Triple
T9187201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruländer |
E220488
|
entity |
| Predicate | modernUseInGermany |
P3657
|
FINISHED |
| Object | drier white wines (often labeled Grauburgunder) |
—
|
LITERAL 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: drier white wines (often labeled Grauburgunder) | Statement: [Ruländer, modernUseInGermany, drier white wines (often labeled Grauburgunder)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernUseInGermany Context triple: [Ruländer, modernUseInGermany, drier white wines (often labeled Grauburgunder)]
-
A.
modernUse
chosen
Indicates how something is currently used or applied in modern times.
-
B.
contemporaryUse
Indicates that something is currently used or practiced in the present time or modern context.
-
C.
usedInPresentDayCountry
Indicates that something is currently utilized or occurs within the boundaries of a specified modern-day country.
-
D.
modernExample
Indicates that something serves as a contemporary or current-day instance or illustration of something else.
-
E.
modernAccess
Indicates that an entity has contemporary, up-to-date means or methods of accessing or interacting with another entity or resource.
- F. None of above.
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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31bd6f88190b2ea644420995e41 |
completed | April 1, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69cc66090e5881908889dc1213815626 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:24 p.m.