Triple
T1180783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flightplan |
E25130
|
entity |
| Predicate | hasAircraftTypeInStory |
P1524
|
FINISHED |
| Object | fictional E-474 airliner |
—
|
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: fictional E-474 airliner | Statement: [Flightplan, hasAircraftTypeInStory, fictional E-474 airliner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftTypeInStory Context triple: [Flightplan, hasAircraftTypeInStory, fictional E-474 airliner]
-
A.
aircraftType
chosen
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
hasAircraftOnDisplay
Indicates that an entity exhibits or presents an aircraft as part of a display or collection.
-
C.
isHelicopterOf
Indicates that one entity is a helicopter that belongs to, is operated by, or is otherwise associated with another entity.
-
D.
aircraftTypesCarried
Indicates that one entity (typically a vessel, facility, or platform) carries or is capable of carrying specific types of aircraft as part of its operations or configuration.
-
E.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd32c5f48190b4e2d39fa052cbb7 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb59ca6c81908597a81646674aaa |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.