Triple
T1671549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Tower |
E36135
|
entity |
| Predicate | façadeType |
P31596
|
FINISHED |
| Object | double-skin façade |
—
|
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: double-skin façade | Statement: [Shanghai Tower, façadeType, double-skin façade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: façadeType Context triple: [Shanghai Tower, façadeType, double-skin façade]
-
A.
façadeDescription
Indicates a textual description that characterizes the appearance, style, or features of a building’s façade.
-
B.
façadeOrientation
Indicates the directional orientation that a building’s façade faces relative to a reference (e.g., cardinal directions or a main street).
-
C.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
D.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
E.
facesBuilding
Indicates that one building is oriented toward and directly faces another building.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab271be3f4819091adcd745dec8159 |
completed | March 6, 2026, 7:12 p.m. |
Created at: March 4, 2026, 7:29 p.m.