Omkar2118/datasets huggingface dataset:
CaRB
Full name: Crowdsourced automatic open Relation extraction Benchmark

CaRB [Bhardwaj et al., 2019] is developed by re-annotating the dev and test splits of OIE2016 via crowd-sourcing. Besides improving annotation quality, CaRB also provides a new matching scorer. CaRB scorer uses token level match and it matches relation with relation, arguments with arguments.

Source: https://arxiv.org/pdf/2205.11725.pdf (section 3.1)

Introducing paper: CaRB: A Crowdsourced Benchmark for Open IE
LSOIE
Full name: Large-Scale dataset for Supervised Open Information Extraction

LSOIE is a large-scale OpenIE data converted from QA-SRL 2.0 in two domains, i.e., Wikipedia and Science. It is 20 times larger than the next largest human-annotated OpenIE data, and thus is reliable for fair evaluation. LSOIE provides n-ary OpenIE annotations and gold tuples are in the 〈ARG0, Relation, ARG1, . . . , ARGn〉 format. The dataset has two subsets ... namely LSOIE-wiki and LSOIE-sci, for comprehensive evaluation. LSOIE-wiki has 24,251 sentences and LSOIE-sci has 47,919 sentences.

Source: https://arxiv.org/pdf/2212.02068v1.pdf (section 5)

Introducing paper: LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction
DigiCall
Full name: DigiCall: Earning Calls Dataset

We release 3.691 earning call transcripts and also annotated data set, labeled particularly for the digital strategy maturity by linguists. 
https://github.com/hpataci/DigiCall
SkinCon
Full name: SKIN Concepts Dataset

**SkinCon** is a skin disease dataset densely annotated by dermatologists. SkinCon includes 3230 images from the Fitzpatrick 17k skin disease (Fitzpatrick Skin Tone) dataset densely labelled with 48 clinical concepts, 22 of which have at least 50 images representing the concept. The concepts used were chosen by two dermatologists considering the clinical descriptor terms used to describe skin lesions. Examples include "plaque", "scale", and "erosion".

Source: [SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis](https://arxiv.org/pdf/2302.00785v1.pdf)

Introducing paper: SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained model debugging and analysis
Rice Grains BRRI
Full name: Rice Grain Disease Dataset for False Smut and Neck Blast

dataset (balanced) of 200 images consists of three classes - False Smut, Neck Blast and healthy grain class. Some of these images contain both diseases together. Field data collected under the supervision of staff from the Bangladesh Rice Research Institute (BRRI).

Introducing paper: Rice grain disease identification using dual phase convolutional neural network based system aimed at small dataset
The Copiale Cipher

The Copiale Cipher is a 105 pages manuscript containing all in all around 75 000 characters. Beautifully bound in green and gold brocade paper, written on high quality paper with two different watermarks, the manuscript can be dated back to around 1750. Apart from what is obviously an owner's mark (“Philipp 1866”) and a note in the end of the last page (“Copiales 3”), the manuscript is completely encoded. The cipher employed consists of 100 different symbols, comprising all from Latin and Greek letters, to diacritics and graphich signs such as Zodiac and alchemical symbols. Catchwords (preview fragments) of one to three or four characters are written at the bottom of left–hand pages.

Transcription, transliteration and decipherment brought to light a German text obviously related to an 18th century secret society, namely the "oculist order". A parallel manuscript is located at the Niedersächsisches Landesarchiv, Staatsarchiv Wolfenbüttel, Germany.
Fontenay Dataset

This data set encompasses 104 images and transcriptions of digital images of original charters from the Cistercian abbey Fontenay in Burgundy (France), dating mainly from the 12th c. and until 1213. The original data set was created as part of the ANR ORIFLAMMS (ANR-12-CORP-0010) project. Texts were transcribed in the original TEI-XML format, rendering both abbreviated and expanded forms of the original text. The alignment data was produced by merging coordinates created through the Oriflamms software.  A new version was prepared in March-June 2022 as part of the research for the following paper: Camps, Jean-Baptiste, Chahan Vidal-Gorène, Dominique Stutzmann, Marguerite Vernet, and Ariane Pinche. « Data Diversity in Handwritten Text Recognition: Challenge or Opportunity? » In Digital Humanities 2022. Conference Abstracts (The University of Tokyo, Japan, 25-29 July 2022), published by DH2022 Local Organizing Committee, 160‑65. Tokyo, 2022.
Google1000

A collection of 1000 public domain volumes that were scanned as part of the Google Book Search project. It is being distributed to support research in a variety of disciplines. Each volume comes
with the scanned images, OCR output, page tags and basic metadata. The volumes in this dataset are written in 4 languages: English, French, Italian and Spanish. This document describes the organization of the dataset and the file formats.