Triple
T16811183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Am Cait |
E408613
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jeff Jenkins |
E422730
|
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: Jeff Jenkins | Statement: [I Am Cait, executiveProducer, Jeff Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Jenkins Context triple: [I Am Cait, executiveProducer, Jeff Jenkins]
-
A.
Jeff Jenkins
chosen
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
B.
Chris Jenkins
Chris Jenkins is a film producer known for his work on the 2009 horror movie "Home."
-
C.
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."
-
D.
Brian Jenkins
Brian Jenkins is a name shared by several notable individuals, including American football coaches and a prominent terrorism and security expert.
-
E.
Michael Jenkins
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2d0793c81909d938ac174a6e63a |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01673ba0e08190a988847fa7ad8e50 |
completed | May 11, 2026, 5:20 a.m. |
Created at: April 10, 2026, 5:23 a.m.