| --- |
| license: odc-by |
| task_categories: |
| - question-answering |
| language: |
| - en |
| pretty_name: ASTRA-QA |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: questions |
| default: true |
| data_files: |
| - split: train |
| path: questions.jsonl |
| - config_name: corpus |
| data_files: |
| - split: train |
| path: corpus.jsonl |
| --- |
| |
| # ASTRA-QA: A Benchmark for Abstract Question Answering over Documents |
|
|
| ASTRA-QA, short for AbSTRAct Question Answering over documents, is a dataset and benchmark for document-level, synthesis-heavy question answering in retrieval-augmented generation systems. |
| It evaluates whether a system can read long documents, organize evidence, and produce grounded abstractive answers with reference-based assessment, rather than only retrieve short facts. |
|
|
| ## Dataset Summary |
|
|
| - **869 questions** in total |
| - **5 task types**: `Single-Sum`, `Pair-Comp`, `Multi-Comp`, `Enum`, and `Temp` |
| - **2 source domains**: academic documents and news documents |
| - **3 retrieval scopes** used in the benchmark: `Simple`, `Middle`, and `Hard` |
|
|
| ## Dataset Files |
|
|
| - `corpus.jsonl`: source documents used for retrieval and evidence grounding |
| - `questions.jsonl`: abstractive question-answer pairs with topic-set style answers and benchmark metadata |
|
|
| ## Task Types |
|
|
| - **Single-Sum**: summarize a single document into a compact grounded answer |
| - **Pair-Comp**: compare two documents, methods, entities, or events |
| - **Multi-Comp**: synthesize comparisons across multiple targets |
| - **Enum**: enumerate key items, themes, findings, or contributions |
| - **Temp**: reconstruct temporally evolving events over a time window |
|
|
| ## Data Sources |
|
|
| ASTRA-QA is constructed from publicly available sources, including arXiv, OpenReview, and news articles collected through `mediastack.com`. |
|
|
| ## License |
|
|
| This dataset is released under the Open Data Commons Attribution License (`ODC-By`). |
|
|
| The `ODC-By` license applies to the dataset annotations, organization, metadata, and benchmark construction. |
| Original source documents remain subject to their respective licenses and terms of use. |
| Users are responsible for complying with the original licenses and source-specific usage terms when using the source content. |
|
|
| ## Citation |
|
|
| Citation information will be added when the paper is released. |
|
|
