Triple
T4501863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Fleming |
E101238
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Andy Jenkins |
E475744
|
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: Andy Jenkins | Statement: [Peggy Fleming, hasChild, Andy Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andy Jenkins Context triple: [Peggy Fleming, hasChild, Andy Jenkins]
-
A.
Jeff Jenkins
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
B.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
C.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
D.
Greg Jenkins
chosen
Greg Jenkins is an American dermatologist best known as the husband of Olympic figure skating champion Peggy Fleming.
-
E.
Dan Jinks
Dan Jinks is an American film and television producer best known for acclaimed movies such as "American Beauty" and "Big Fish."
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56f9dca08190b926f40e201a3e97 |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6f8abc3481909dbb42ddde2729ca |
completed | March 21, 2026, 10:14 a.m. |
Created at: March 20, 2026, 1 p.m.