Triple
T5755392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liuzhou Bailian Airport |
E126952
|
entity |
| Predicate | hasMetricRunway |
P27404
|
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: [Liuzhou Bailian Airport, hasMetricRunway, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetricRunway Context triple: [Liuzhou Bailian Airport, hasMetricRunway, true]
-
A.
usesMetricRunway
chosen
Indicates that a runway is measured, marked, or operated using metric units rather than imperial units.
-
B.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
-
C.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
-
D.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
E.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02906848c8190bf7b0d62f57c27fa |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021cc68648190bb86d049ebe80f12 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:49 p.m.