Triple
T8672177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salutations |
E205822
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jim Keltner |
E213411
|
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: Jim Keltner | Statement: [Salutations, producer, Jim Keltner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Keltner Context triple: [Salutations, producer, Jim Keltner]
-
A.
Jim Keltner
chosen
Jim Keltner is an American session drummer renowned for his work with artists such as John Lennon, George Harrison, Bob Dylan, and many others across rock and pop music.
-
B.
Ken Koblun
Ken Koblun is a Canadian bassist best known for his early involvement with the influential 1960s rock band Buffalo Springfield.
-
C.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
D.
Larry Kellner
Larry Kellner is an American business executive best known for leading Continental Airlines as its chief executive officer.
-
E.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
- 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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc491a34d08190b0795079d192a03d |
completed | March 31, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf286a364c8190b7f4f9d8243e2548 |
completed | April 3, 2026, 2:39 a.m. |
Created at: March 30, 2026, 6:31 p.m.