Triple
T1375659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogor |
E29215
|
entity |
| Predicate | hasBotanicalGardenArea_ha |
P27103
|
FINISHED |
| Object | approximately 87 |
—
|
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: approximately 87 | Statement: [Bogor, hasBotanicalGardenArea_ha, approximately 87]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBotanicalGardenArea_ha Context triple: [Bogor, hasBotanicalGardenArea_ha, approximately 87]
-
A.
hasBotanicalGarden
Indicates that one entity possesses, contains, or includes a botanical garden as part of its facilities or domain.
-
B.
containsGarden
Indicates that one entity includes or has a garden within its area or boundaries.
-
C.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
D.
hasBotanicalResource
Indicates that an entity possesses, contains, or is associated with a plant-based resource (such as plants, plant parts, or botanical materials) used for some purpose.
-
E.
hasGardenType
Indicates that an entity possesses or is associated with a garden of a specified type.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2f9b51c8190ad52fd8c151499be |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.