Triple
T8630791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A220-100 |
E204394
|
entity |
| Predicate | designedForAirports |
P84518
|
FINISHED |
| Object | noise-sensitive airports |
—
|
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: noise-sensitive airports | Statement: [A220-100, designedForAirports, noise-sensitive airports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedForAirports Context triple: [A220-100, designedForAirports, noise-sensitive airports]
-
A.
appliesToAirport
Indicates that something is relevant, valid, or specifically intended for use at a particular airport.
-
B.
aircraftFacility
Indicates that a facility is designed, equipped, or used to support the operation, maintenance, or accommodation of aircraft.
-
C.
isLocatedAtAirportType
Indicates that one entity is situated at, or associated with, an airport of a specified type (e.g., international, regional, military).
-
D.
airportSpecialization
Indicates that an airport is specialized or designated for a particular primary function, service type, or category of operations.
-
E.
hubAirport
Indicates that an airport serves as a primary hub or central operating base for a particular airline or carrier.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:27 p.m.