Triple
T21688841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marchesa |
E535303
|
entity |
| Predicate | frequentUseCase |
P144936
|
FINISHED |
| Object | red carpet events |
—
|
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: red carpet events | Statement: [Marchesa, frequentUseCase, red carpet events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentUseCase Context triple: [Marchesa, frequentUseCase, red carpet events]
-
A.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
B.
frequentOccasion
Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
-
C.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
D.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
E.
isFrequentlyPerformedBy
Indicates that an action or activity is carried out often or on a regular basis by a particular entity.
- F. None of above. chosen
Provenance (4 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cd51d481908df67e4f69826b06 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:44 p.m.