Triple
T24535263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raffles City Chengdu |
E606931
|
entity |
| Predicate | hasGreenDesignElements |
P83569
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Raffles City Chengdu, hasGreenDesignElements, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenDesignElements Context triple: [Raffles City Chengdu, hasGreenDesignElements, yes]
-
A.
hasSustainabilityFeature
chosen
Indicates that an entity includes or is associated with a feature, attribute, or characteristic that contributes to environmental, social, or economic sustainability.
-
B.
hasDesignConsideration
Indicates that one entity takes another entity into account as a factor, constraint, or requirement in its design or planning.
-
C.
hasGreenType
Indicates that an entity possesses or is associated with a type classified as green.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:26 a.m.