Triple
T10746177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony |
E253453
|
entity |
| Predicate | aircraftIntroducedOfAircraft |
P95768
|
FINISHED |
| Object | 1942 |
—
|
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: 1942 | Statement: [Tony, aircraftIntroducedOfAircraft, 1942]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftIntroducedOfAircraft Context triple: [Tony, aircraftIntroducedOfAircraft, 1942]
-
A.
aircraftModelProduced
Indicates that a specific aircraft model has been manufactured or produced by a particular entity (such as a company or organization).
-
B.
firstAircraftName
Indicates the name assigned to the first aircraft associated with a given entity or context.
-
C.
firstFlightOnType
Indicates that an entity represents the first flight event conducted with a particular aircraft type or model.
-
D.
firstJetAirlinerInServiceFor
Indicates that the subject is the first jet airliner ever to enter commercial service for the specified operator or context.
-
E.
developedAircraft
Indicates that an entity (such as a person or organization) was responsible for designing, creating, or engineering a particular aircraft.
- 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_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. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:15 p.m.