Triple
T28184124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BC |
E716120
|
entity |
| Predicate | airlineFleetModel |
P152831
|
FINISHED |
| Object | Boeing 737 family |
—
|
NE NERFINISHED |
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: Boeing 737 family | Statement: [BC, airlineFleetModel, Boeing 737 family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineFleetModel Context triple: [BC, airlineFleetModel, Boeing 737 family]
-
A.
airlineFleetManufacturer
Indicates that an airline’s fleet includes aircraft produced by a specific manufacturer.
-
B.
airlineFleetDesignation
Indicates the specific fleet or operational group within an airline to which an aircraft or service is assigned.
-
C.
airlineFleetCategory
Indicates the classification category of an airline based on the characteristics or size of its aircraft fleet.
-
D.
aircraftInFleet
Indicates that a particular aircraft is included as a member of a specified fleet.
-
E.
usedOnAirlineFleets
chosen
Indicates that something (typically an aircraft model or equipment) is operated as part of one or more airline fleets.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 10:21 p.m.