Triple
T3913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John F. Kennedy International Airport |
E74
|
entity |
| Predicate | runwaySurface |
P422
|
FINISHED |
| Object | asphalt |
—
|
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: asphalt | Statement: [John F. Kennedy International Airport, runwaySurface, asphalt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwaySurface Context triple: [John F. Kennedy International Airport, runwaySurface, asphalt]
-
A.
largestAirport
Indicates that one airport is the largest (typically by area, traffic, or capacity) among a specified set or within a given region.
-
B.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
C.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
D.
adjacentToInfrastructure
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
E.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23bcc8eb48190b897cc331563980a |
completed | Feb. 28, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69a23994309081909ff3e869deef2156 |
completed | Feb. 28, 2026, 12:40 a.m. |
| PDg | Predicate description generation | batch_69a23bcb4bbc819093775f623998d62d |
completed | Feb. 28, 2026, 12:50 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.