Triple
T9187202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruländer |
E220488
|
entity |
| Predicate | synonymUsage |
P46176
|
FINISHED |
| Object | traditional term for richer, sweeter styles in Germany |
—
|
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: traditional term for richer, sweeter styles in Germany | Statement: [Ruländer, synonymUsage, traditional term for richer, sweeter styles in Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: synonymUsage Context triple: [Ruländer, synonymUsage, traditional term for richer, sweeter styles in Germany]
-
A.
synonym
Indicates that two terms have the same or nearly the same meaning in a given context.
-
B.
termAlsoUsedFor
chosen
Indicates that one term is also used to refer to the same or closely related concept as another term.
-
C.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
D.
usedTerm
Indicates that one entity employed, referenced, or applied a particular term in some context.
-
E.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
- 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.