datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dojo_sector_symbol_relations
Languages: 简体中文 · English
dojo_sector_symbol_relations — Stock–Sector Mapping
Overview
Maps each stock to L1/L2/L3 sector paths with primary and secondary assignments. One row per (ticker, market) pair.
Files
File
Description
data.parquet
Full stock ↔ sector relations
Key Fields
Field
Description
ticker
Stock symbol
market
us, cn, or hk
primary
JSON object — primary sector path
secondary
JSON array —… See the full description on the dataset page: https://huggingface.co/datasets/AlphaDojo/dojo_sector_symbol_relations.SP_Relational_PlacementThis dataset was created using LeRobot. Episode 40 is a duplicate "Place the pink marker to the back of the green block."
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 51,
"total_frames": 40180,
"total_tasks": 9,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:51"
},
"data_path":… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/SP_Relational_Placement.factnet_relations
FactNet Relations Dataset
Overview
The Synset Relations dataset contains rich semantic relationships between FactSynsets, enabling advanced reasoning and cross-lingual fact retrieval. These relations capture hypernymy, causality, temporality, geographic relationships, and other semantic connections between facts.
Paper: https://arxiv.org/abs/2602.03417
Github: https://github.com/yl-shen/factnet
Dataset: https://huggingface.co/collections/openbmb/factnet… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/factnet_relations.Relation252K
Relation252K Dataset
Paper | Github
This dataset, Relation252K, contains 218 diverse image editing tasks used to evaluate the RelationAdapter model presented in the paper "RelationAdapter: Learning and Transferring Visual Relation with Diffusion Transformers". The dataset consists of source-target image pairs designed to test the model's ability to capture and apply content-aware visual transformations.
Dataset Structure
The paired dataset is stored in a .jsonl file.… See the full description on the dataset page: https://huggingface.co/datasets/handsomeWilliam/Relation252K.RelationRecognitionRelationship_chartEgo-Exo4D-Relation-TrainEgo-Exo4D-Relation-Testnyush-galaxea-a1-relation
NYUSH Galaxea A1 — Relation
Data collected by KazimierzY.
Formats and branches
Branch
Representation
main (default)
EEF · LeRobot v2.1
v3
EEF · LeRobot v3.0
v2.1
EEF · LeRobot v2.1 (compatibility branch)
Preview
Each GIF contains both camera views on one shared playback clock. Left: Agent View; right: Wrist Camera. The timestamp shows elapsed dataset time; playback is 2× speed.
Approach the hamburger
Episode 47 ·… See the full description on the dataset page: https://huggingface.co/datasets/pengyue-polaron/nyush-galaxea-a1-relation.relational-transformerARO_VG_Relationtask1418_bless_semantic_relation_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1418_bless_semantic_relation_classification
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/task1418_bless_semantic_relation_classification.ARO-Visual-Relationgalahad-deconf-relation
Deconfounded relation set (RoboCasa)
Part of the Galahad release · Project page · Code + battery + generator
624 episodes; relation ⟂ position: anchor and target slots randomized, so "next to" / "far from" the anchor — not any remembered slot — predicts the target.
LeRobot v2.1 format. Generated by generator/collect_rc_relation.py in the release repo; the generator produces the exam (the battery) and the medicine (the training set) from the same code. This public copy is a… See the full description on the dataset page: https://huggingface.co/datasets/phi-monster/galahad-deconf-relation.synthetic-object-relations
Synthetic Object Relations Dataset
A synthetic image dataset generated with Flux Schnell featuring clean object-relation prompts designed for training spatial reasoning in vision and diffusion models.
Dataset Description
This dataset contains images generated from structured prompts describing spatial relationships between objects. Unlike typical caption datasets that use free-form text, our prompts follow consistent patterns that explicitly encode:
Object identities… See the full description on the dataset page: https://huggingface.co/datasets/AbstractPhil/synthetic-object-relations.ARO-Visual-RelationClaude-Opus-4.6-stance-distilled-RELATIONALCreated: 2026-03-11
Target: 1000 training examples for QLoRA fine-tuning
Format: OpenAI chat format (system/user/assistant), <think> reasoning traces
Most people create AI to do science problems. I'm creating an AI (Eva) that can effectively navigate life, which is more about relating with people and day-to-day reasoning.
