Commonsense reasoning systems
GPTKB entity
Statements (43)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Artificial intelligence system
|
| gptkbp:application |
gptkb:robot
Natural language processing Question answering |
| gptkbp:challenge |
Knowledge representation
Scalability Ambiguity resolution |
| gptkbp:conference |
gptkb:AAAI_Commonsense_Reasoning_Symposium
|
| gptkbp:dataSource |
Crowdsourcing
Text mining Expert curation |
| gptkbp:developedBy |
1980s
|
| gptkbp:difficulty |
Contextual reasoning
Handling exceptions Implicit knowledge capture |
| gptkbp:field |
gptkb:artificial_intelligence
Cognitive science |
| gptkbp:goal |
Bridge gap between human and machine understanding
|
| https://www.w3.org/2000/01/rdf-schema#label |
Commonsense reasoning systems
|
| gptkbp:limitation |
Bias in data
Difficulty in formalizing commonsense Incomplete knowledge bases |
| gptkbp:notableContributor |
gptkb:Doug_Lenat
gptkb:Yejin_Choi gptkb:Push_Singh |
| gptkbp:notableExample |
gptkb:ConceptNet
gptkb:Cyc gptkb:ATOMIC gptkb:Open_Mind_Common_Sense |
| gptkbp:purpose |
Automate human-like reasoning
Enable machines to understand everyday situations |
| gptkbp:relatedTo |
gptkb:Winograd_Schema_Challenge
gptkb:CommonsenseQA gptkb:Story_Cloze_Test Commonsense knowledge bases Knowledge graphs Reasoning engines |
| gptkbp:uses |
Machine learning
Large language models Inference algorithms Symbolic reasoning |
| gptkbp:bfsParent |
gptkb:Henry_Lieberman
|
| gptkbp:bfsLayer |
6
|