relations
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.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.Relationship_chartsynthetic-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.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Superseded by OpenGloss v2.2 (2026-09-08): 148,292 live lexemes and 288,304 senses — tier 5 closes the WordNet gap (38,100 entries imported from Princeton WordNet 3.0 and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.