Triple
T17709366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal F |
E441521
|
entity |
| Predicate | hasNumberOfRunwaysServed |
P2956
|
FINISHED |
| Object | multiple (via Boryspil 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: multiple (via Boryspil International Airport) | Statement: [Terminal F, hasNumberOfRunwaysServed, multiple (via Boryspil International Airport)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRunwaysServed Context triple: [Terminal F, hasNumberOfRunwaysServed, multiple (via Boryspil International Airport)]
-
A.
numberOfRunways
chosen
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
-
B.
hasRunwaysAt
Indicates that a location or facility possesses one or more runways situated at that place.
-
C.
isSingleRunwayForAirport
Indicates that a runway is the only (single) runway serving a particular airport.
-
D.
runwaysUsableAt
Indicates that certain runways at a location are available and suitable for use (e.g., for takeoff or landing) at a given time or under specified conditions.
-
E.
hasParallelRunway
Indicates that one runway is parallel in orientation and alignment to another 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47299cd7881908aac13b84acb61f7 |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:05 a.m.