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---
dataset_info:
features:
- name: id
dtype: string
- name: embedding
sequence: float64
splits:
- name: train
num_bytes: 751739666430
num_examples: 243212198
download_size: 640572858900
dataset_size: 751739666430
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc0-1.0
tags:
- openalex
- embeddings
pretty_name: OpenAlex Mutilingual Embeddings
source_dataset:
- openalex
---
# OpenAlex Multilingual Embeddings
This dataset contains multilingual text embeddings of all records in [OpenAlex](https://openalex.org/) with a title or an abstract from the snapshot of 2023-10-20.
The dataset was created for the [FORAS project](https://asreview.nl/project/foras/) to investigate the efficacy of
different methods of searching in databases of academic publications. All scripts will be available in a [GitHub repository](https://github.com/IDfuse/foras).
The project is supported by a grant from the Dutch Research Council (grant no. 406.22.GO.048)
## Description of the data
- The dataset has two columns, `id` and `embedding`. The `id` columns contains the OpenAlex identifier of the record. The `embedding` column contains the text embedding,
which is a vector of 384 floats.
- The multilingual embedding model [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) was used to generate the embeddings. For every
with a title or abstract we generated an embedding of `'query: '` + `title` + `' '` + `abstract`. The model has a maximum token input length of 512 tokens. |