Triple
T5516884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KPUB |
E144705
|
entity |
| Predicate | hasTaxiways |
P59863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [KPUB, hasTaxiways, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTaxiways Context triple: [KPUB, hasTaxiways, true]
-
A.
hasTaxiway
chosen
Indicates that an airport or runway is connected to or served by a taxiway used for aircraft ground movement.
-
B.
numberOfRunways
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
-
C.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
D.
hasRunwayAccessVia
Indicates that an entity has access to a runway by means of a specified connecting route, facility, or intermediary.
-
E.
hasRunwayAccessTo
Indicates that one location or facility is directly connected to another via a usable runway, allowing aircraft to move between them without leaving runway infrastructure.
- 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f5e8ce08190b7f5f2131bebcd4f |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:33 p.m.