Triple
T4955552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerry Schatzberg |
E111271
|
entity |
| Predicate | workedFor |
P1910
|
FINISHED |
| Object | Glamour |
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 | Statement: [Jerry Schatzberg, workedFor, Glamour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glamour Context triple: [Jerry Schatzberg, workedFor, Glamour]
-
A.
Glamour
chosen
Glamour is a popular international women's magazine known for its coverage of fashion, beauty, lifestyle, and celebrity culture.
-
B.
Glamorous
"Glamorous" is a 2007 hip hop and R&B song by American singer Fergie featuring Ludacris, known for its catchy chorus and themes of maintaining humility despite wealth and fame.
-
C.
Glam
"Glam" is a track from Christina Aguilera's album *Bionic*, known for its fashion-themed lyrics and electro-pop production.
-
D.
Grits & Glamour
Grits & Glamour is a country music tour collaboration featuring veteran artists Pam Tillis and Lorrie Morgan, known for blending classic hits with storytelling and Southern charm.
-
E.
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.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71babb44819085b4cd4864433e79 |
completed | March 20, 2026, 4:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81de17748190a26abda7d3703b8e |
completed | March 21, 2026, 11:32 a.m. |
Created at: March 20, 2026, 1:32 p.m.