extractive-qa
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.drcd-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.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.
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.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.