Triple
T2254665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedric Gibbons |
E49692
|
entity |
| Predicate | notableEmployerEra |
P561
|
FINISHED |
| Object | classic Hollywood era |
—
|
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: classic Hollywood era | Statement: [Cedric Gibbons, notableEmployerEra, classic Hollywood era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEmployerEra Context triple: [Cedric Gibbons, notableEmployerEra, classic Hollywood era]
-
A.
notableEra
chosen
Indicates the historical period or era for which an entity is especially recognized or significant.
-
B.
notableEraNickname
Indicates the informal or popular nickname by which a particular historical era or period is commonly known.
-
C.
notableEmployer
Indicates that an entity has been employed by, or has worked for, a particularly significant or noteworthy organization or individual.
-
D.
notableWorkPeriod
Indicates the time span during which an entity produced or was associated with its most significant or well-known works.
-
E.
notableYearOfActivity
Indicates the specific year during which an entity was particularly active, prominent, or notable in its activities or impact.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc121af78819085b2e601d2f9bcdf |
completed | March 7, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.