Triple
T37274795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VEMR |
E924615
|
entity |
| Predicate | belongsToICAORegionPrefix |
P121695
|
FINISHED |
| Object | VE |
—
|
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: VE | Statement: [VEMR, belongsToICAORegionPrefix, VE]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToICAORegionPrefix Context triple: [VEMR, belongsToICAORegionPrefix, VE]
-
A.
hasIcaoRegion
Indicates that an entity is associated with a specific ICAO (International Civil Aviation Organization) region.
-
B.
hasIcaoOrEquivalentCodeType
Indicates that an entity is associated with a specific ICAO or functionally equivalent code classification or type.
-
C.
ICAORegion
chosen
Indicates that an entity is located within, associated with, or governed by a specific ICAO (International Civil Aviation Organization) region.
-
D.
hasIcaoAirport
Indicates that an entity is associated with an airport identified by a specific ICAO (International Civil Aviation Organization) airport code.
-
E.
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.
- 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_69f76eacdd8c819094080d3991e6d37c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a000fda03948190881b7275f249768f |
completed | May 10, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_6a000f607f1881908ee750d58da91690 |
completed | May 10, 2026, 4:53 a.m. |
Created at: May 3, 2026, 4:16 p.m.