datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
task960_ancora-ca-ner_named_entity_recognition
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task960_ancora-ca-ner_named_entity_recognition
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task960_ancora-ca-ner_named_entity_recognition.danish-ner-sft-v1
danish-ner-sft-v1
Danish named-entity SFT rows derived from chcaa/dansk-ner
(DANSK), which annotates Danish Gigaword text with the 18 OntoNotes entity
types using the same scheme in every split. Each row asks for a random subset
of entity types (1-6, including types absent from the passage so the empty
marker is exercised) and renders the answer in one of fourteen output formats.
Ten are key-value, listing the extracted entities: JSON, key: value,
key=value, [key] value, value… See the full description on the dataset page: https://huggingface.co/datasets/jensjepsen/danish-ner-sft-v1.bioleaflets-biomedical-ner
Dataset Card for BioLeaflets Dataset
Dataset Summary
BioLeaflets is a biomedical dataset for Data2Text generation. It is a corpus of 1,336 package leaflets of medicines authorised in Europe, which were obtained by scraping the European Medicines Agency (EMA) website.
Package leaflets are included in the packaging of medicinal products and contain information to help patients use the product safely and appropriately.
This dataset comprises the large majority (∼ 90%) of… See the full description on the dataset page: https://huggingface.co/datasets/ruslan/bioleaflets-biomedical-ner.NEREL_bench
NEREL-bench
Summary
NEREL-bench is a benchmark dataset designed to evaluate the capabilities of Large Language Models (LLMs) in performing knowledge graph construction tasks on Russian-language texts. The dataset focuses on three fundamental tasks essential for building knowledge graphs: named entity recognition, relation extraction between entities, and generation of contextual definitions for both entities and relations. These tasks are critical for evaluating whether… See the full description on the dataset page: https://huggingface.co/datasets/bond005/NEREL_bench.complex_ner
Elephant Labs Complex PII Dataset for Long Contexts and Advanced Anonymization (with Business and Software-related Entities)
Developed by: Elephant Labs
LinkedIn: Elephant Labs
Dataset Size: 20,0000 synthetic documents
Number of tokens in text: 14,140,795 (Tokenized with tiktoken.encoding_for_model("gpt-3.5-turbo"))
Dataset Summary
Purpose: A synthetically generated dataset for advanced NER tasks, supporting both token classification and LLM fine-tuning (enabling… See the full description on the dataset page: https://huggingface.co/datasets/MorryShah/complex_ner.Generated_OE_Gregory_Dialogues_Text_and_Evaluation
Generated Old English Gregory's Dialogues (variatio)
A complete, machine-generated Old English variatio of the Old English Dialogues of
Gregory the Great (Waerferth's translation), produced on 19 July 2026, together with the
full generation and evaluation apparatus: prompt, constraint lexicon scripts, validator,
dependency parses, word embeddings, and all quantitative evaluation results.
The project is described in:
Martin Arista, J., & Nunez, M. Evaluating Generated Old… See the full description on the dataset page: https://huggingface.co/datasets/Nerthus-Project/Generated_OE_Gregory_Dialogues_Text_and_Evaluation.nero-s-progress-curriculum-token-pools
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]… See the full description on the dataset page: https://huggingface.co/datasets/j0no12/nero-s-progress-curriculum-token-pools.NEREL_instruct
NEREL-instruct
NEREL-instruct is an instruction-based dataset derived from the NEREL corpus — a large Russian dataset annotated with nested named entities, relations, and events. The original NEREL annotations (texts + manual entity/relation markup) were converted into a structured instruction-following format using Qwen2.5-32B-Instruct. The result is a semi‑synthetic dataset designed for fine‑tuning large language models (LLMs) on a variety of information extraction tasks.
The… See the full description on the dataset page: https://huggingface.co/datasets/bond005/NEREL_instruct.Nero-Titles
Nero Titles
A 727,319-row, English-dominant chat-title training corpus with published source counts, safety filtering, exact-input deduplication, and TitleBench exclusion.
