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title: README
emoji: 🐨
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colorTo: indigo
sdk: static
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---

**💪 Feel free to join the organization if you want to add a dataset with a similar purpose :) Please [tell me](https://tillwenke.github.io/about/) about your dataset before asking to join the org.**

To test your **RAG** and other **semantic information retrieval solutions** it would be powerful to have access to a dataset that consists of a text corpus,
correct responses to queries (e.g. question-answer) to test the solution end-to-end and maybe even a set of relevant passages
from the text corpus for each query to test the retrieval component separately as well.
We call this a question-answer-passages dataset.

There are plenty of large-scale datasets of this kind such as [Google's Natural Questions](https://ai.google.com/research/NaturalQuestions/).

Still we lack such datasets that are **small-scale** and **narrow-domain** to just test our RAG solution quickly or to see how it performs
in a certain domain context.

We created this space to create a collections of such datasets to boost the developement of RAG solutions and welcome any feedback about how your ideal RAG-Dataset would look like. :)

Datasets consist of:
* A **text corpus** already split into passages, referencing passages by id.
* A dataset for testing consistig of:
  * A **question**, and one or ideally both of the followin.
  * A correct **short answer**.
  * A **list of the passage ids** that are relevant to answer the question.