Triple
T13334410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecca Pearson |
E317651
|
entity |
| Predicate | presentedAtDifferentAges |
P15918
|
FINISHED |
| Object | young adult |
—
|
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: young adult | Statement: [Rebecca Pearson, presentedAtDifferentAges, young adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presentedAtDifferentAges Context triple: [Rebecca Pearson, presentedAtDifferentAges, young adult]
-
A.
designedAtAge
Indicates that something was designed when the designer was a specified age.
-
B.
typicalAge
Indicates the usual or characteristic age associated with an entity, event, or condition.
-
C.
playedEarlyYearsOf
chosen
Indicates that one entity portrayed or acted as the younger/early-life version of another entity in a performance or production.
-
D.
approximateStartAge
Indicates the estimated or roughly determined age at which an event, condition, or state begins.
-
E.
typicallyIssuedAtAge
Indicates the age at which something is most commonly or customarily issued to an individual.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cff44e08190b9583baf0b626e42 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:30 p.m.