Statements (64)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:benchmark
|
| gptkbp:bfsLayer |
6
|
| gptkbp:bfsParent |
gptkb:BERT_family
|
| gptkbp:aims_to |
machine reading comprehension models
|
| gptkbp:based_on |
real-world data
|
| gptkbp:challenges |
current AI systems
|
| gptkbp:collaborated_with |
government agencies
international researchers |
| gptkbp:collaborations |
industry partners
|
| gptkbp:consists_of |
multiple-choice questions
|
| gptkbp:contains |
over 28,000 questions
|
| gptkbp:developed_by |
Chinese researchers
|
| gptkbp:encourages |
development of advanced algorithms
|
| gptkbp:facilitates |
benchmarking of models
|
| gptkbp:has_influence_on |
subsequent benchmarks
|
| https://www.w3.org/2000/01/rdf-schema#label |
RACE benchmark
|
| gptkbp:includes |
passages from various sources
|
| gptkbp:is_accessible_by |
researchers worldwide
|
| gptkbp:is_adopted_by |
gptkb:Educational_Institution
|
| gptkbp:is_analyzed_in |
data scientists
model performance |
| gptkbp:is_associated_with |
deep learning techniques
|
| gptkbp:is_available_on |
gptkb:archive
|
| gptkbp:is_challenged_by |
emerging datasets
|
| gptkbp:is_cited_in |
numerous academic papers
|
| gptkbp:is_compared_to |
S Qu AD
|
| gptkbp:is_considered_as |
a challenging dataset
|
| gptkbp:is_designed_for |
reading comprehension
|
| gptkbp:is_designed_to |
test understanding of context
|
| gptkbp:is_discussed_in |
online forums
|
| gptkbp:is_divided_into |
two subsets
|
| gptkbp:is_documented_in |
research publications
|
| gptkbp:is_evaluated_by |
statistical methods
accuracy metrics peer review process robustness cross-validation techniques |
| gptkbp:is_explored_in |
case studies
thesis and dissertations |
| gptkbp:is_implemented_in |
various programming languages
|
| gptkbp:is_influenced_by |
advancements in AI technology
|
| gptkbp:is_integrated_with |
AI development frameworks
|
| gptkbp:is_part_of |
reading comprehension tasks
AI evaluation frameworks |
| gptkbp:is_popular_in |
AI research community
|
| gptkbp:is_prominent_in |
machine learning literature
|
| gptkbp:is_promoted_by |
workshops and conferences
|
| gptkbp:is_recognized_by |
AI competitions
|
| gptkbp:is_referenced_in |
academic curricula
|
| gptkbp:is_related_to |
natural language understanding
|
| gptkbp:is_supported_by |
community contributions
grants and funding |
| gptkbp:is_tested_for |
human performance
|
| gptkbp:is_used_by |
research institutions
|
| gptkbp:is_utilized_in |
gptkb:Educational_Institution
AI ethics discussions policy making in education training AI models |
| gptkbp:performance |
human-level comprehension
|
| gptkbp:provides |
standardized evaluation metrics
|
| gptkbp:published_by |
gptkb:2017
|
| gptkbp:supports |
gptkb:language
|
| gptkbp:updates |
new data periodically
|
| gptkbp:used_in |
natural language processing research
|