Triple
T19942908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PostSecret |
E479350
|
entity |
| Predicate | curatedBy |
P5107
|
FINISHED |
| Object | Frank Warren |
—
|
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: Frank Warren | Statement: [PostSecret, curatedBy, Frank Warren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Warren Context triple: [PostSecret, curatedBy, Frank Warren]
-
A.
Frank Warren
Frank Warren is a prominent British boxing promoter and manager known for guiding the careers of numerous world champions and staging major boxing events in the UK.
-
B.
Frank Warren
chosen
Frank Warren is an American author and entrepreneur best known for founding the community art project and blog PostSecret, which invites people to anonymously share their personal secrets on postcards.
-
C.
Bob Arum
Bob Arum is a prominent American boxing promoter and founder of Top Rank, known for promoting many of the sport’s biggest stars and events over several decades.
-
D.
Lou Duva
Lou Duva was a renowned American boxing trainer and manager known for guiding multiple world champions and being inducted into the International Boxing Hall of Fame.
-
E.
Don Peterman
Don Peterman was an American cinematographer known for his work on major Hollywood films across several decades, including comedies, dramas, and visual-effects-heavy productions.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a63f2e48190ba1cb7a4f415e7f6 |
completed | April 20, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:54 p.m.