Triple
T22015388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frogner Park |
E543693
|
entity |
| Predicate | materialUsedInSculptures |
P136410
|
FINISHED |
| Object | bronze |
—
|
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: bronze | Statement: [Frogner Park, materialUsedInSculptures, bronze]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialUsedInSculptures Context triple: [Frogner Park, materialUsedInSculptures, bronze]
-
A.
hasSculptureMaterial
chosen
Indicates that a sculpture is made from, or incorporates, a specified material.
-
B.
usesSculptureFor
Indicates that one entity employs or utilizes a sculpture for a particular purpose, function, or activity.
-
C.
statueMaterialDetail
Indicates that a statue is made of, or incorporates, a specific material with detailed characterization (e.g., type, composition, or quality).
-
D.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
E.
templeMaterial
Indicates that a temple is constructed from, or primarily composed of, a specified material.
- 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a774548190bcd98dc28f2d2c5f |
completed | April 28, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:22 p.m.