Shrinked version (48 entity type) of the turkish_ner. Original turkish_ner dataset: Automatically annotated Turkish corpus for named entity recognition and text categorizatio
An open, broad-coverage corpus for Finnish named entity recognition presented in Luoma et al. (2020) A Broad-coverage Corpus for Finnish Named Entity Recognition.
A translation of the word pair similarity dataset wordsim-353 to Twi. The dataset was presented in the paper Alabi et al.: Massive vs. Curated Embeddings for Low-Resourced La
Urdu fake news datasets that contain news of 5 different news domains. These domains are Sports, Health, Technology, Entertainment, and Business. The real news are collected b
\ VIVOS is a free Vietnamese speech corpus consisting of 15 hours of recording speech prepared for Vietnamese Automatic Speech Recognition task. The corpus was prepared by
WikiHop is open-domain and based on Wikipedia articles; the goal is to recover Wikidata information by hopping through documents. The goal is to answer text understanding quer
WinoBias, a Winograd-schema dataset for coreference resolution focused on gender bias. The corpus contains Winograd-schema style sentences with entities corresponding to peopl
A Winograd schema is a pair of sentences that differ in only one or two words and that contain an ambiguity that is resolved in opposite ways in the two sentences and requires
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained models with respect to cross-lingual natural language understanding and generation. T
XOR-TyDi QA brings together for the first time information-seeking questions, open-retrieval QA, and multilingual QA to create a multilingual open-retrieval QA dat
XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering performance. The dataset consists of a subset of 240 pa
The Yoruba GV NER dataset is a labeled dataset for named entity recognition in Yoruba. The texts were obtained from Yoruba Global Voices News articles https://yo.globalvoices.
A translation of the word pair similarity dataset wordsim-353 to Yorùbá. The dataset was presented in the paper Alabi et al.: Massive vs. Curated Embeddings for Low-Resourced