Triple
T6274175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenkins |
E140612
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Michael Jenkins |
E210606
|
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: Michael Jenkins | Statement: [Jenkins, hasNotableBearer, Michael Jenkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Jenkins Context triple: [Jenkins, hasNotableBearer, Michael Jenkins]
-
A.
Michael Jenkins
Michael Jenkins is a theatre producer best known for his work on the hit musical comedy "Spamalot."
-
B.
Michael Jenkins
chosen
Michael Jenkins is an Australian screenwriter and director known for his work in film and television, including influential Australian dramas.
-
C.
Jeff Jenkins
Jeff Jenkins is a television producer best known for his work on reality TV series, particularly within the Kardashian franchise.
-
D.
Andrew Jenkins
Andrew Jenkins is a British businessman best known for his long-serving leadership role as chairman of Carlisle United Football Club.
-
E.
Allen Jenkins
Allen Jenkins was an American character actor known for his comic supporting roles in numerous Hollywood films of the 1930s and 1940s.
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063c0629c8190805ddf1a604e9ca4 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c669d6ff748190b77d5a2c9cbe506b |
completed | March 27, 2026, 11:28 a.m. |
Created at: March 22, 2026, 4:25 p.m.