Stanford Question Answering Dataset
GPTKB entity
Statements (53)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:Data
|
gptkbp:application |
gptkb:AI_technology
educational purposes benchmarking models |
gptkbp:available_at |
https://rajpurkar.github.io/ SQu AD-explorer/
|
gptkbp:collaborator |
gptkb:students
gptkb:Linguistics data scientists AI researchers |
gptkbp:contains |
questions
answers |
gptkbp:contribution |
facilitating research
advancing NLP improving QA systems providing benchmarks |
gptkbp:created_by |
gptkb:Stanford_University
|
gptkbp:data_type |
gptkb:JSON
test set training set validation set |
gptkbp:evaluates |
F1 score
Exact Match |
gptkbp:features |
crowdsourced
question-answer pairs human-annotated context passages |
gptkbp:field |
gptkb:Artificial_Intelligence
computational linguistics deep learning data mining information retrieval |
gptkbp:has_version |
gptkb:SQu_AD_2.0
SQu AD 1.1 |
https://www.w3.org/2000/01/rdf-schema#label |
Stanford Question Answering Dataset
|
gptkbp:impact |
widely used in industry
widely used in academia influenced subsequent datasets inspired new research directions |
gptkbp:influenced_by |
gptkb:SQu_AD
|
gptkbp:is_cited_in |
Rajpurkar et al. 2016
SQu AD paper |
gptkbp:language |
English
|
gptkbp:provides_information_on |
over 100,000 questions
over 500,000 answers |
gptkbp:related_to |
question answering systems
|
gptkbp:release_year |
gptkb:2016
|
gptkbp:type |
open-domain question answering
|
gptkbp:used_for |
gptkb:machine_learning
natural language processing |
gptkbp:visitors |
100,000
|
gptkbp:bfsParent |
gptkb:the_Stanford_AI_Laboratory
gptkb:The_Stanford_AI_Laboratory |
gptkbp:bfsLayer |
4
|