datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NER
Adapting Large Language Models to Domains via Continual Pre-Training
This repo contains the NER dataset used in our ICLR 2024 paper Adapting Large Language Models via Reading Comprehension.
We explore continued pre-training on domain-specific corpora for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a simple method… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/NER.ner_court_decisions
Basic Information
This dataset is converted from fewshot-goes-multilingual/cs_czech-court-decisions-ner using script convert_ner_court_decisions.py.
For longer texts (>200 ws tokens), the script samples text around the selected entity. It always follows form "<initial 20 ws tokens>, ..., <sampled window>".
Then it extracts category name for the entity, all occurences of such entity in the text, and creates simple json representation. For example:
{
"label": "Reference na rozhodnutí… See the full description on the dataset page: https://huggingface.co/datasets/CZLC/ner_court_decisions.vc-deal-flow-signal-glossary
VC Deal Flow Signal Glossary
The controlled vocabulary used across the VC Deal Flow Signal site —
84 definitions covering code-side sourcing, engineering acceleration
metrics, discoverability surfaces (programmatic SEO, AEO, GEO, AIO),
agent infrastructure (MCP, A2A, x402), academic citation infrastructure,
and venture vocabulary including the SaaS efficiency quintet (burn
multiple, magic number, CAC payback, LTV, quick ratio).
Maintained as a single source of truth and refreshed… See the full description on the dataset page: https://huggingface.co/datasets/the-data-nerd/vc-deal-flow-signal-glossary.DXwand-qna-with-context-dataset
QnA with Context Dataset
A bilingual (Arabic–English) question-answering dataset with context, designed to benchmark and fine-tune models on a wide range of reading comprehension and retrieval-augmented generation (RAG) scenarios.
Dataset Description
This dataset provides question–context–answer triples for training and evaluating QA models. It covers both Arabic and English, spans multiple domains, and includes carefully curated negative samples to challenge models on… See the full description on the dataset page: https://huggingface.co/datasets/nermineatif/DXwand-qna-with-context-dataset.ner_dataset.csv
Dataset : Name Entity Recognition
The dataset used is a custom NER dataset provided in CSV format with columns:
sentence_id: Unique identifier for sentences.
words: The words in each sentence.
labels: The named entity labels corresponding to each word.
my_uni_nerFunder-NER
Dataset Card for Dataset Named Entity Recognition of funders of scientific research
Dataset Summary
Training/test set for automatically identifying funder entities mentioned in scientific papers. This data set is generated from Open Access documents hosted at https://econstor.eu and manually curated/labeled.
Supported Tasks and Leaderboards
The dataset is for training and testing the automatic recognition of funders as they are acknowledged in scientific… See the full description on the dataset page: https://huggingface.co/datasets/ZBWatHF/Funder-NER.Zarma_NER
ZarmaNER-600 Dataset
Dataset Description
ZarmaNER-600 is a gold-standard dataset for Named Entity Recognition (NER) in Zarma. This dataset contains 600 manually annotated sentences, making it the first publicly available NER corpus for Zarma. It was created to support research in low-resource NLP, particularly for sequence tagging tasks, as part of the Rule-to-Tag (R2T) framework introduced in our paper, "R2T: A Case Study in Principled Learning for Low-Resource POS… See the full description on the dataset page: https://huggingface.co/datasets/27Group/Zarma_NER.