Triple
T14918329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kröller-Müller Museum |
E371440
|
entity |
| Predicate | hasSculptureGardenArea |
P116671
|
FINISHED |
| Object | one of the largest sculpture gardens in Europe |
—
|
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: one of the largest sculpture gardens in Europe | Statement: [Kröller-Müller Museum, hasSculptureGardenArea, one of the largest sculpture gardens in Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSculptureGardenArea Context triple: [Kröller-Müller Museum, hasSculptureGardenArea, one of the largest sculpture gardens in Europe]
-
A.
hasBotanicalGardenArea_ha
Indicates that an entity possesses a botanical garden whose area is measured in hectares.
-
B.
hasSculptureType
Indicates that an entity is associated with a sculpture and specifies the type or category of that sculpture.
-
C.
hasCourtyardArea
Indicates that an entity includes or is associated with a courtyard and specifies the size or extent of that courtyard space.
-
D.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
E.
sculptureParkName
Indicates that a sculpture park has the specified name.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62f76bc81909ebc8899096cd1a0 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:33 a.m.