Triple
T15943213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KABQ |
E386616
|
entity |
| Predicate | ICAORegionPrefix |
P34409
|
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: [KABQ, ICAORegionPrefix, K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ICAORegionPrefix Context triple: [KABQ, ICAORegionPrefix, K]
-
A.
ICAOcode
Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
-
B.
ICAOTypeDesignator
Indicates the standardized aircraft type code assigned by ICAO that specifies the model or family of an aircraft used in aviation operations and documentation.
-
C.
associatedAirportICAOSubregion
Indicates a relationship where an airport is linked to the specific ICAO-defined subregion in which it is located or with which it is operationally associated.
-
D.
icaoRegionPrefix
chosen
Indicates the regional ICAO prefix that designates the geographic or administrative region associated with an aviation-related entity.
-
E.
icaoCodeType
Indicates that the relationship specifies or classifies the ICAO (International Civil Aviation Organization) code associated with an entity.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.