Triple
T10443239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw Modlin Airport |
E246219
|
entity |
| Predicate | runwayLength_category |
P20697
|
FINISHED |
| Object | over 2500 m |
—
|
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: over 2500 m | Statement: [Warsaw Modlin Airport, runwayLength_category, over 2500 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayLength_category Context triple: [Warsaw Modlin Airport, runwayLength_category, over 2500 m]
-
A.
hasRunwayLengthCategory
chosen
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
-
B.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
C.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
D.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
E.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:15 p.m.