datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
turkish-extractive-qa-1.5m
Turkish Extractive QA 1.5M v2
Cevap metni ve başlangıç konumu doğrulanabilir Türkçe çıkarımsal soru-cevap kayıtları.
Doğrulanmış boyut
Train: 1,470,000
Validation: 15,000
Test: 15,000
Toplam: 1,500,000
Ana görev sütunları: id, context, question, answer, answer_start, question_type
Provenance
Veri insan mesajlarından, belgelerinden veya web kazımasından alınmamıştır. Tamamı
depodaki üretici koduyla deterministik olarak oluşturulur. Her satırda… See the full description on the dataset page: https://huggingface.co/datasets/GoktugD/turkish-extractive-qa-1.5m.extractive_qa_question_answering_hr
Dataset Card
HR-Multiwoz is a fully-labeled dataset of 5980 extractive qa spanning 10 HR domains to evaluate LLM Agent. It is the first labeled open-sourced conversation dataset in the HR domain for NLP research.
Please refer to HR-MultiWOZ: A Task Oriented Dialogue (TOD) Dataset for HR LLM Agent for details about the dataset construction.
Dataset Sources
Repository: xwjzds/extractive_qa_question_answering_hr
Paper: HR-MultiWOZ: A Task Oriented Dialogue (TOD)… See the full description on the dataset page: https://huggingface.co/datasets/xwjzds/extractive_qa_question_answering_hr.HunSum-2-extractivedrcd-zhtw-extractive-qa-sft
steven0226/drcd-zhtw-extractive-qa-sft
繁體中文抽取式閱讀理解 SFT 資料集，衍生自 DRCD（Delta Reading Comprehension Dataset）。
來源與授權（重要）
原始資料：DRCD（Delta Research Center / 台達電子），
授權 CC BY-SA 3.0，內容改編自繁體中文維基百科。
論文引用：Shao et al., "DRCD: a Chinese Machine Reading Comprehension Dataset", arXiv:1806.00920.
本資料集是 DRCD 的 Adaptation（改編作品），依 CC BY-SA 授權鏈條，以 CC BY-SA 4.0 釋出。
所做的修改
將原始 SQuAD 風格 JSON 重新格式化為 chat SFT 格式（system/user/assistant 三則訊息，assistant 輸出固定 JSON schema）
從… See the full description on the dataset page: https://huggingface.co/datasets/steven0226/drcd-zhtw-extractive-qa-sft.PersianSciQA-Extractive
PersianSciQA-Extractive Dataset
Dataset Summary
The PersianSciQA-Extractive dataset is a large-scale resource featuring over 10,000 question-answer pairs for the Persian language. This dataset is specifically designed to support the training and evaluation of models on the task of extractive question answering (Extractive QA) within the scientific domain.
This work builds directly upon the foundation laid by the original safora/persian-scientific-qa dataset, which was… See the full description on the dataset page: https://huggingface.co/datasets/safora/PersianSciQA-Extractive.cnn_dailymail_extractive
Data Card for Extractive CNN/DailyMail Dataset
Overview
This is an extractive version of the CNN/Dailymail dataset. The structure of this dataset is identical to the original except for a minor modification in the data representation and the introduction of labels to denote the extractive summary.
The labels are generated following a greedy algorithm, as proposed by Liu (2019). The curation process can be found in the bertsum-hf repository. I am uploading it in case… See the full description on the dataset page: https://huggingface.co/datasets/ereverter/cnn_dailymail_extractive.TR-Extractive-QA-82KThe dataset consists of nearly 82K {Context, Question, Answer} triplets in Turkish. Since most of the answers are only a few words and taken directly from the provided context, it can be better used in in finetuning encoder-only models like BERT for extractive question answering or embedding models for retrieval. The dataset is a filtered and combined version of multiple Turkish QA-based datasets.
Please use ucsahin/TR-Extractive-QA-5K for more detailed and sampled version of this dataset.
cannabis-fda-extractive-pilot
FDA Cannabis Extractive Experimental Pilot
Experimental, automatically screened, unreviewed draft dataset. This dataset is not medical advice, is not production-ready, and must not be represented as clinician-reviewed, legally cleared, or suitable for patient-facing systems.
