Triple
T334229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivanka Trump |
E6687
|
entity |
| Predicate | modeledFor |
P2006
|
FINISHED |
| Object | Versace |
E40976
|
NE 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: Versace | Statement: [Ivanka Trump, modeledFor, Versace]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Versace Context triple: [Ivanka Trump, modeledFor, Versace]
-
A.
Versace
chosen
Versace is a renowned Italian luxury fashion house known for its bold, glamorous designs and iconic Medusa logo.
-
B.
Prada
Prada is a renowned Italian luxury fashion house known for its high-end clothing, leather goods, and accessories.
-
C.
Balmain
Balmain is a French luxury fashion house renowned for its opulent, sharply tailored designs and influential presence on international runways.
-
D.
Tommy Hilfiger
Tommy Hilfiger is an American fashion brand and designer known for his classic, preppy clothing and accessories that blend traditional Americana with modern style.
-
E.
Calvin Klein
Calvin Klein is an American fashion brand renowned for its minimalist aesthetic, iconic underwear and denim lines, and influential advertising campaigns.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac641708190b85fa21368e5de8e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3d247650481909006cc27bfa385e3 |
completed | March 1, 2026, 5:44 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.