Triple
T17944869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunter Schafer |
E448676
|
entity |
| Predicate | hasModeledFor |
P17880
|
FINISHED |
| Object | Mugler |
—
|
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: Mugler | Statement: [Hunter Schafer, hasModeledFor, Mugler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mugler Context triple: [Hunter Schafer, hasModeledFor, Mugler]
-
A.
Galliano
Galliano is a high-fashion brand led by British designer John Galliano, known for its theatrical, avant-garde couture and dramatic runway presentations.
-
B.
the fashion brand Mugler
Mugler is a French luxury fashion house renowned for its avant-garde, sculptural designs and bold, theatrical aesthetic.
-
C.
Profumo
Profumo is an Italian surname most famously associated with John Profumo, the British politician at the center of the 1963 Profumo affair scandal.
-
D.
Profumo
"Profumo" is a popular 1986 rock song by Italian singer-songwriter Gianna Nannini, known for its passionate vocals and melodic, guitar-driven sound.
-
E.
Thierry Mugler
chosen
Thierry Mugler was a French fashion designer and creative visionary known for his dramatic, sculptural couture and influential work in haute couture and fragrance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad9819a88190ad4ea7d562cf3f28 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 10:21 a.m.