Triple
T7948692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glamour |
E184558
|
entity |
| Predicate | hasEdition |
P35
|
FINISHED |
| Object | Glamour Brazil |
E39388
|
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: Glamour Brazil | Statement: [Glamour, hasEdition, Glamour Brazil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glamour Brazil Context triple: [Glamour, hasEdition, Glamour Brazil]
-
A.
Wonderbra
Wonderbra is a famous push-up bra brand known for its cleavage-enhancing lingerie and iconic advertising campaigns.
-
B.
Still Brazy
Still Brazy is a politically charged West Coast hip-hop album by rapper YG, noted for its G-funk-influenced production and commentary on life in Compton and contemporary social issues.
-
C.
Glamour
chosen
Glamour is a popular international women's magazine known for its coverage of fashion, beauty, lifestyle, and celebrity culture.
-
D.
Glitz
Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
-
E.
Brave Miss World
Brave Miss World is a documentary film that follows former Miss World Linor Abargil’s global campaign against sexual violence after surviving a brutal rape.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2bf6f48190ac7491c41045cab2 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe03c7d308190aec1172415be995c |
completed | March 31, 2026, 2:54 p.m. |
Created at: March 30, 2026, 5:10 p.m.