Triple
T8540928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jomo Kenyatta International Airport |
E202190
|
entity |
| Predicate | icaoLocationIndicator |
P419
|
FINISHED |
| Object | HKJK |
E202190
|
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: HKJK | Statement: [Jomo Kenyatta International Airport, icaoLocationIndicator, HKJK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HKJK Context triple: [Jomo Kenyatta International Airport, icaoLocationIndicator, HKJK]
-
A.
HKJK
chosen
HKJK is the ICAO airport code for Jomo Kenyatta International Airport, the main international gateway serving Nairobi, Kenya.
-
B.
HKY
HKY is the three-letter IATA airport code for Hickory Regional Airport in Hickory, North Carolina, USA.
-
C.
HKMO
HKMO is the ICAO airport code for Moi International Airport, a major international airport serving Mombasa, Kenya.
-
D.
KJK
KJK is the IATA airport code for Koksijde Air Base in Belgium.
-
E.
HK
HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e10bc081909a7210c577b807fb |
completed | March 31, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea86036a881909cd1744cdb5b7a7f |
completed | April 2, 2026, 5:33 p.m. |
Created at: March 30, 2026, 6:18 p.m.