datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
blurbs-clustering-s2sThis dataset can be used as a benchmark for clustering word embeddings for German.
The datasets contains book titles and is based on the dataset from the GermEval 2019 Shared Task on Hierarchical Classification of Blurbs. It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to MTEB's ArxivClusteringS2S.
Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/blurbs-clustering-s2s.blurbs-clustering-p2pThis dataset can be used as a benchmark for clustering word embeddings for German.
The datasets contains book titles and is based on the dataset from the GermEval 2019 Shared Task on Hierarchical Classification of Blurbs. It contains 18'084 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to MTEB's ArxivClusteringP2P.
Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/blurbs-clustering-p2p.blurbThe BioCreative II Gene Mention task. The training corpus for the current task consists mainly of the training and testing corpora (text collections) from the BCI task, and the testing corpus for the current task consists of an additional 5,000 sentences that were held 'in reserve' from the previous task. In the current corpus, tokenization is not provided; instead participants are asked to identify a gene mention in a sentence by giving its start and end characters. As before, the training set consists of a set of sentences, and for each sentence a set of gene mentions (GENE annotations).
- Homepage: https://biocreative.bioinformatics.udel.edu/tasks/biocreative-ii/task-1a-gene-mention-tagging/
- Repository: https://github.com/cambridgeltl/MTL-Bioinformatics-2016/raw/master/data/
- Paper: Overview of BioCreative II gene mention recognition
https://link.springer.com/article/10.1186/gb-2008-9-s2-s2BLURB
Dataset Card for BLURB
Dataset Summary
BLURB is a collection of resources for biomedical natural language processing. In general domains, such as newswire and the Web, comprehensive benchmarks and leaderboards such as GLUE have greatly accelerated progress in open-domain NLP. In biomedicine, however, such resources are ostensibly scarce. In the past, there have been a plethora of shared tasks in biomedical NLP, such as BioCreative, BioNLP Shared Tasks, SemEval, and BioASQ… See the full description on the dataset page: https://huggingface.co/datasets/EMBO/BLURB.BLURB-synth
BLURB-synth: Synthetic audio data based on BLURB corpora
Dataset Summary
Synthetic audio data based on BLURB corpora. More details coming soon...
Supported Tasks and Leaderboards
Biomedical Language Understanding and Reasoning Benchmark (BLURB)
Text-to-Speech
Automatic-Speech-Recognition
Languages
English
Data Structure
Data Instances
Coming soon...
Data Fields
Coming soon...… See the full description on the dataset page: https://huggingface.co/datasets/uy-rrodriguez/BLURB-synth.Irish-Book-Blurbs
Irish-Language Book Metadata (Litriocht.com)
This dataset contains metadata only — titles, authors, publishers, and
descriptive blurbs — for 5,696 Irish-language books. It does not
contain the full text of any book.
The purpose is to help people discover and find Irish-language books.
Each record includes a permalink pointing to the book's page on
Litriocht.com where the physical book can be purchased.
What This Dataset Is
Book titles in Irish
Short descriptive… See the full description on the dataset page: https://huggingface.co/datasets/DanielGallagherIRE/Irish-Book-Blurbs.blurb-pubmedqaBlurbsClusteringS2S.v2
BlurbsClusteringS2S.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of book titles. Clustering of 28 sets, either on the main or secondary genre.
Task category
t2c
Domains
Fiction, Written
Reference
https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/BlurbsClusteringS2S.v2.PubmedQA_BlurbBlurbsClusteringP2P
BlurbsClusteringP2P
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of book titles+blurbs. Clustering of 28 sets, either on the main or secondary genre.
Task category
t2c
Domains
Written
Reference
https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/BlurbsClusteringP2P.BlurbsClusteringP2P.v2
BlurbsClusteringP2P.v2
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of book titles+blurbs. Clustering of 28 sets, either on the main or secondary genre.
Task category
t2c
Domains
Fiction, Written
Referencehttps://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/BlurbsClusteringP2P.v2.BlurbsClusteringS2S
BlurbsClusteringS2S
An MTEB dataset
Massive Text Embedding Benchmark
Clustering of book titles. Clustering of 28 sets, either on the main or secondary genre.
Task category
t2c
Domains
Written
Reference
https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html
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(["BlurbsClusteringS2S"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/BlurbsClusteringS2S.Paper_1_PubmedQA_Blurb-dataset