Triple
T4289396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winnipeg James Armstrong Richardson International Airport |
E97349
|
entity |
| Predicate | hasDeicingFacilities |
P24007
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Winnipeg James Armstrong Richardson International Airport, hasDeicingFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDeicingFacilities Context triple: [Winnipeg James Armstrong Richardson International Airport, hasDeicingFacilities, yes]
-
A.
hasRunwayDeicingFacilities
chosen
Indicates that the subject location or facility is equipped with infrastructure or systems specifically for deicing aircraft runways.
-
B.
hasSnowAndIce
Indicates that the subject is covered with or contains both snow and ice.
-
C.
hasIceSurface
Indicates that an entity possesses or is characterized by a surface composed primarily of ice.
-
D.
hasEmergencyAirstrip
Indicates that an entity possesses or includes an airstrip specifically designated and equipped for emergency use.
-
E.
hasSeaplaneFacilities
Indicates that a location or facility provides infrastructure and services specifically for the operation, docking, or handling of seaplanes.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35061f5448190b3356b29a9129160 |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.