Triple
T17489512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Schlitz |
E425865
|
entity |
| Predicate | surname |
P18
|
FINISHED |
| Object | Schlitz |
—
|
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: Schlitz | Statement: [Don Schlitz, surname, Schlitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schlitz Context triple: [Don Schlitz, surname, Schlitz]
-
A.
Schlitz
chosen
Schlitz is the surname of Don Schlitz, the American country music songwriter best known for penning hits like “The Gambler.”
-
B.
Schlitz
Schlitz is a river in the German state of Hesse that flows through the town of Schlitz before joining the Werra.
-
C.
Gambrinus Brewery
Gambrinus Brewery is a major Czech brewery based in Plzeň, renowned for its traditional pale lagers and significant role in the country’s beer culture.
-
D.
Budweis
Budweis is the German name for České Budějovice, a historic city in the Czech Republic renowned for its brewing tradition and medieval architecture.
-
E.
Pabst Brewing Company
Pabst Brewing Company is a historic American brewery best known for producing Pabst Blue Ribbon and other classic beer brands.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451d461308190844c143dcfb61fac |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:48 a.m.