Triple
T10006302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Was |
E198250
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | John Mayer |
E26841
|
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: John Mayer | Statement: [Don Was, workedWith, John Mayer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Mayer Context triple: [Don Was, workedWith, John Mayer]
-
A.
John Mayer
chosen
John Mayer is an American singer-songwriter and virtuoso guitarist known for blending blues, rock, and pop in both chart-topping hits and acclaimed live performances.
-
B.
John D. Mayer
John D. Mayer is an American psychologist best known for co-developing the theory of emotional intelligence and contributing extensively to personality and emotion research.
-
C.
Jason Mraz
Jason Mraz is an American singer-songwriter known for his laid-back acoustic pop style and hit songs like "I'm Yours" and "I Won't Give Up."
-
D.
Ray LaMontagne
Ray LaMontagne is an American singer-songwriter known for his raspy, soulful voice and folk-influenced acoustic music.
-
E.
John Tedder
John Tedder is known primarily as the son of Arthur Tedder, the prominent British air marshal and senior Royal Air Force commander during World War II.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd16afb481909a5d5893e024683f |
completed | April 2, 2026, 1:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a5d7e088190b5b1a852bfdc9073 |
completed | April 5, 2026, 1:57 p.m. |
Created at: March 30, 2026, 8:51 p.m.