Triple
T8723340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Hierro Airport |
E207066
|
entity |
| Predicate | usesRunwayMetric |
P27404
|
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: [El Hierro Airport, usesRunwayMetric, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRunwayMetric Context triple: [El Hierro Airport, usesRunwayMetric, yes]
-
A.
usesRunwayOf
Indicates that one entity makes use of the runway that belongs to or is associated with another entity.
-
B.
usesMetricRunway
chosen
Indicates that a runway is measured, marked, or operated using metric units rather than imperial units.
-
C.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
D.
usesRunwayNumberingConvention
Indicates that an airport or runway follows a specific standardized system for assigning runway identification numbers.
-
E.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d0791208190b043332247372d7b |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:36 p.m.