Triple
T27938288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SouthJet Flight 227 |
E700670
|
entity |
| Predicate | aircraftTypeInFiction |
P1524
|
FINISHED |
| Object | commercial jet 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: commercial jet airliner | Statement: [SouthJet Flight 227, aircraftTypeInFiction, commercial jet airliner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTypeInFiction Context triple: [SouthJet Flight 227, aircraftTypeInFiction, commercial jet airliner]
-
A.
usesFictionalAircraftType
Indicates that an entity makes use of, operates, or features a type of aircraft that is fictional rather than real.
-
B.
portraysAircraft
Indicates that one entity visually represents or depicts an aircraft in some medium or form.
-
C.
fighterType
Indicates the specific combat or fighting style category that an entity belongs to.
-
D.
aircraftType
chosen
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
poweredAircraftType
Indicates that one entity is a type or category of aircraft that is propelled by an onboard power source (e.g., engines), as opposed to being unpowered.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 7:15 p.m.