Triple
T4118259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stratolaunch carrier aircraft |
E90345
|
entity |
| Predicate | numberOfMainLandingGearLegs |
P54378
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Stratolaunch carrier aircraft, numberOfMainLandingGearLegs, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainLandingGearLegs Context triple: [Stratolaunch carrier aircraft, numberOfMainLandingGearLegs, 12]
-
A.
landingGearType
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
B.
landingGear
Indicates that an entity’s landing gear is present, deployed, or otherwise involved in a landing-related state or action relative to another entity or context.
-
C.
numberOfRoadWheelsPerSide
Indicates the count of road wheels present on each side of a vehicle or similar wheeled system.
-
D.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
-
E.
wheelCount
Indicates the number of wheels associated with a given 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0245adbc81908b89a40850047975 |
completed | March 9, 2026, 5:24 p.m. |
Created at: March 9, 2026, 3:41 p.m.