Triple
T3393806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albany International Airport |
E71479
|
entity |
| Predicate | hasAirportCodePrefix |
P49384
|
FINISHED |
| Object | K |
—
|
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: K | Statement: [Albany International Airport, hasAirportCodePrefix, K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirportCodePrefix Context triple: [Albany International Airport, hasAirportCodePrefix, K]
-
A.
hasAirportCodeType
Indicates that an airport code is associated with a specific classification or type (e.g., IATA, ICAO, FAA).
-
B.
hasAirportCodeCity
Indicates that a city is associated with a specific airport code (such as an IATA or ICAO code) that identifies its airport.
-
C.
hasAirportCodeRegion
Indicates that an airport code is associated with, or belongs to, a specific geographic or administrative region.
-
D.
hasPostalCodePrefix
Indicates that a location’s postal code begins with a specified sequence of characters.
-
E.
hasIATAcode
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
- F. None of above. chosen
Provenance (4 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb853746c8190bfa1447e6ebbefb3 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb2e426b88190b82d9830149b142e |
completed | March 8, 2026, 5:33 p.m. |
Created at: March 8, 2026, 3:14 p.m.