VQuAnDa - Verbalization Question Answering Dataset

Introduction

We introduce a KBQA dataset containing verbalizations of answers. The dataset is based on LC-QuAD which uses DBpedia v04.16 as the target KB.

VQuAnDa details

The dataset contains 5000 examples and we have already split it in train (80%) and test (20%) sets.

• dataset/ here you will find the dataset files (train, test).

The dataset is stored in JSON dumps and each instance contains 4 key-value pairs:

{
    "uid": "Unique id in the dataset",
    "question": "Question",
    "verbalized_answer": "Answer verbalization",
    "query": "SPARQL query of the question"
}

Baseline models

Alongside the dataset, we provide some baseline models. Here you can find the baseline implementations and instructions for how to run them.

License

The dataset is under Attribution 4.0 International (CC BY 4.0)

Cite

@InProceedings{kacupaj2020vquanda,
    title={VQuAnDa: Verbalization QUestion ANswering DAtaset},
    author={Kacupaj, Endri and Zafar, Hamid and Lehmann, Jens and Maleshkova, Maria},
    booktitle={The Semantic Web},
    pages={531--547},
    year={2020},
    publisher={Springer International Publishing},
}