Triple
T12533289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne McGregor |
E299622
|
entity |
| Predicate | usesInPractice |
P46656
|
FINISHED |
| Object | scientific research |
—
|
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: scientific research | Statement: [Wayne McGregor, usesInPractice, scientific research]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesInPractice Context triple: [Wayne McGregor, usesInPractice, scientific research]
-
A.
usedInPractice
chosen
Indicates that something is actually applied or implemented in real-world practice rather than just being theoretical or proposed.
-
B.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
C.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
-
D.
areInterpretedInPracticeBy
Indicates that something (such as a rule, concept, or specification) is given concrete meaning or applied in real-world situations by a particular agent or group.
-
E.
isUsedUnder
Indicates that one entity is utilized or applied within the context, conditions, or framework defined by another entity.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.