Triple
T5713660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dust |
E125969
|
entity |
| Predicate | hasFormerMember |
P1168
|
FINISHED |
| Object | Kenny Aaronson |
E540184
|
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: Kenny Aaronson | Statement: [Dust, hasFormerMember, Kenny Aaronson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenny Aaronson Context triple: [Dust, hasFormerMember, Kenny Aaronson]
-
A.
Kenny Aaronson
chosen
Kenny Aaronson is an American rock bassist and session musician known for his work with numerous bands and artists since the 1970s.
-
B.
Joel McNeely
Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
-
C.
Mike Kellin
Mike Kellin was an American character actor known for his prolific work in film, television, and theater from the 1950s through the 1970s.
-
D.
Leon Shamroy
Leon Shamroy was an acclaimed American cinematographer, renowned for his work on numerous Hollywood classics and for winning multiple Academy Awards during the mid-20th century.
-
E.
John Hoffman
John Hoffman is an American writer, producer, and director best known for co-creating the mystery-comedy television series "Only Murders in the Building."
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024b5205c8190aaab291a6e485ec1 |
completed | March 22, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07dedffd481909fafd916190b016f |
completed | March 22, 2026, 11:40 p.m. |
Created at: March 22, 2026, 3:46 p.m.