dbpedia
Datasets
All datasets matching “dbpedia”dbpedia_14
Dataset Card for DBpedia14
Dataset Summary
The DBpedia ontology classification dataset is constructed by picking 14 non-overlapping classes
from DBpedia 2014. They are listed in classes.txt. From each of thse 14 ontology classes, we
randomly choose 40,000 training samples and 5,000 testing samples. Therefore, the total size
of the training dataset is 560,000 and testing dataset 70,000.
There are 3 columns in the dataset (same for train and test splits), corresponding to… See the full description on the dataset page: https://huggingface.co/datasets/fancyzhx/dbpedia_14.DBPedia_test_top_250_only_w_correct-v2
DBPediaHardNegatives
An MTEB dataset
Massive Text Embedding Benchmark
DBpedia-Entity is a standard test collection for entity search over the DBpedia knowledge base. The hard negative version has been created by pooling the 250 top documents per query from BM25, e5-multilingual-large and e5-mistral-instruct.
Task category
t2t
Domains
Written, Encyclopaedic
Reference
https://github.com/iai-group/DBpedia-Entity/
How to evaluate on this task
You can evaluate… See the full description on the dataset page: https://huggingface.co/datasets/mteb/DBPedia_test_top_250_only_w_correct-v2.dbpedia-entities-openai-1M1M OpenAI Embeddings -- 1536 dimensions
Created: June 2023.
Text used for Embedding: title (string) + text (string)
Embedding Model: text-embedding-ada-002
First used for the pgvector vs VectorDB (Qdrant) benchmark: https://nirantk.com/writing/pgvector-vs-qdrant/
Citation
@dataset{dbpedia-entities-openai-1M,
doi = {10.57967/hf/6768},
url = {https://huggingface.co/datasets/KShivendu/dbpedia-entities-openai-1M},
author = {{Kumar Shivendu} and {Nirant Kasliwal}},
title =… See the full description on the dataset page: https://huggingface.co/datasets/KShivendu/dbpedia-entities-openai-1M.dbpedia
DBPedia
An MTEB dataset
Massive Text Embedding Benchmark
DBpedia-Entity is a standard test collection for entity search over the DBpedia knowledge base
Task category
t2t
Domains
Written, Encyclopaedic
Reference
https://github.com/iai-group/DBpedia-Entity/
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["DBPedia"])
evaluator = mteb.MTEB(task)
model =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/dbpedia.dbpedia-entities-openai3-text-embedding-3-large-1536-1M1M OpenAI Embeddings: text-embedding-3-large 1536 dimensions
Created: February 2024.
Text used for Embedding: title (string) + text (string)
Embedding Model: OpenAI text-embedding-3-large
This dataset was generated from the first 1M entries of https://huggingface.co/datasets/BeIR/dbpedia-entity, extracted by @KShivendu_ here
dbpedia_openai_1m
DBpedia OpenAI 1M Dataset
A comprehensive vector database resource containing 1,000,000 DBpedia entity descriptions with pre-computed OpenAI text-embedding-ada-002 embeddings (1536-D). This dataset is optimized for large-scale similarity search, retrieval tasks, and distributed vector database deployments.
Dataset Overview
Size: 1,000,000 base vectors + 10,000 query vectors
Embedding Model: OpenAI text-embedding-ada-002
Dimensions: 1536
Source:… See the full description on the dataset page: https://huggingface.co/datasets/maknee/dbpedia_openai_1m.