Triple
T8037261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway A 16L/34R |
E187137
|
entity |
| Predicate | belongsToAirportType |
P16113
|
FINISHED |
| Object | international airport |
—
|
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: international airport | Statement: [Runway A 16L/34R, belongsToAirportType, international airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToAirportType Context triple: [Runway A 16L/34R, belongsToAirportType, international airport]
-
A.
belongsToAirport
Indicates that one entity is part of, associated with, or under the jurisdiction of a specific airport.
-
B.
associatedWithAirportType
chosen
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
C.
belongsToAirportSystem
Indicates that an airport is a member or component of a specific airport system or network.
-
D.
isLocatedAtAirportType
Indicates that one entity is situated at, or associated with, an airport of a specified type (e.g., international, regional, military).
-
E.
servesAirportType
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f188e1c8190b92760c91d31f2df |
completed | March 31, 2026, 3:27 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:23 p.m.