Triple
T22995121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Budenholzer |
E572167
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Budenholzer |
—
|
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: Budenholzer | Statement: [Mike Budenholzer, familyName, Budenholzer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Budenholzer Context triple: [Mike Budenholzer, familyName, Budenholzer]
-
A.
Budenholzer
chosen
Budenholzer is the surname of Mike Budenholzer, an American professional basketball coach best known for leading the Milwaukee Bucks to the 2021 NBA championship.
-
B.
Benedenberg
Benedenberg is a small village in the Dutch province of South Holland, located within the municipality of Krimpenerwaard.
-
C.
Oberholzer
Oberholzer is a surname of Germanic origin, commonly found in German-speaking regions and among their diasporas.
-
D.
Boerne
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
E.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
- 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f25af48190a98b7baeec824ae6 |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.