Triple
T8262507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun d'Or International Airlines |
E193226
|
entity |
| Predicate | fleetOwnershipModel |
P72672
|
FINISHED |
| Object | aircraft operated by El Al |
—
|
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: aircraft operated by El Al | Statement: [Sun d'Or International Airlines, fleetOwnershipModel, aircraft operated by El Al]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fleetOwnershipModel Context triple: [Sun d'Or International Airlines, fleetOwnershipModel, aircraft operated by El Al]
-
A.
ownershipModel
Indicates the type or structure of ownership relationship that governs how control, rights, or shares are held between entities.
-
B.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
C.
usesFleetOf
chosen
Indicates that one entity operates or relies on a group of vehicles, vessels, or similar assets collectively as a fleet to perform its activities or services.
-
D.
vehicleManufacturerHosted
Indicates that a vehicle manufacturer organized, sponsored, or served as the host for a particular event or activity.
-
E.
fleetNumbers
Indicates that there is an association between an entity and one or more identifying numbers assigned to it as part of a fleet.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7938723081909379cf78a4449b80 |
completed | March 31, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69cb36b8707881909aca349230495a5a |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:49 p.m.