fever
Datasets
All datasets matching “fever”nli_fever
Overview
The original dataset can be found here
while the Github repo is here.
This dataset has been proposed in Combining fact extraction and verification with neural semantic matching networks. This dataset has been created as a modification
of FEVER.
In the original FEVER setting, the input is a claim from Wikipedia and the expected output is a label.
However, this is different from the standard NLI formalization which is basically a pair-of-sequence to label problem.
To… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/nli_fever.FEVER_test_top_250_only_w_correct-v2
FEVERHardNegatives
An MTEB dataset
Massive Text Embedding Benchmark
FEVER (Fact Extraction and VERification) consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. 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
Encyclopaedic, Written… See the full description on the dataset page: https://huggingface.co/datasets/mteb/FEVER_test_top_250_only_w_correct-v2.fever
Dataset Card for "fever"
Dataset Summary
With billions of individual pages on the web providing information on almost every conceivable topic, we should have
the ability to collect facts that answer almost every conceivable question. However, only a small fraction of this
information is contained in structured sources (Wikidata, Freebase, etc.) – we are therefore limited by our ability to
transform free-form text to structured knowledge. There is, however, another problem… See the full description on the dataset page: https://huggingface.co/datasets/fever/fever.fever_gold_evidence
Dataset Card for fever_gold_evidence
Dataset Summary
Dataset for training classification-only fact checking with claims from the FEVER dataset.
This dataset is used in the paper "Generating Label Cohesive and Well-Formed Adversarial Claims", EMNLP 2020
The evidence is the gold evidence from the FEVER dataset for REFUTE and SUPPORT claims.
For NEI claims, we extract evidence sentences with the system in "Christopher Malon. 2018. Team Papelo: Transformer Networks at FEVER.… See the full description on the dataset page: https://huggingface.co/datasets/copenlu/fever_gold_evidence.climate-fever
ClimateFEVER
An MTEB dataset
Massive Text Embedding Benchmark
CLIMATE-FEVER is a dataset adopting the FEVER methodology that consists of 1,535 real-world claims (queries) regarding climate-change. The underlying corpus is the same as FVER.
Task category
t2t
Domains
Encyclopaedic, Written
Reference
https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using… See the full description on the dataset page: https://huggingface.co/datasets/mteb/climate-fever.climate_fever
Dataset Card for ClimateFever
Dataset Summary
A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets… See the full description on the dataset page: https://huggingface.co/datasets/tdiggelm/climate_fever.