Triple
T25430861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FUN |
E637248
|
entity |
| Predicate | airportRunwayUsedAsRecreationArea |
P159757
|
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: [FUN, airportRunwayUsedAsRecreationArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportRunwayUsedAsRecreationArea Context triple: [FUN, airportRunwayUsedAsRecreationArea, yes]
-
A.
airportRunwayUsedAsRoad
Indicates that an airport runway is being utilized as a road for vehicular traffic.
-
B.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
C.
runwayUsage
Indicates that a particular runway is being used or assigned for aircraft operations such as takeoffs or landings.
-
D.
runwayAdjacentTo
Indicates that a runway is directly next to or alongside another feature or area, with no significant separation between them.
-
E.
airfieldUsedDuring
Indicates that an airfield was in operational use during a specified time period or event.
- F. None of above. chosen
Provenance (4 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f7a205688190b8f36bff5013247c |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 21, 2026, 1:58 p.m.