This small English conversational dataset was created to test an auditable Gemma 4 fine-tuning pipeline. It contains exact answer passages from captured FDA pages about CBD/cannabis safety, paired with… See the full description on the dataset page: https://huggingface.co/datasets/aznatkoiny/cannabis-fda-extractive-pilot.tigqa-extractive-qa
TIGQA — Extractive QA Subset
Dataset Summary
This repository contains a cleaned, extractive-QA-only (SQuAD-style) subset of the TIGQA
question–answering data: 1,665 question–answer pairs in Tigrinya, each with a single answer
located as an exact character span inside its context passage (answer_start and the span
length), ready for direct use in span-extraction QA training and evaluation.
Every row carries a match_status field (exact or fuzzy) recording how… See the full description on the dataset page: https://huggingface.co/datasets/Hailay/tigqa-extractive-qa.financial-reports-extractive-summarization_eval
Financial Reports Extractive Summarization Evaluation Dataset
Validation and test splits for evaluating models on Arabic financial reports extractive summarization.
Dataset Structure
Format: Simple prompt-answer pairs
Validation: ~20 examples (10%)
Test: ~20 examples (10%)
Language: Arabic
Domain: Financial reports and market news
Fields
id: Unique identifier
prompt: The summarization prompt
full_text: Complete financial report
answer: Ground… See the full description on the dataset page: https://huggingface.co/datasets/SahmBenchmark/financial-reports-extractive-summarization_eval.TR-Extractive-QA-5K
Dataset Card for Dataset Name
The dataset consists of nearly 5000 {Context, Question, Answer} triplets in Turkish. It can be used in finetuning large language models for text-generation, masked language modeling, instruction following, and extractive question answering.
The dataset is a manually curated version of multiple Turkish QA-based datasets and some of the answers are arranged by hand.
squad-extractive-qaxwjzds-extractive-qachatgpt-malaysian-extractive-qa
Synthetic Malaysian Extractive QA
Generated using ChatGPT3.5, notebooks at https://github.com/mesolitica/malaysian-dataset/tree/master/question-answer/chatgpt3.5-extractive-news
ExtractiveInsight
ExtractiveInsight
tags: information_extraction, narrative_structure, contextualization
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'ExtractiveInsight' dataset is a curated collection of paragraphs from various documents, each annotated with labels indicating the type of contextualization insights extracted from the text. These insights may include historical references, cultural context, authorial intent, or any other… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/ExtractiveInsight.HotpotQA-Extractive-Readerafrica-egypt-capmas-price-index-for-manufacturing-and-extractive-industries-349d0492
Price Index for Manufacturing and Extractive Industries | Africa (CAPMAS Egypt Open Data)
15,778 rows - 1 Africa country/area - 2013-2026 - 8 indicators - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 15,778 rows from CAPMAS Egypt Open Data, covering Price Index for Manufacturing and Extractive Industries. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-egypt-capmas-price-index-for-manufacturing-and-extractive-industries-349d0492.SQUAD-Extractive-InstructionSquad 1 & 2 together with instruction for Extractive Instruction tuning.
financial-reports-extractive-summarization_train
Financial Reports Extractive Summarization Training Dataset
Training split of the Arabic financial reports extractive summarization dataset in conversational format.
Dataset Structure
Format: Conversational (human-agent pairs)
Size: ~160 training examples (80% of total)
Language: Arabic
Domain: Financial reports and market news
Features
id: Unique identifier
conversations: Human prompt and agent summary
report_type: Type of financial report… See the full description on the dataset page: https://huggingface.co/datasets/SahmBenchmark/financial-reports-extractive-summarization_train.AMI_EXTRACTIVEextractive-arxivvidore_v3_finance_en_english_extractive_Chartvidore_v3_finance_en_english_extractive_Textextractive_qavidore_v3_hr_english_extractive_Infographicvidore_v3_pharmaceuticals_english_extractive_Chartvidore_v3_pharmaceuticals_english_extractive_Infographicvidore_v3_hr_english_extractive_Chartvidore_v3_computer_science_english_extractivevidore_v3_energy_french_extractive