Triple
T307351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DeepMind |
E6331
|
entity |
| Predicate | hasKeyPerson |
P256
|
FINISHED |
| Object | Demis Hassabis |
E39539
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Demis Hassabis | Statement: [DeepMind, hasKeyPerson, Demis Hassabis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Demis Hassabis Context triple: [DeepMind, hasKeyPerson, Demis Hassabis]
-
A.
Demis Hassabis
chosen
Demis Hassabis is a British artificial intelligence researcher, neuroscientist, and entrepreneur best known as the co-founder and CEO of DeepMind, a leading AI company acquired by Google.
-
B.
Shane Legg
Shane Legg is a computer scientist and AI researcher best known as a co-founder of DeepMind and for his influential work on artificial general intelligence.
-
C.
Ilya Sutskever
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
-
D.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
-
E.
Geoffrey Hinton
Geoffrey Hinton is a pioneering computer scientist widely regarded as one of the founding figures of deep learning and modern artificial intelligence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea313be88190b4441f3ea41a99e2 |
completed | Feb. 28, 2026, 1:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c415f83c8190b95755f23faae026 |
completed | March 1, 2026, 4:44 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.