Triple
T28501147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atago Green Hills |
E721232
|
entity |
| Predicate | hasGreenDesignElement |
P83569
|
FINISHED |
| Object | terraced greenery |
—
|
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: terraced greenery | Statement: [Atago Green Hills, hasGreenDesignElement, terraced greenery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenDesignElement Context triple: [Atago Green Hills, hasGreenDesignElement, terraced greenery]
-
A.
hasGreenType
Indicates that an entity possesses or is associated with a type classified as green.
-
B.
hasSustainabilityFeature
chosen
Indicates that an entity includes or is associated with a feature, attribute, or characteristic that contributes to environmental, social, or economic sustainability.
-
C.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
D.
hasGreenRoof
Indicates that a building or structure possesses a roof that is covered with vegetation or designed as a green roof.
-
E.
hasDesignRecognition
Indicates that an entity has received recognition, awards, or notable acknowledgment specifically for its design.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 3:06 a.m.