Triple
T2583816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentino |
E57151
|
entity |
| Predicate | designsFor |
P40514
|
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: [Valentino, designsFor, red-carpet events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designsFor Context triple: [Valentino, designsFor, red-carpet events]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
-
C.
designedWith
Indicates that one entity was created, planned, or developed using another entity as a tool, method, or guiding basis in its design process.
-
D.
helpsDesign
Indicates that one entity assists or contributes to another entity’s design or design process.
-
E.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3cb33a08190a3eae1a95e1b63bf |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd37ef248819090ab6b86b67e355f |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.