extraction
tweet_sentiment_extraction
TweetSentimentExtractionClassification
An MTEB dataset
Massive Text Embedding Benchmark
Task category
t2c
Domains
Social, Written
Reference
https://www.kaggle.com/competitions/tweet-sentiment-extraction/overview
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(["TweetSentimentExtractionClassification"])
evaluator = mteb.MTEB(task)
model =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/tweet_sentiment_extraction.wikidata-extraction
Wikidata Extraction
This dataset contains all RDF triples extracted from the latest Wikidata, converted from the N-Triples format to Parquet.
The data originates from Wikidata, a free and open knowledge base that acts as central storage for structured data used by Wikipedia and other Wikimedia projects. The source file is the "truthy" N-Triples dump (latest-truthy.nt.bz2), which contains only the current, non-deprecated statements.
The code to extract this data is available at… See the full description on the dataset page: https://huggingface.co/datasets/piebro/wikidata-extraction.invoice-extraction-benchmark
Invoice Extraction Benchmark v1
A synthetic test set for invoice data extraction (invoice OCR, intelligent document
processing, accounts-payable capture): 181 documents with answer keys and a scorer.
Run any invoice reader over the documents, write its output as one JSON file, and score it
field by field.
Source, scorer and generator: https://github.com/DrewKraken/invoice-extraction-benchmark
(this dataset is a mirror of corpus/v1/ there; the GitHub repository is canonical).
Who… See the full description on the dataset page: https://huggingface.co/datasets/drew-ipp/invoice-extraction-benchmark.DRIVE-digital-retinal-images-for-vessel-extractionarXiv:2501.18921https://arxiv.org/abs/2501.18921
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