Triple
T7751316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAN |
E175768
|
entity |
| Predicate | hasICAOCode |
P419
|
FINISHED |
| Object | KSAN |
E32610
|
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: KSAN | Statement: [SAN, hasICAOCode, KSAN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KSAN Context triple: [SAN, hasICAOCode, KSAN]
-
A.
KSAN
chosen
KSAN is the ICAO airport code for San Diego International Airport, a major commercial airport serving the San Diego, California area.
-
B.
KSAT
KSAT is the ICAO airport code for San Antonio International Airport, a major commercial airport serving the San Antonio, Texas area.
-
C.
KSAV
KSAV is the ICAO airport code for Savannah/Hilton Head International Airport, a commercial and military airfield serving the Savannah, Georgia and Hilton Head Island, South Carolina region.
-
D.
KMSKA
KMSKA is the Royal Museum of Fine Arts in Antwerp, renowned for its extensive collection of Flemish and Belgian art spanning several centuries.
-
E.
KAN
KAN is the IATA airport code for Mallam Aminu Kano International Airport, a major airport serving Kano in northern Nigeria.
- 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703b264c0819095c37534a676531d |
completed | March 27, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be576274819092e5ebdbcf2361da |
completed | March 29, 2026, 5:53 a.m. |
Created at: March 27, 2026, 4:08 p.m.