Triple
T32017248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Rock |
E817576
|
entity |
| Predicate | appliesNeuroscienceTo |
P83724
|
FINISHED |
| Object | leadership |
—
|
LITERAL 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: leadership | Statement: [David Rock, appliesNeuroscienceTo, leadership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesNeuroscienceTo Context triple: [David Rock, appliesNeuroscienceTo, leadership]
-
A.
neuralBasis
Indicates that one entity serves as the neural or brain-based mechanism underlying, enabling, or explaining the function, behavior, or property of another entity.
-
B.
appliesResearchTo
chosen
Indicates that an entity uses or implements research findings, methods, or insights in relation to another entity, context, or problem.
-
C.
isNeuroprotective
Indicates that one entity confers protection to another entity’s nervous system or neural structures, helping to prevent or reduce neural damage or degeneration.
-
D.
brain
Indicates that an entity functions as the brain (central cognitive or control organ) of another entity.
-
E.
usesNeuralNetworks
Indicates that one entity employs neural network models or techniques as part of its functioning, processing, or decision-making.
- F. None of above.
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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: May 1, 2026, 12:16 a.m.