It predicts the answer in terms of only the input question, ignoring the knowledge base. We use it to measure the dataset bias.
• KVMemNN (Key-Value Memory Networks)
• RGCN (Relational Graph Convolutional Networks)
• SRN (Stepwise Relational Networks)
• RNN seq2seq SPARQL parser
• RNN seq2seq program parser
• BART seq2seq SPARQL parser
• BART seq2seq program parser

Instructions of how to run these models are described in their README files. Before trying them, you need to first download the dataset and unzip it into the folder ./dataset. The file tree should be like

.
+-- dataset
|   +-- kb.json
|   +-- train.json
|   +-- val.json
|   +-- test.json
+-- GRU
|   +-- preprocess.py
|   +-- train.py
|   +-- ...
+-- KVMemNN
+-- RGCN
...