Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: A model for a knowledge base-based single-relation question answering

Keyphrases: knowledge base-based single-relation question answering text

Dataset description:
KnowIT VQA: KnowIT VQA is a video dataset with 24,282 human-generated question-answer pairs about The Big Bang Theory. The dataset combines visual, textual and temporal coherence reasoning together with knowledge-based questions, which need of the experience obtained from the viewing of the series to be answered.
WikiTableQuestions: WikiTableQuestions is a question answering dataset over semi-structured tables. It is comprised of question-answer pairs on HTML tables, and was constructed by selecting data tables from Wikipedia that contained at least 8 rows and 5 columns.
AQUA: The question-answer (QA) pairs are automatically generated using state-of-the-art question generation methods based on paintings and comments provided in an existing art understanding dataset. The QA pairs are cleansed by crowdsourcing workers with respect to their grammatical correctness, answerability, and answers' correctness.
SimpleQuestions: SimpleQuestions is a large-scale factoid question answering dataset. It consists of 108,442 natural language questions, each paired with a corresponding fact from Freebase knowledge base.

Options:- A: KnowIT VQA  B: WikiTableQuestions  C: AQUA  D: SimpleQuestions
SimpleQuestions