Triple
T13968237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aiken Regional Airport |
E335982
|
entity |
| Predicate | hasICAOCode |
P419
|
FINISHED |
| Object |
KAIK
KAIK is the ICAO airport code for Aiken Regional Airport, a public airport serving Aiken, South Carolina, USA.
|
E1072190
|
NE FINISHED |
How this triple was built (4 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: KAIK | Statement: [Aiken Regional Airport, hasICAOCode, KAIK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KAIK Context triple: [Aiken Regional Airport, hasICAOCode, KAIK]
-
A.
KAIA
KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
-
B.
kai yang
Kai yang is a popular Thai-style grilled chicken dish, especially associated with the Isan region of northeastern Thailand.
-
C.
Kai (quay)
Kai (quay) is a type of waterside street or embankment road that runs along a river or harbor, typically used for access to docks and waterfront areas.
-
D.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
-
E.
KARI
KARI is South Korea's national aerospace research organization responsible for developing space and aeronautical technologies, including satellites and launch vehicles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KAIK Triple: [Aiken Regional Airport, hasICAOCode, KAIK]
Generated description
KAIK is the ICAO airport code for Aiken Regional Airport, a public airport serving Aiken, South Carolina, USA.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KAIK Target entity description: KAIK is the ICAO airport code for Aiken Regional Airport, a public airport serving Aiken, South Carolina, USA.
-
A.
KAIA
KAIA is a major international airport in Jeddah, Saudi Arabia, serving as a key gateway for pilgrims traveling to the holy cities of Mecca and Medina.
-
B.
kai yang
Kai yang is a popular Thai-style grilled chicken dish, especially associated with the Isan region of northeastern Thailand.
-
C.
Kai (quay)
Kai (quay) is a type of waterside street or embankment road that runs along a river or harbor, typically used for access to docks and waterfront areas.
-
D.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
-
E.
KARI
KARI is South Korea's national aerospace research organization responsible for developing space and aeronautical technologies, including satellites and launch vehicles.
- F. None of above. chosen
Provenance (5 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8daeac8190aadd4b3b60222482 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1da70588190a6c9a3895d92be5b |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba74a96b08190a08c51c231e49e5d |
completed | May 6, 2026, 8:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba8585fb08190998d6a005dc0bd31 |
completed | May 6, 2026, 8:45 p.m. |
Created at: April 9, 2026, 10:18 p.m.