Triple
T15502364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 16/34 at Westchester County Airport |
E378991
|
entity |
| Predicate | hasLengthFeet |
P118899
|
FINISHED |
| Object | 6549 |
—
|
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: 6549 | Statement: [Runway 16/34 at Westchester County Airport, hasLengthFeet, 6549]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthFeet Context triple: [Runway 16/34 at Westchester County Airport, hasLengthFeet, 6549]
-
A.
heightFeet
Indicates a relationship where a subject has its vertical size or stature specified in feet as a unit of measurement.
-
B.
heightApproximateFeet
Indicates that one entity’s height is approximately equal to a specified value measured in feet.
-
C.
feetFeature
Indicates that one entity has a specific characteristic, attribute, or notable aspect related to its feet.
-
D.
archLength
Indicates the measured length of an arch-shaped structure or path between two defined points.
-
E.
depthFeetApprox
Indicates an approximate measurement of an entity’s depth expressed in feet.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcc5bb88190b8a9a81419a9a38b |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:54 a.m.