Triple
T32722416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Higashiyama Zoo and Botanical Gardens |
E836708
|
entity |
| Predicate | skyTowerHeight |
P93280
|
FINISHED |
| Object | about 134 meters |
—
|
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 134 meters | Statement: [Higashiyama Zoo and Botanical Gardens, skyTowerHeight, about 134 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skyTowerHeight Context triple: [Higashiyama Zoo and Botanical Gardens, skyTowerHeight, about 134 meters]
-
A.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
B.
approximateHeightOfTallestStructure
chosen
Indicates the estimated height value associated with the tallest structure in a given context or set.
-
C.
towerName
Indicates the specific name assigned to a tower in the relationship.
-
D.
rankInCityByHeight
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
E.
buildingHeight
Indicates the vertical extent or height measurement of a building.
- 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_69f34935455881909088975d79460418 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c8b484b48190b5c37ba1c3101056 |
completed | May 3, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:11 a.m.