Triple
T3783100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robyn Rihanna Fenty |
E85464
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fenty |
E85465
|
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: Fenty | Statement: [Robyn Rihanna Fenty, familyName, Fenty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fenty Context triple: [Robyn Rihanna Fenty, familyName, Fenty]
-
A.
Fenty
chosen
Fenty is the surname of global music and fashion icon Rihanna, which she also uses as the brand name for her beauty and fashion ventures.
-
B.
Marchesa
Marchesa is the Italian noble title traditionally used to designate a woman holding the rank of marquess.
-
C.
Vivienne
Vivienne is the given first name of Patti Scialfa, the American singer-songwriter and member of Bruce Springsteen's E Street Band.
-
D.
Vivienne
Vivienne was a British writer and socialite best known as the first wife of poet T. S. Eliot and a central, troubled figure in his life and work.
-
E.
Chloé
Chloé is a French luxury fashion house renowned for its feminine ready-to-wear, leather goods, and accessories.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3db11108190aa81ee8ed22709fe |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f04747448190be484cda5b2a7a8c |
completed | March 14, 2026, 5:21 a.m. |
Created at: March 9, 2026, 3:13 p.m.