Triple
T2088427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAN |
E32609
|
entity |
| Predicate | associatedWithFAAIdentifier |
P420
|
FINISHED |
| Object | SAN |
—
|
LITERAL 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: SAN | Statement: [SAN, associatedWithFAAIdentifier, SAN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithFAAIdentifier Context triple: [SAN, associatedWithFAAIdentifier, SAN]
-
A.
aircraftRegistration
Indicates that an aircraft is assigned a specific official registration identifier or code.
-
B.
FAAcode
chosen
Indicates that an entity (such as an airport or facility) is associated with a specific identifying code assigned by the Federal Aviation Administration (FAA).
-
C.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
D.
relatedAircraft
Indicates that there is an association or connection between two aircraft, such as operational, functional, or contextual relatedness.
-
E.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
- F. None of above.
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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba712388819091d68a4bb99f6b17 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.