Triple
T13475186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WMKK |
E318231
|
entity |
| Predicate | terminal |
P11513
|
FINISHED |
| Object | klia2 |
E409254
|
NE 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: klia2 | Statement: [WMKK, terminal, klia2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: klia2 Context triple: [WMKK, terminal, klia2]
-
A.
klia2
chosen
klia2 is the low-cost carrier terminal complex of Kuala Lumpur International Airport, serving as a major hub for budget airlines in Malaysia.
-
B.
KLIT
KLIT is the ICAO airport code for Bill and Hillary Clinton National Airport, the primary commercial airport serving Little Rock, Arkansas.
-
C.
KLAL
KLAL is the ICAO airport code for Lakeland Linder International Airport in Lakeland, Florida, a regional airport known for general aviation and cargo operations.
-
D.
KLu
KLu is the commonly used abbreviation for the Royal Netherlands Air Force, the aerial warfare branch of the Dutch armed forces.
-
E.
KL10
KL10 is a 36-bit mainframe CPU model developed by Digital Equipment Corporation for high-end DECsystem-10 and DECSYSTEM-20 systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2551b48190a074fd256791742d |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7462f94988190a857fa8cd32cdd0a |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:42 p.m.