Triple
T16004291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn Decker |
E388172
|
entity |
| Predicate | startedModeling |
P83822
|
FINISHED |
| Object | teenage years |
—
|
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: teenage years | Statement: [Brooklyn Decker, startedModeling, teenage years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startedModeling Context triple: [Brooklyn Decker, startedModeling, teenage years]
-
A.
startedModelingAtAge
Indicates the age at which an entity first began engaging in modeling as an activity or profession.
-
B.
beganModelingCareer
chosen
Indicates that an entity started or initiated their professional modeling career at a particular time or under certain circumstances.
-
C.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
D.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
E.
startedPainting
Indicates that an entity began the activity or process of painting, marking the initiation of that action.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.