SimpleQuestions is a large-scale factoid question answering dataset. It consists of 108442 natural language questions, each paired with a corresponding fact ...

This dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support.

This repository provides a version of the SimpleQuestions dataset mapped to Wikidata. Description Data is organized in 6 files.

Large-scale Simple Question Answering with Memory Networks. 2015. SimpleQuestions. SimpleQuestions is a large-scale factoid question answering dataset.

Created by Bordes et al. at 2015, the The SimpleQuestions Dataset Dataset for question answering with human generated questions paired with a corresponding fact ...

To address this problem, we present SimpleDBpediaQA, a new benchmark dataset for simple question answering over knowledge graphs that was created by mapping ...

To this end, we introduce a new dataset of 100k questions that we use in conjunction with existing benchmarks. We conduct our study within the framework of ...

24 апр. 2018 г. · Abstract:The SimpleQuestions dataset is one of the most commonly used benchmarks for studying single-relation factoid questions.

This dataset has everything you need to try your own hand at this task. Can you correctly generate the answer to questions given the Wikipedia article text?

30 окт. 2024 г. · A factuality benchmark called SimpleQA that measures the ability for language models to answer short, fact-seeking questions.