Triple
T36174348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KLIA2 |
E1046538
|
entity |
| Predicate | builtToHandle |
P20750
|
FINISHED |
| Object | high passenger capacity |
—
|
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: high passenger capacity | Statement: [KLIA2, builtToHandle, high passenger capacity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: builtToHandle Context triple: [KLIA2, builtToHandle, high passenger capacity]
-
A.
builtThrough
Indicates that something was created, developed, or achieved by means of a specified method, process, or intermediary.
-
B.
builtToMark
Indicates that something was constructed for the purpose of commemorating, signaling, or designating a particular event, place, boundary, or significance.
-
C.
designedToWithstand
chosen
Indicates that something has been intentionally created or engineered to resist, endure, or remain functional under specified conditions, forces, or stresses.
-
D.
wasBuilt
Indicates that one entity constructed, created, or assembled another entity, typically at a specific time or over a period.
-
E.
heldBenchIn
Indicates that an individual previously held a judicial position on a specified court or bench.
- 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_69f76e3c1b10819081fc7a807a71cf84 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.