Triple
T10423407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kona International Airport |
E245722
|
entity |
| Predicate | hasIATACode |
P2569
|
FINISHED |
| Object | KOA |
E245721
|
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: KOA | Statement: [Kona International Airport, hasIATACode, KOA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KOA Context triple: [Kona International Airport, hasIATACode, KOA]
-
A.
KOA
chosen
KOA is the three-letter IATA airport code for Kona International Airport on the island of Hawaiʻi.
-
B.
Koozå
Koozå is a Cirque du Soleil touring production that blends acrobatics and clowning in a whimsical, circus-themed narrative.
-
C.
KOKB
KOKB is the ICAO airport code for Oceanside Municipal Airport, a public general aviation facility serving Oceanside, California.
-
D.
KOXB
KOXB is the ICAO airport code for Ocean City Municipal Airport in Maryland, a public airport serving the Ocean City resort area.
-
E.
Koja
Koja is a coastal district in North Jakarta, Indonesia, known for its dense urban neighborhoods and proximity to the city’s port and industrial areas.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2de4d48190aee65b3f6ec3cc48 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ea554888190bf2ef31e33c0ff14 |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:12 p.m.