Triple
T13258802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dandy Warhols |
E315733
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Brent DeBoer |
E1040122
|
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: Brent DeBoer | Statement: [The Dandy Warhols, member, Brent DeBoer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brent DeBoer Context triple: [The Dandy Warhols, member, Brent DeBoer]
-
A.
Brent DeBoer
chosen
Brent DeBoer is an American musician best known as the drummer and vocalist for the rock band The Dandy Warhols.
-
B.
Kalen Douglas DeBoer
Kalen Douglas DeBoer is an American college football coach known for leading successful high-powered offenses and rapidly elevating multiple programs to national prominence.
-
C.
Bryan Devendorf
Bryan Devendorf is an American drummer best known as a founding member and rhythmic backbone of the indie rock band The National.
-
D.
Craig Borten
Craig Borten is an American screenwriter best known for co-writing the acclaimed biographical drama film "Dallas Buyers Club."
-
E.
Ken Schretzmann
Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f778088819082b8a596c04bfe02 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74610b2c481909497296e999226e8 |
completed | May 3, 2026, 12:56 p.m. |
Created at: April 9, 2026, 9:25 p.m.