Triple
T17513096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Germs |
E426499
|
entity |
| Predicate | drummer |
P15280
|
FINISHED |
| Object | Don Bolles |
—
|
NE NERFINISHED |
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: Don Bolles | Statement: [The Germs, drummer, Don Bolles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Bolles Context triple: [The Germs, drummer, Don Bolles]
-
A.
Don Bolles
chosen
Don Bolles is an American punk rock drummer best known for his work with the influential Los Angeles band the Germs.
-
B.
Dave Boller
Dave Boller is an American football executive best known for serving as the general manager of the San Diego Fleet in the Alliance of American Football.
-
C.
Phil Brent
Phil Brent is a fictional character from the soap opera "All My Children," known for his complex family relationships and dramatic storylines.
-
D.
David Loughery
David Loughery is an American screenwriter and producer known for writing thrillers and genre films such as "Passenger 57," "Lakeview Terrace," and "Obsessed."
-
E.
Tim Baltz
Tim Baltz is an American comedian and actor known for his work on television comedies such as The Righteous Gemstones and Shrink.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525d29fc819080851bf744bc78ed |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:49 a.m.