NewsQASum is a dataset for question answering and summarization of news articles. It contains CNN articles from the overlap between the NewsQA question-answering dataset and the CNN DailyMail summarization dataset. Each article is annotated with a summary and a list of questions and corresponding answers.
Use Cases
- Training question-answering models based on annotated news articles.
- Evaluating summarization models based on provided article summaries.
- Developing multi-task NLP systems based on combined QA and summarization annotations.
- Benchmarking text retrieval systems based on the structured article-question pairs.
Strengths
- Articles are annotated with both summaries and question-answer pairs, providing multi-task utility.
- Data is sourced from established NLP corpora (NewsQA and CNN DailyMail), suggesting a known provenance.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Last updated 2023-11-24 22:55:39; freshness should be verified.
Provenance
- Source
- CNN articles from the NewsQA and CNN DailyMail datasets.
- Collection Method
- Articles at the overlap of two existing datasets were annotated with summaries and QA pairs.