extractive
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.