Triple
T31405187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebony Fashion Fair |
E801109
|
entity |
| Predicate | featuredDesigner |
P202377
|
FINISHED |
| Object | Christian Dior |
—
|
NE NERFINISHED |
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: Christian Dior | Statement: [Ebony Fashion Fair, featuredDesigner, Christian Dior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredDesigner Context triple: [Ebony Fashion Fair, featuredDesigner, Christian Dior]
-
A.
designerAlias
Indicates that one name or label is used as an alternative alias for a designer.
-
B.
designerType
Indicates the specific kind or category of designer role associated with an entity.
-
C.
designedBy
Indicates that one entity is the creator, planner, or architect responsible for the form or structure of another entity.
-
D.
designerOccupation
Indicates that one entity serves as the professional designer or design specialist for another entity.
-
E.
designerNationality
Indicates that a designer has a specific national or country affiliation.
- 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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_6a00781b749c8190921c46e110cae0b0 |
completed | May 10, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_6a0077df3c8481909fabc9e84f5936e3 |
completed | May 10, 2026, 12:19 p.m. |
| PDg | Predicate description generation | batch_6a00781ac0f48190a77e2c326a4d6693 |
completed | May 10, 2026, 12:20 p.m. |
Created at: April 29, 2026, 9:20 p.m.