Quick start
from datasets import load_dataset
dataset = load_dataset(
"json",
data_files="hf://datasets/j0no12/Nero-Titles/data.jsonl",
split="train",
)
print(len(dataset))
# 727319
print(dataset[0])
Dataset summary
Property
Value
Final rows
727,319
Raw… See the full description on the dataset page: https://huggingface.co/datasets/j0no12/Nero-Titles.dinercall-ner
dinercall‑ner
A synthetic bilingual (Chinese / English) dataset for restaurant‑reservation NER on ASR‑like utterances
📖 Overview
dinercall-ner contains 20 000 automatically generated reservation requests that mimic spoken input from an Automatic Speech Recognition (ASR) system.
Languages: 70 % Mandarin (Traditional Chinese), 30 % English.
File format: dataset.parquet (columnar, ready for datasets or pandas).
Each row provides the raw (error‑prone) utterance and… See the full description on the dataset page: https://huggingface.co/datasets/Luigi/dinercall-ner.medical-ner-sft
Medical Named Entity Recognition (NER)
Part of the AxisMapper Medical AI Suite — 16 domain-specific SFT datasets for fine-tuning medical LLMs.
Built by AmareshHebbar | Studio Ilios / Humanova Minds
What this dataset does
Clinical text → structured JSON with conditions, drugs, dosages, procedures
Why download this
Train clinical NER models to extract structured data from unstructured clinical notes. Output is JSON-formatted for downstream pipeline… See the full description on the dataset page: https://huggingface.co/datasets/AmareshHebbar/medical-ner-sft.pharmacy-ner-sft
Pharmacy NER — Drug Entity Extraction
Part of the AxisMapper Medical AI Suite — 16 domain-specific SFT datasets for fine-tuning medical LLMs.
Built by AmareshHebbar | Studio Ilios / Humanova Minds
What this dataset does
Clinical/biomedical text → drug name, dosage, frequency, route, indication
Why download this
Automate medication extraction from clinical notes, discharge summaries, or biomedical literature. Powers medication reconciliation and… See the full description on the dataset page: https://huggingface.co/datasets/AmareshHebbar/pharmacy-ner-sft.esic-nerDataset sintético para treinamento em tarefa de extração de entidades (NER) para uso em classificação de dados pessoais (PII) em formulários e-SIC.
Estatísticas do train split
Summary
samples: 4473
samples_with_any_entity: 3571 (79.83%)
samples_with_any_pii (excludes ORG_JURIDICA, DOC_EMPRESA): 2244 (50.17%)
entity_records_total: 14510
literal_occurrences_total: 14686
Note: ORG_JURIDICA and DOC_EMPRESA are labels but are treated as non-PII (excluded from PII-only… See the full description on the dataset page: https://huggingface.co/datasets/EliMC/esic-ner.lean-six-sigma-ner-360
Lean Six Sigma NER Dataset
Dataset Description
This dataset contains 360 high-quality Named Entity Recognition (NER) samples focused on Lean Six Sigma methodologies, business process improvement, and operational optimization across multiple industries. Each sample identifies and categorizes key entities, tools, and methodologies within DMAIC (Define, Measure, Analyze, Improve, Control) framework responses across diverse business domains.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/cw18/lean-six-sigma-ner-360.recipes_for_dishes_and_food_with_vectors_sentiment_ners
Description in English:
The dataset is collected from Russian-language Telegram channels with various food recipes,The dataset was collected and tagged automatically using the data collection and tagging service Scoutie.Try Scoutie and collect the same or another dataset using link for FREE.
Dataset fields:
taskId - task identifier in the Scouti service. text - main text. url - link to the publication. sourceLink - link to Telegram. subSourceLink - link to the… See the full description on the dataset page: https://huggingface.co/datasets/ScoutieAutoML/recipes_for_dishes_and_food_with_vectors_sentiment_ners.task610_conllpp_ner
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task610_conllpp_ner
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task610_conllpp_ner.Neru-66K-Bilingual-SFT
Neru-66K-Bilingual-SFT
This dataset is a high-quality, professional 66,000 (66K) row bilingual Supervised Fine-Tuning (SFT) instruction set optimized for training Large Language Models (LLMs) in both Turkish-to-English and English-to-Turkish translation tasks.
