Triple
T6893875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KE |
E159119
|
entity |
| Predicate | airlineICAOCode |
P26821
|
FINISHED |
| Object | KAL |
E159120
|
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: KAL | Statement: [KE, airlineICAOCode, KAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KAL Context triple: [KE, airlineICAOCode, KAL]
-
A.
KAL
chosen
KAL is the ICAO airline designator used to identify Korean Air in international aviation operations.
-
B.
KALO
KALO is the ICAO airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
-
C.
KALS
KALS is the ICAO airport code for San Luis Valley Regional Airport serving Alamosa, Colorado.
-
D.
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.
-
E.
KUL
KUL is the IATA airport code for Kuala Lumpur International Airport, the main international gateway serving Malaysia’s capital region.
- 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_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d931da24819096b9b205f2c0ebb0 |
completed | March 27, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748db2bd48190bb26f60c58ec8229 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:24 p.m.