Triple
T19312705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goethe–Schiller Monument |
E483010
|
entity |
| Predicate | imageMotifOn |
P41002
|
FINISHED |
| Object | postcards of Weimar |
—
|
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: postcards of Weimar | Statement: [Goethe–Schiller Monument, imageMotifOn, postcards of Weimar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageMotifOn Context triple: [Goethe–Schiller Monument, imageMotifOn, postcards of Weimar]
-
A.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
B.
transformationMotif
Indicates a recurring pattern or theme in which one entity undergoes a change in form, state, or identity in relation to another.
-
C.
imageOf
Indicates that one entity is a visual representation or depiction of another entity.
-
D.
evokesImageOf
Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
-
E.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cf25c081908a30814b15d78c25 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.