This is the first batch of relating data I distilled from Claude Opus 4.6 oriented with a specific stance, which produces measurably better quality outputs than an unoriented… See the full description on the dataset page: https://huggingface.co/datasets/aptgetupdate/Claude-Opus-4.6-stance-distilled-RELATIONAL.rollout_groot_vision_only_Relational_PlacementThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/rollout_groot_vision_only_Relational_Placement.task1325_qa_zre_question_generation_on_subject_relation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1325_qa_zre_question_generation_on_subject_relation
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… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1325_qa_zre_question_generation_on_subject_relation.task970_sherliic_causal_relationship
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task970_sherliic_causal_relationship
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/task970_sherliic_causal_relationship.opengloss-v2.1-relations
Superseded by OpenGloss v2.2 (2026-09-08): 148,292 live lexemes and 288,304 senses — tier 5 closes the WordNet gap (38,100 entries imported from Princeton WordNet 3.0 and enriched), inflected-form headwords are folded onto their lemmas, and every inherited field carries a migrate provenance record. v2.1 stays published for reproducibility.
OpenGloss v2.1 — Relations
The OpenGloss v2.1 semantic graph as an edge list. The relations config holds every live typed edge — fourteen… See the full description on the dataset page: https://huggingface.co/datasets/mjbommar/opengloss-v2.1-relations.opengloss-v2.3-relations
OpenGloss v2.3 — Relations
The OpenGloss v2.3 semantic graph as an edge list. The relations config holds every live typed edge — fourteen relation types — with the target resolved to a sense id wherever the target's entry exists in the release, which is what makes this a sense graph rather than a word graph. The tombstoned config recovers the edges the free reconcile pass demoted, deduplicated or capped away, with the type they carried when they were removed and the reason… See the full description on the dataset page: https://huggingface.co/datasets/mjbommar/opengloss-v2.3-relations.lexical_relation_classification[Lexical Relation Classification](https://aclanthology.org/P19-1169/)task391_causal_relationship
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task391_causal_relationship
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/task391_causal_relationship.pubmed_causal_relation_pretrain_pure_textrollout_molmoact2_Reasoning_Step_076596_Relational_PlacementThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/justintiensmith/rollout_molmoact2_Reasoning_Step_076596_Relational_Placement.formal-logic-simple-order-multi-token-dynamic-objects-paired-relationship-0-100000opengloss-v2.0-relations
Superseded by OpenGloss v2.1 (2026-09-07): 109,633 lexemes and 250,003 live senses — twice this release's coverage — plus a new opengloss-v2.1-inflections form→lemma lookup. v2.0 stays published for reproducibility.
OpenGloss v2.0 — Relations
The OpenGloss v2.0 semantic graph as an edge list. The relations config holds every live typed edge — fourteen relation types — with the target resolved to a sense id wherever the target's entry exists in the release, which is what makes… See the full description on the dataset page: https://huggingface.co/datasets/mjbommar/opengloss-v2.0-relations.task1510_evalution_relation_extraction
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1510_evalution_relation_extraction
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/task1510_evalution_relation_extraction.opengloss-v2.2-relations
Superseded by OpenGloss v2.3 (2026-09-09): tier 6 adds ~12,000 named entities (people, places, organizations, works, events) with entity_type, Wikidata ids and alias_of links, and every proper noun in the release is now typed. v2.2 stays published for reproducibility.
OpenGloss v2.2 — Relations
The OpenGloss v2.2 semantic graph as an edge list. The relations config holds every live typed edge — fourteen relation types — with the target resolved to a sense id wherever the… See the full description on the dataset page: https://huggingface.co/datasets/mjbommar/opengloss-v2.2-relations.