datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
statcan-dialogue-dataset-retrieval
Statcan Dialogue Dataset (Processed for Retrieval Tasks)
This is a variant of the Statcan Dialogue Dataset, which we processed specifically for multilingual retrieval (english, french). It contains everything in CSVs, rather than having metadata hosted separately.
Quickstart
from datasets import load_dataset
repo = 'McGill-NLP/statcan-dialogue-dataset-retrieval'
# load english queries, training split
queries_en = load_dataset(repo, 'queries_english', split='train') #… See the full description on the dataset page: https://huggingface.co/datasets/McGill-NLP/statcan-dialogue-dataset-retrieval.financial-retrieval
Overview
This dataset contains normalized, long-form records used to benchmark multiple chatbots on financial retrieval QA.
Each row represents a single (ticker, chatbot) pair answering one question.
These records are derived from a verification step that extracts structured fields from each chatbot’s answer.
Columns (normalized dataset)
Column
Type
Description
ticker
string
Company identifier used for the question (e.g., AAPL, 7203:JP).
question
string… See the full description on the dataset page: https://huggingface.co/datasets/daloopa/financial-retrieval.medquad-retrieval-pretriage
MedQuAD Retrieval Pre-Triage Dataset
Dataset Description
This repository contains a processed, retrieval-oriented derivative of the MedQuAD medical question-answering dataset.
It was prepared for contextual medical information retrieval in SortMed, an academic medical pre-triage assistant.
The corpus is not used to train the SortMed triage classifiers. It is used by a separate semantic retrieval component that identifies medically related question-answer entries… See the full description on the dataset page: https://huggingface.co/datasets/cristian-untaru/medquad-retrieval-pretriage.retrieval_grounding
Dino Data Retrieval Grounding Preview
What This Dataset Is
This dataset is a focused retrieval-grounding preview built from four Dino Data capability slices:
search trigger detection
grounded search integration
history search trigger
history search integration
The goal is to train or inspect assistant behavior around two connected problems:
deciding when retrieval or history lookup is needed
generating answers that stay grounded to supplied evidence or prior thread… See the full description on the dataset page: https://huggingface.co/datasets/DinoDS/retrieval_grounding.Philosophical-Triplets-Retrieval
Dataset Card: johnnyboycurtis/Philosophical-Triplets-Retrieval
This dataset is designed for training and evaluating dense retrieval models, specifically for Retrieval Augmented Generation (RAG) systems in complex, subject-matter-heavy domains. It focuses on philosophical texts, demanding high semantic fidelity from retrieval models.
Dataset Details
Feature
Value
Hugging Face Path
johnnyboycurtis/Philosophical-Triplets-Retrieval
Task
Information Retrieval… See the full description on the dataset page: https://huggingface.co/datasets/johnnyboycurtis/Philosophical-Triplets-Retrieval.Indian-Legal-Retrieval-Generation
Indian-Legal-Retrieval-Generation
An expert-verified evaluation set for retrieval-augmented question answering over Indian
court / legal documents. This is the small benchmark used in CourtNav.
Paper: CourtNav: Voice-Guided, Anchor-Accurate Navigation of Long Legal Documents in Courtrooms — Sai Khadloya, Kush Juvekar, Arghya Bhattacharya, Utkarsh Saxena.
Status: work in progress — contents and structure may still evolve.
Overview
21 lawyer-verified question/answer… See the full description on the dataset page: https://huggingface.co/datasets/adalat-ai/Indian-Legal-Retrieval-Generation.