Triple
T127772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messerschmitt Bf 109 |
E2586
|
entity |
| Predicate | wingConfiguration |
P6541
|
FINISHED |
| Object | low-wing monoplane |
—
|
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: low-wing monoplane | Statement: [Messerschmitt Bf 109, wingConfiguration, low-wing monoplane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wingConfiguration Context triple: [Messerschmitt Bf 109, wingConfiguration, low-wing monoplane]
-
A.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
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.
landingGearType
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
D.
wingspan
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
-
E.
flightAbility
Indicates the capability or potential of an entity to fly or engage in powered or unpowered aerial movement.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25763ccf8819094e8dffb2ff98480 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.