Triple
T593586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petronas Towers |
E17328
|
entity |
| Predicate | citySkylineRole |
P8652
|
FINISHED |
| Object | dominant feature of Kuala Lumpur skyline |
—
|
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: dominant feature of Kuala Lumpur skyline | Statement: [Petronas Towers, citySkylineRole, dominant feature of Kuala Lumpur skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citySkylineRole Context triple: [Petronas Towers, citySkylineRole, dominant feature of Kuala Lumpur skyline]
-
A.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
B.
urbanRole
chosen
Indicates the function, status, or role that an entity holds within an urban or city context.
-
C.
roleInUrbanPlan
Indicates the specific function, responsibility, or position an entity holds within an urban planning context or scheme.
-
D.
hasUrbanRole
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
E.
architecturalRole
Indicates the functional or design-related role that one entity plays within the structure, layout, or organization of another entity.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd15c5881909b59ed4c88687e7b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.