Non-Synthetic
Dataset Details
Curated by: ezfiez dev
Language(s) (NLP): Turkish, English
License: CC-BY-4.0 (Permissive license. Free to use for both commercial and personal projects, provided appropriate… See the full description on the dataset page: https://huggingface.co/datasets/ezfiez/Neru-66K-Bilingual-SFT.smolified-banglish-ner
🤏 smolified-banglish-ner
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model Arban221B/smolified-banglish-ner.
📦 Asset Details
Origin: Smolify Foundry (Job ID: b8fa685c)
Records: 10000
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by Arban221B.
Generated via Smolify.ai.
lean-six-sigma-ner-v1
Lean Six Sigma NER Dataset
Dataset Description
This dataset contains 102 high-quality Named Entity Recognition (NER) samples focused on Lean Six Sigma methodologies, business process improvement, and supply chain optimization. Each sample identifies and categorizes key entities, tools, and methodologies within DMAIC (Define, Measure, Analyze, Improve, Control) framework responses.
Dataset Structure
Data Fields
id: Unique identifier for each sample… See the full description on the dataset page: https://huggingface.co/datasets/cw18/lean-six-sigma-ner-v1.indicphi-clinical-ner-500
IndicPHI Synthetic Clinical NER (GLiNER)
Synthetic multilingual Indian clinical documents for NER / GLiNER training,
with PHI/PII surrogate entities. Produced by IndicPHI (Track C SDG).
Provenance
Source run: 20260724T100211
Artifact: data/generated/runs/20260724T100211/s9_gliner_s6_export/gliner_docs.jsonl
Rows: 479
Languages: 23
Language counts
code
n
as
22
bn
20
brx
19
doi
21
en
22
gu
21
hi
22
kn
22
kok
21
ks
21… See the full description on the dataset page: https://huggingface.co/datasets/Sidharth1743/indicphi-clinical-ner-500.Mental_Health_Support_ChatBOT_Conversation
Mental Health Support Dataset
Instruction–response pairs for training supportive, non-diagnostic,
safety-aware mental health chatbots.
Fields
instruction: user message
response: Bot reposne
category: intent label
Safety
This dataset includes crisis escalation examples and refusal patterns.
Not a replacement for professional care.
task962_ancora-ca-ner_missing_word_prediction
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task962_ancora-ca-ner_missing_word_prediction
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task962_ancora-ca-ner_missing_word_prediction.task961_ancora-ca-ner_text_auto_completion
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task961_ancora-ca-ner_text_auto_completion
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task961_ancora-ca-ner_text_auto_completion.smolified-banglish-ner
🤏 smolified-banglish-ner
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model AitijhyaR/smolified-banglish-ner.
📦 Asset Details
Origin: Smolify Foundry (Job ID: dac3e97c)
Records: 9900
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by AitijhyaR.
Generated via Smolify.ai.
smolified-engla-ner
🤏 smolified-engla-ner
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model smolify/smolified-engla-ner.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 16e31f25)
Records: 9921
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by smolify.
Generated via Smolify.ai.
smolified-banglish-ner
🤏 smolified-banglish-ner
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model Ayan-12/smolified-banglish-ner.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 849ef9b5)
Records: 9970
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by Ayan-12.
Generated via Smolify.ai.
autotrain-data-chinese-nerweather_russian_regions_with_vectors_sentiment_ner
Description in English:
The dataset is collected from Russian-language Telegram channels with weather forecasts in various regions of Russia,The dataset was collected and tagged automatically using the data collection and tagging service Scoutie.Try Scoutie and collect the same or another dataset using link FOR FREE.
Dataset fields:
taskId - task identifier in the Scoutie service. text - main text. url - link to the publication. sourceLink - link to Telegram.… See the full description on the dataset page: https://huggingface.co/datasets/ScoutieAutoML/weather_russian_regions_with_vectors_sentiment_ner.Sample_NERFsmolified-banglish-ner
🤏 smolified-banglish-ner
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model smolify/smolified-banglish-ner.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 53c8c249)
Records: 1280
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by smolify.
Generated via Smolify.ai.