Triple
T17928802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 35 |
E448269
|
entity |
| Predicate | hasRunwayDesignatorType |
P129756
|
FINISHED |
| Object | numeric |
—
|
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: numeric | Statement: [Runway 35, hasRunwayDesignatorType, numeric]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayDesignatorType Context triple: [Runway 35, hasRunwayDesignatorType, numeric]
-
A.
hasRunwayDesignationSide
Indicates that a runway designation is associated with a specific side or direction of the runway (e.g., left, right, or center).
-
B.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
C.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
D.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
E.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a5511a408190973cf5fa1f286a26 |
completed | April 19, 2026, 9:50 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:20 a.m.