Triple
T12294493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Embraer 195 |
E293047
|
entity |
| Predicate | typicalCabinCrew |
P104313
|
FINISHED |
| Object | 2 to 4 flight attendants |
—
|
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: 2 to 4 flight attendants | Statement: [Embraer 195, typicalCabinCrew, 2 to 4 flight attendants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCabinCrew Context triple: [Embraer 195, typicalCabinCrew, 2 to 4 flight attendants]
-
A.
coCrewMember
Indicates that two or more individuals serve together as members of the same crew on a shared mission, vehicle, or operation.
-
B.
cabinCrewBrand
Indicates a relationship where a cabin crew member is associated with or represents a particular airline brand.
-
C.
typicalPilotPosition
Indicates the usual or standard spatial position or placement where a pilot is located relative to the associated object or system.
-
D.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
E.
internationalCrewMember
Indicates that an individual is a member of a crew composed of people from more than one country.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:52 p.m.