Triple
T19017199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort McMurray International Airport |
E465382
|
entity |
| Predicate | runwayLength_07_25 |
P6291
|
FINISHED |
| Object | 2286 metres |
—
|
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: 2286 metres | Statement: [Fort McMurray International Airport, runwayLength_07_25, 2286 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayLength_07_25 Context triple: [Fort McMurray International Airport, runwayLength_07_25, 2286 metres]
-
A.
runwayLength
chosen
Indicates the length of a runway associated with an airport or airfield.
-
B.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
C.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
-
D.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
E.
runwayEnd
Indicates that one entity represents the end point or terminus of a runway associated with the other 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6dc0f9081909cddc5186603e885 |
completed | April 20, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.