Triple
T1191431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Airlines |
E25368
|
entity |
| Predicate | aircraftConfigurationBuilt |
P19270
|
FINISHED |
| Object | single-engine 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: single-engine monoplane | Statement: [Ryan Airlines, aircraftConfigurationBuilt, single-engine monoplane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftConfigurationBuilt Context triple: [Ryan Airlines, aircraftConfigurationBuilt, single-engine monoplane]
-
A.
aircraftConfigurationProduced
chosen
Indicates that a specific aircraft configuration has been manufactured or produced.
-
B.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
C.
aircraftBuilder
Indicates that one entity is the manufacturer or constructor responsible for building the aircraft represented by the other entity.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
hasWingConfiguration
Indicates how an entity’s wings are arranged, structured, or configured relative to its body or to each other.
- F. None of above.
Provenance (3 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd74e2c08190b4a48425f94addaa |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.