Triple
T19803425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Fleming |
E475744
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Greg Jenkins |
—
|
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: Greg Jenkins | Statement: [Peggy Fleming, spouse, Greg Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Jenkins Context triple: [Peggy Fleming, spouse, Greg Jenkins]
-
A.
Greg Jenkins
chosen
Greg Jenkins is an American dermatologist best known as the husband of Olympic figure skating champion Peggy Fleming.
-
B.
Eric Jenkins
Eric Jenkins is a film editor known for his work on the influential 1982 teen comedy-drama "Fast Times at Ridgemont High."
-
C.
Chris Jenkins
Chris Jenkins is a film producer known for his work on the 2009 horror movie "Home."
-
D.
Ken Jenkins
Ken Jenkins is an American actor best known for his role as the irascible hospital administrator Dr. Bob Kelso on the television series "Scrubs."
-
E.
Brian Jenkins
Brian Jenkins is a name shared by several notable individuals, including American football coaches and a prominent terrorism and security expert.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654266e18819085698aed8b0e2ba8 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.