Triple
T25731680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spreuer Bridge |
E645257
|
entity |
| Predicate | hasNumberOfPaintedPanels |
P171387
|
FINISHED |
| Object | about 45 |
—
|
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: about 45 | Statement: [Spreuer Bridge, hasNumberOfPaintedPanels, about 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPaintedPanels Context triple: [Spreuer Bridge, hasNumberOfPaintedPanels, about 45]
-
A.
hasNumberOfInscribedPanels
Indicates the relationship that specifies how many inscribed panels are associated with a given entity.
-
B.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
C.
hasNumberOfEnamelPanels
Indicates the relationship that specifies how many enamel panels are present on or associated with a given object or entity.
-
D.
numberOfConcretePanels
Indicates the total count of concrete panels associated with or used in relation to a given entity.
-
E.
numberOfStainedGlassPanels
Indicates the count of stained glass panels associated with a given entity or object.
- F. None of above. chosen
Provenance (4 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 21, 2026, 11:16 p.m.