Triple
T10746186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony |
E253453
|
entity |
| Predicate | eraOfAircraft |
P66519
|
FINISHED |
| Object | 1930s–1940s aviation |
—
|
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: 1930s–1940s aviation | Statement: [Tony, eraOfAircraft, 1930s–1940s aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eraOfAircraft Context triple: [Tony, eraOfAircraft, 1930s–1940s aviation]
-
A.
aircraftEra
chosen
Indicates the historical time period or era during which an aircraft was designed, produced, or primarily operated.
-
B.
aircraftGeneration
Indicates a generational relationship between aircraft, such as one model being a successor, predecessor, or belonging to a specific generation relative to another.
-
C.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
D.
isEarlyCommercialAircraftOf
Indicates that one entity is an early commercial aircraft model associated with, or belonging to the early commercial aviation phase of, another entity (such as an airline, manufacturer, or time period).
-
E.
aircraftMostAssociatedWith
Indicates the aircraft that is most strongly or commonly linked to, used by, or representative of a given entity compared to other 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d711b85d9c8190a66f536e2f22ed04 |
completed | April 9, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.