AlphaFold
E39542
AlphaFold is an artificial intelligence system developed by DeepMind that predicts protein 3D structures from amino acid sequences with unprecedented accuracy, revolutionizing structural biology.
All labels observed (9)
How this entity was disambiguated
This entity first appeared as the object of triple T307333 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AlphaFold Context triple: [DeepMind, knownFor, AlphaFold]
-
A.
DeepMind
DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
-
B.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
-
C.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
D.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
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E.
Claude
Claude is a given name most famously associated with Claude Shannon, the American mathematician and electrical engineer known as the father of information theory.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AlphaFold Target entity description: AlphaFold is an artificial intelligence system developed by DeepMind that predicts protein 3D structures from amino acid sequences with unprecedented accuracy, revolutionizing structural biology.
-
A.
DeepMind
DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
-
B.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
-
C.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
D.
GPT-3
GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
-
E.
Claude
Claude is a given name most famously associated with Claude Shannon, the American mathematician and electrical engineer known as the father of information theory.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence system
ⓘ
protein structure prediction system ⓘ protein structure prediction system ⓘ |
| achievement |
top performance in CASP13 protein structure prediction competition
ⓘ
top performance in CASP14 protein structure prediction competition ⓘ |
| announced | 2020 ⓘ |
| announcedAt | CASP13 ⓘ |
| approach |
end-to-end differentiable learning
ⓘ
structure prediction from sequence alone ⓘ |
| basedOn |
attention mechanisms
ⓘ
evolutionary information ⓘ multiple sequence alignments ⓘ transformer architecture ⓘ |
| citation | Jumper et al., Nature 2021 ⓘ |
| dataSource | UniProt protein sequences ⓘ |
| developer |
DeepMind
ⓘ
DeepMind ⓘ Google DeepMind ⓘ
linked to:
DeepMind
|
| evaluationMetric | GDT_TS ⓘ |
| field |
bioinformatics
ⓘ
computational biology ⓘ structural biology ⓘ |
| hostedOn | EMBL-EBI AlphaFold Protein Structure Database ⓘ |
| impact |
accelerated determination of protein structures
ⓘ
reduced need for experimental structure determination ⓘ |
| input | amino acid sequence ⓘ |
| language | Python ⓘ |
| license | open-source license ⓘ |
| majorUpdate |
AlphaFold2
ⓘ
linked to:
AlphaFold
|
| notableFor |
high accuracy in protein structure prediction
ⓘ
near-experimental accuracy in protein structure prediction ⓘ revolutionizing structural biology ⓘ |
| organization | Alphabet Inc. ⓘ |
| output | protein 3D structure ⓘ |
| parentOrganization | DeepMind ⓘ |
| published | 2021 ⓘ |
| relatedTo |
CASP (Critical Assessment of protein Structure Prediction)
ⓘ
Protein Data Bank ⓘ |
| releaseDate | 2018 ⓘ |
| repository | GitHub ⓘ |
| sponsor | Alphabet Inc. ⓘ |
| supports | proteins from many organisms ⓘ |
| task | protein structure prediction ⓘ |
| usedBy |
academic researchers
ⓘ
pharmaceutical companies ⓘ |
| usedFor |
drug discovery
ⓘ
functional annotation of proteins ⓘ protein engineering ⓘ |
| uses |
deep learning
ⓘ
neural networks ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: AlphaFold Description of subject: AlphaFold is an artificial intelligence system developed by DeepMind that predicts protein 3D structures from amino acid sequences with unprecedented accuracy, revolutionizing structural biology.
Referenced by (31)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
subject linked to:
Stanislav Nikolov
2021 Nature paper on AlphaFold protein structure prediction system
→
mainSubject
→
AlphaFold protein structure prediction system
ⓘ
subject linked to:
Rishub Jain
linked to: AlphaFold
subject linked to:
Michal Zielinski
Mona Pacholska
→
coAuthorOf
→
2021 Nature paper "Highly accurate protein structure prediction with AlphaFold"
ⓘ
linked to: AlphaFold
linked to: AlphaFold
linked to: AlphaFold
2021 Nature paper on AlphaFold protein structure prediction
→
describes
→
AlphaFold protein structure prediction system
ⓘ
subject linked to:
David Reiman
linked to: AlphaFold
linked to: AlphaFold